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{{primary sources|date=January 2022}}

{{Short description|Transactional distributed SQL database}}
{{Short description|Transactional distributed SQL database}}
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{{AfDM|page=YugabyteDB (2nd nomination)|year=2022|month=January|day=11|substed=yes|origtag=afdx|help=off}}
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{{Infobox software
{{Infobox software
| title =
| title =
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| developer = Yugabyte, Inc.
| developer = Yugabyte, Inc.
| released = {{Start date and age|2016}}
| released = {{Start date and age|2016}}
| latest release version = 2.8 (Stable)<br> 2.11 (Development)
| latest release version = 2.20 (Stable)<br> 2.19 (Development)
| latest release date = {{Start date and age|2021|11|18}}<br> {{Start date and age|2021|11|23}}
| latest release date = {{Start date and age|2024|01|25}}<br> {{Start date and age|2023|10|25}}
| programming language = [[C++]]
| programming language = [[C++]]
| operating system = Linux RedHat 7.x and derivatives, MacOS
| operating system = Linux RedHat 7.x and derivatives, MacOS
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==History==
==History==
Yugabyte was founded by ex-[[Facebook]] engineers Kannan Muthukkaruppan, Karthik Ranganathan, and Mikhail Bautin. At Facebook, they were part of the team that built and operated [[Apache Cassandra|Cassandra]] and [[Apache HBase|HBase]].<ref>{{cite web |title=Karthik Ranganathan |url=https://www.dataversity.net/contributors/karthik-ranganathan/ |website=Dataversity |access-date=30 December 2021}}</ref><ref>{{cite web |title=Apache hadoop goes realtime at Facebook |url=https://dl.acm.org/doi/abs/10.1145/1989323.1989438 |website=Association For Computer Machinery |access-date=15 January 2022}}</ref> The team scaled the data platform for massive real-time workloads such as Facebook [[Messenger (software)|Messenger]] and Facebook's [[Operational Data Store]] from millions to billions of users in just a few years.<ref>{{cite web |title=YugaByte Raises $8M in Series A Funding |access-date=30 December 2021|url=https://www.finsmes.com/2017/11/yugabyte-raises-8m-in-series-a-funding.html |website=FINSMES}}</ref>
Yugabyte was founded by ex-[[Facebook]] engineers Kannan Muthukkaruppan, Karthik Ranganathan, and Mikhail Bautin. At Facebook, they were part of the team that built and operated [[Apache Cassandra|Cassandra]] and [[Apache HBase|HBase]]<ref>{{cite web |title=Karthik Ranganathan |url=https://www.dataversity.net/contributors/karthik-ranganathan/ |website=Dataversity |access-date=30 December 2021}}</ref><ref>{{cite book |url=https://dl.acm.org/doi/abs/10.1145/1989323.1989438 |website=Association For Computer Machinery |year=2011 |doi=10.1145/1989323.1989438 |access-date=15 January 2022|last1=Borthakur |first1=Dhruba |last2=Rash |first2=Samuel |last3=Schmidt |first3=Rodrigo |last4=Aiyer |first4=Amitanand |last5=Gray |first5=Jonathan |last6=Sarma |first6=Joydeep Sen |last7=Muthukkaruppan |first7=Kannan |last8=Spiegelberg |first8=Nicolas |last9=Kuang |first9=Hairong |last10=Ranganathan |first10=Karthik |last11=Molkov |first11=Dmytro |last12=Menon |first12=Aravind |title=Proceedings of the 2011 ACM SIGMOD International Conference on Management of data |chapter=Apache hadoop goes realtime at Facebook |page=1071 |isbn=9781450306614 |s2cid=207188340 }}</ref> for workloads such as Facebook [[Messenger (software)|Messenger]] and Facebook's [[Operational Data Store]].<ref>{{cite web |title=YugaByte Raises $8M in Series A Funding |access-date=30 December 2021|url=https://www.finsmes.com/2017/11/yugabyte-raises-8m-in-series-a-funding.html |website=FINSMES|date=2 November 2017 }}</ref>


The founders came together in February 2016 to build YugabyteDB,<ref>{{cite web |title=Yugabyte CTO outlines a PostgreSQL path to distributed cloud |url=https://venturebeat.com/2021/07/26/yugabyte-cto-outlines-a-postgresql-path-to-distributed-cloud/ |website=VentureBeat |access-date=31 December 2021}}</ref> believing that the trends they experienced at Facebook – [[microservices]], [[Containerization (computing)|containerization]], [[High-availability cluster|high availability]], geographic distribution, [[API]]s, and [[Open-source software|open-source]] – were relevant to all businesses, especially as they move from on-premise to cloud-native operations.<ref>{{cite web |title=Yugabyte expands its fully managed enterprise cloud service with $188M |access-date=30 December 2021|url=https://venturebeat.com/2021/10/28/yugabyte-expands-its-fully-managed-enterprise-cloud-service-with-188m/ |website=VentureBeat}}</ref>
The founders came together in February 2016 to build YugabyteDB.<ref>{{cite web |title=Yugabyte CTO outlines a PostgreSQL path to distributed cloud |url=https://venturebeat.com/2021/07/26/yugabyte-cto-outlines-a-postgresql-path-to-distributed-cloud/ |website=VentureBeat |date=26 July 2021 |access-date=31 December 2021}}</ref><ref>{{cite web |title=Yugabyte expands its fully managed enterprise cloud service with $188M |access-date=30 December 2021|url=https://venturebeat.com/2021/10/28/yugabyte-expands-its-fully-managed-enterprise-cloud-service-with-188m/ |website=VentureBeat|date=28 October 2021 }}</ref>


YugabyteDB was initially available in two editions: community and enterprise. In July 2019, Yugabyte open sourced previously commercial features and launched YugabyteDB as 100% open-source under the [[Apache License|Apache]] 2.0 license.
YugabyteDB was initially available in two editions: community and enterprise. In July 2019, Yugabyte open-sourced previously commercial features and launched YugabyteDB as open-source under the [[Apache License|Apache]] 2.0 license.<ref>{{cite web |title=Yugabyte Expands Multi-Region Database Capabilities and Enterprise-Grade Security with YugabyteDB 2.5 |url=https://www.businesswire.com/news/home/20201112005160/en/Yugabyte-Expands-Multi-Region-Database-Capabilities-and-Enterprise-Grade-Security-with-YugabyteDB-2.5 |website=businesswire.com |date=12 November 2020 |access-date=30 November 2024}}</ref>

The rapid evolution of the product led to being named as a 2020 [[Gartner]] Cool Vendor in Data Management.<ref>{{cite web |title=Yugabyte Named a 2020 Gartner Cool Vendor in Data Management |url=https://www.businesswire.com/news/home/20201102005567/en/Yugabyte-Named-a-2020-Gartner-Cool-Vendor-in-Data-Management |website=BusinessWire |access-date=30 December 2021}}</ref>

Yugabyte launched Yugabyte Cloud,<ref>{{cite web |title=Yugabyte Cloud: a Managed Distributed SQL Database |url=https://www.infoq.com/news/2021/10/yugabyte-cloud/ |website=InfoQ |access-date=31 December 2021}}</ref> a fully managed [[Cloud database|database-as-a-service]] offering of YugabyteDB, in September 2021.<ref>{{cite web |title=Yugabyte Delivers Effortless Distributed SQL With Cloud Database-as-a-Service |url=https://www.businesswire.com/news/home/20210921005390/en/Yugabyte-Delivers-Effortless-Distributed-SQL-With-Cloud-Database-as-a-Service |website=BusinessWire |access-date=30 December 2021}}</ref> Yugabyte Cloud combines the power of distributed SQL with the ease of use of a cloud database management system.


=== Funding ===
=== Funding ===
⚫
In October 2021, five years after the company's inception, Yugabyte closed a $188 Million Series C funding round to become a [[Unicorn (finance)|Unicorn]] start-up with a valuation of $1.3Bn<ref>{{cite web |title=Another cloud native SQL database unicorn: Yugabyte raises $188M Series C funding at $1.3B valuation |url=https://www.zdnet.com/article/another-globally-distributed-cloud-native-sql-database-unicorn-yugabyte-raises-188m-series-c-funding-at-1-3b-valuation/ |website=ZDNet |access-date=12 January 2022}}</ref>

⚫
Only 6 years after the company inception Yugabyte closed a $188 Million Series C finding round to became a [[Unicorn (finance)|Unicorn]] start-up with a valuation of $1.3Bn<ref>{{cite web |title=Another cloud native SQL database unicorn: Yugabyte raises $188M Series C funding at $1.3B valuation |url=https://www.zdnet.com/article/another-globally-distributed-cloud-native-sql-database-unicorn-yugabyte-raises-188m-series-c-funding-at-1-3b-valuation/ |website=ZDNet |access-date=12 January 2022}}</ref>


{| class="wikitable"
{| class="wikitable"
Line 64: Line 58:
| 10 Feb 2016
| 10 Feb 2016
| $8M
| $8M
| [[Lightspeed Venture Partners]], Jeff Rothschild<ref>{{cite web |title=YugaByte Raises $8M in Series A Funding |url=http://www.finsmes.com/2017/11/yugabyte-raises-8m-in-series-a-funding.html |website=Finsmes}}</ref><ref>{{cite web |title=YugaByte Receives $8M Series A Round |url=http://www.vcnewsdaily.com/yugabyte/venture-capital-funding/rvcdzhbtxd |website=VC News Daily |access-date=12 January 2022}}</ref>
| [[Lightspeed Venture Partners]], Jeff Rothschild<ref>{{cite web |title=YugaByte Raises $8M in Series A Funding |url=http://www.finsmes.com/2017/11/yugabyte-raises-8m-in-series-a-funding.html |website=Finsmes|date=2 November 2017 }}</ref><ref>{{cite web |title=YugaByte Receives $8M Series A Round |url=http://www.vcnewsdaily.com/yugabyte/venture-capital-funding/rvcdzhbtxd |website=VC News Daily |access-date=12 January 2022}}</ref>
|-
|-
| A
| A
| 12 Jun 2018
| 12 Jun 2018
| $16M
| $16M
| Lightspeed Venture Partners, Dell Technology Capital<ref>{{cite web |title=YugaByte raises $16 Million to combine SQL and NoSQL in a single database |url=https://technologies.org/yugabyte-raises-16-million-to-combine-sql-and-nosql-in-a-single-database/ |website=Technologies.org |access-date=12 January 2022}}</ref><ref>{{cite web |title=YugaByte’s new database software rakes in $16 million so developers can move to any cloud |url=https://techcrunch.com/2018/06/12/yugabytes-new-database-software-rakes-in-16-million-so-developers-can-move-to-any-cloud/ |website=TechCrunch |access-date=12 January 2022}}</ref>
| Lightspeed Venture Partners, Dell Technology Capital<ref>{{cite web |title=YugaByte raises $16 Million to combine SQL and NoSQL in a single database |url=https://technologies.org/yugabyte-raises-16-million-to-combine-sql-and-nosql-in-a-single-database/ |website=Technologies.org |access-date=12 January 2022}}</ref><ref>{{cite web |title=YugaByte's new database software rakes in $16 million so developers can move to any cloud |url=https://techcrunch.com/2018/06/12/yugabytes-new-database-software-rakes-in-16-million-so-developers-can-move-to-any-cloud/ |website=TechCrunch |date=12 June 2018 |access-date=12 January 2022}}</ref>
|-
|-
| B
| B
| 09 Jun 2020
| 09 Jun 2020
| $30M
| $30M
| [[Wipro]] Ventures, Lightspeed Venture Partners. Dell Technology Capital. 8VC <ref>{{cite web |title=Another globally distributed cloud native SQL database on the rise: Yugabyte Raises $30 million in Series B Funding |url=https://zd.net/3dOJNIy |website=ZDNet |access-date=12 January 2022}}</ref><ref>{{cite web |title=Yugabyte raises $30M for its cloud-native distributed SQL database |url=https://siliconangle.com/2020/06/09/yugabyte-raises-30m-cloud-native-distributed-sql-database/ |website=SiliconAngle |access-date=12 January 2022}}</ref>
| [[Wipro]] Ventures, Lightspeed Venture Partners. Dell Technology Capital. 8VC <ref>{{cite web |title=Another globally distributed cloud native SQL database on the rise: Yugabyte Raises $30 million in Series B Funding |url=https://zd.net/3dOJNIy |website=ZDNet |access-date=12 January 2022}}</ref><ref>{{cite web |title=Yugabyte raises $30M for its cloud-native distributed SQL database |url=https://siliconangle.com/2020/06/09/yugabyte-raises-30m-cloud-native-distributed-sql-database/ |website=SiliconAngle |date=9 June 2020 |access-date=12 January 2022}}</ref>
|-
|-
| B
| B
| 03 Mar 2021
| 03 Mar 2021
| $48M
| $48M
| Wipro Ventures. Lightspeed Venture Partners. Greenspring Associates, Dell Technology Capital, 8VC<ref>{{cite web |title=Yugabyte raises $48M for open source SQL database alternative |url=https://venturebeat.com/2021/03/03/yugabyte-raises-48m-for-open-source-sql-database-alternative/ |website=VentureBeat |access-date=12 January 2022}}</ref><ref>{{cite web |title=Yugabyte Raises $48 Million Funding Round to Accelerate Distributed SQL Enterprise Adoption and Fuel Global Expansion |url=https://finance.yahoo.com/news/yugabyte-raises-48-million-funding-140000688.html |website=YahoonFinance |access-date=12 January 2022}}</ref>
| Wipro Ventures. Lightspeed Venture Partners. Greenspring Associates, Dell Technology Capital, 8VC<ref>{{cite web |title=Yugabyte raises $48M for open source SQL database alternative |url=https://venturebeat.com/2021/03/03/yugabyte-raises-48m-for-open-source-sql-database-alternative/ |website=VentureBeat |date=3 March 2021 |access-date=12 January 2022}}</ref><ref>{{cite web |title=Yugabyte Raises $48 Million Funding Round to Accelerate Distributed SQL Enterprise Adoption and Fuel Global Expansion |url=https://finance.yahoo.com/news/yugabyte-raises-48-million-funding-140000688.html |website=YahoonFinance |access-date=12 January 2022}}</ref>
|-
|-
| C
| C
| 28 Oct 2021
| 28 Oct 2021
| $188M
| $188M
| Wells Fargo Strategic Capital, [[Sapphire Ventures]], [[Meritech Capital Partners]], Lightspeed Venture Partners, Dell Technology Capital, 8VC<ref>{{cite web |title=Yugabyte's latest funding round values the distributed SQL system at $1.3bn |url=https://go.theregister.com/feed/www.theregister.com/2021/10/29/yugabyte_series_c/ |website=The Register |access-date=12 January 2022}}</ref><ref>{{cite web |title=Another cloud native SQL database unicorn: Yugabyte raises $188M Series C funding at $1.3B valuation |url=https://www.zdnet.com/article/another-globally-distributed-cloud-native-sql-database-unicorn-yugabyte-raises-188m-series-c-funding-at-1-3b-valuation/ |website=ZDNet |access-date=12 January 2022}}</ref><ref>{{cite web |title=High-performance database startup Yugabyte raises $188M in new funding round |url=https://siliconangle.com/2021/10/28/high-performance-database-startup-yugabyte-raises-188m-series-c-funding-round/ |website=Silicon Angle |access-date=12 January 2022}}</ref>
| Wells Fargo Strategic Capital, [[Sapphire Ventures]], [[Meritech Capital Partners]], Lightspeed Venture Partners, Dell Technology Capital, 8VC<ref>{{cite web |title=Yugabyte's latest funding round values the distributed SQL system at $1.3bn |url=https://go.theregister.com/feed/www.theregister.com/2021/10/29/yugabyte_series_c/ |website=The Register |access-date=12 January 2022}}</ref><ref>{{cite web |title=Another cloud native SQL database unicorn: Yugabyte raises $188M Series C funding at $1.3B valuation |url=https://www.zdnet.com/article/another-globally-distributed-cloud-native-sql-database-unicorn-yugabyte-raises-188m-series-c-funding-at-1-3b-valuation/ |website=ZDNet |access-date=12 January 2022}}</ref><ref>{{cite web |title=High-performance database startup Yugabyte raises $188M in new funding round |url=https://siliconangle.com/2021/10/28/high-performance-database-startup-yugabyte-raises-188m-series-c-funding-round/ |website=Silicon Angle |date=28 October 2021 |access-date=12 January 2022}}</ref>
|}
|}

==Features==

YugabyteDB has the following key features:
* [[Scalability#HORIZONTAL-SCALING|Horizontally scaling]] from 3 nodes upward<ref>{{cite web |title=Horizontal Scalability |url=https://docs.yugabyte.com/latest/explore/linear-scalability/ |website=Yugabyte}}</ref><ref>{{cite web |title=How YugabyteDB Scales to More than 1 Million Inserts Per Sec |url=https://medium.com/yugabyte/how-yugabytedb-scales-to-more-than-1-million-inserts-per-sec-the-distributed-sql-blog-2a1410647321 |website=Medium}}</ref>
* Deploy a database instance across multiple failure zones (rack, availability zone, cloud region) in order to survive an outage at the failure zone level
* Enterprise-grade security for [[Data at rest]], [[Data in transit|Data in motion]], Field-level encryption, Authentication, and Authorisation as well as appropriate audit logging
* Code compatibility with [[PostgreSQL]] by reusing PostgreSQL's query layer to achieve a high degree of compatibility with existing PostgreSQL applications including triggers, functions, stored procedures, strong secondary indexes, and distributed ACID transactions.
* Geo-placement of data - the ability to limit data to a given location or set of locations
* Asynchronous replication between database instances
* Cloud Agnostic - running on-premise, in [[Amazon Web Services]] (AWS), [[Microsoft Azure]], and [[Google Cloud Platform]] (GCP) to avoid [[vendor lock-in]] on a single cloud provider
* Support for Hybrid (on-premise and in the cloud) or Multi-cloud (across multiple cloud vendors) deployments
* [[Rolling release]] allowing the database to be upgraded without taking it down

== Use cases ==

Yugabyte, in common with other transactional distributed SQL databases, is best suited to supporting:
* [[System of record|System of Record]] i.e. the main transactional systems of an organization, these would typically include applications such as shopping carts, IoT event stores, bank transactions, etc.
* System of Reference or [[Master Data Management]] systems used to store items such as product catalogs and other reference data.

System of Analysis (such as a [[Data warehouse]]) use cases are NOT good use cases for any distributed SQL database<ref>{{Cite web|title=Distributed Database Systems: The Case for NewSQL|url=https://hal-lirmm.ccsd.cnrs.fr/lirmm-03228968/document|url-status=live|access-date=4 January 2022|website=HAL-LIRMM Archive}}</ref> Analytical queries generally collect a large amount of data in a single query and doing this in a distributed SQL database is prone to significant latency due to the distributed nature of the data store.

As a result, early adoption of distributed SQL databases such as YugabyteDB has been in [[Retail]], [[Telephone company|Telcos]], [[FinTech]] and [[Internet of things|IoT]] vertical segments which are characterized by having high-volume, transactional data that needs to be highly available as they are mission-critical to the organization.


== Architecture ==
== Architecture ==


YugabyteDB is a distributed SQL database that is strongly transactionally consistent across failure zones (i.e. [[ACID]] compliance]<ref>{{cite web |title=ACID Transactions |url=https://devopedia.org/acid-transactions |website=Devopedia |access-date=12 January 2022}}</ref><ref>{{cite web |title=ICT SOLUTIONS FOR LOCAL FLEXIBILITY MARKETS |url=https://www.conferenceie.ase.ro/wp-content/uploads/2020/06/ProceedingsIE2020/ict_solutions_for_local_flexibility_markets.pdf |website=Academia de Studii Economice din Bucuresti |publisher=Proceedings of the IE 2020 International Conference |access-date=15 January 2022}}</ref> as demonstrated by Jepsen testing.<ref>{{cite web |title=YugaByte DB 1.3.1 |url=https://jepsen.io/analyses/yugabyte-db-1.3.1 |access-date=30 December 2021|website=Jepsen.io}}</ref> In [[CAP Theorem]] terms YugabyteDB is a Consistent/Partition Tolerant (CP) database.<ref>{{cite web |title=YugaByteDB: A Distributed Cloud Native Database for a Highly Scalable Data Store |url=https://www.opensourceforu.com/2020/09/yugabytedb-a-distributed-cloud-native-database-for-a-highly-scalable-data-store/ |website=Open Source Foru |access-date=15 January 2022}}</ref><ref>{{cite web |title=Yugabyte Design Goals |url=https://docs.yugabyte.com/latest/architecture/design-goals/ |website=Yugabyte.com |access-date=15 January 2022}}</ref>
YugabyteDB is a distributed SQL database that aims to be strongly transactionally consistent across failure zones (i.e. [[ACID]] compliance].<ref>{{cite web |title=ACID Transactions |url=https://devopedia.org/acid-transactions |website=Devopedia |date=18 August 2019 |access-date=12 January 2022}}</ref><ref>{{cite web |title= ICT Solutions for local flexibility markets |url=https://www.conferenceie.ase.ro/wp-content/uploads/2020/06/ProceedingsIE2020/ict_solutions_for_local_flexibility_markets.pdf |website=Academia de Studii Economice din Bucuresti |publisher=Proceedings of the IE 2020 International Conference |access-date=15 January 2022}}</ref> Jepsen testing, the ''de facto'' industry standard for verifying correctness, has never fully passed, mainly due to race conditions during schema changes.<ref>{{cite web |title=YugaByte DB 1.3.1 |url=https://jepsen.io/analyses/yugabyte-db-1.3.1 |access-date=30 December 2021|website=Jepsen.io}}</ref> In [[CAP Theorem]] terms YugabyteDB is a Consistent/Partition Tolerant (CP) database.<ref>{{cite web |title=YugaByteDB: A Distributed Cloud Native Database for a Highly Scalable Data Store |url=https://www.opensourceforu.com/2020/09/yugabytedb-a-distributed-cloud-native-database-for-a-highly-scalable-data-store/ |website=Open Source Foru |date=14 September 2020 |access-date=15 January 2022}}</ref><ref>{{cite web |title=Yugabyte Design Goals |url=https://docs.yugabyte.com/latest/architecture/design-goals/ |website=Yugabyte.com |access-date=15 January 2022}}</ref><ref>{{cite journal |title=A Generic and Extensible Core and Prototype of Consistent, Distributed, and Resilient LIS |year=2020 |doi=10.3390/ijgi9070437 |doi-access=free |last1=Galić |first1=Zdravko |last2=Vuzem |first2=Mario |journal=ISPRS International Journal of Geo-Information |volume=9 |issue=7 |page=437 |bibcode=2020IJGI....9..437G }}</ref>


YugabyteDB has two layers<ref>{{cite web |title=Yugabyte Layered Architecture |url=https://docs.yugabyte.com/latest/architecture/layered-architecture/ |website=Yugabyte |access-date=15 January 2022}}</ref>, a storage engine known as DocDB and the Yugabyte Query Layer<ref name="ntnu">{{cite web |last1=Hirsch |first1=Orhan Henrik |title=Scalability of NewSQL Databases in a Cloud Environment |url=https://ntnuopen.ntnu.no/ntnu-xmlui/bitstream/handle/11250/2777732/no.ntnu%3ainspera%3a57320302%3a31535683.pdf?sequence=1&isAllowed=y |website=Norwegian University of Science and Technology |publisher=NYNU Open |access-date=15 January 2022}}</ref>.
YugabyteDB has two layers,<ref>{{cite web |title=Yugabyte Layered Architecture |url=https://docs.yugabyte.com/latest/architecture/layered-architecture/ |website=Yugabyte |access-date=15 January 2022}}</ref> a storage engine known as DocDB and the Yugabyte Query Layer.<ref name="ntnu">{{cite web |last1=Hirsch |first1=Orhan Henrik |title=Scalability of NewSQL Databases in a Cloud Environment |url=https://ntnuopen.ntnu.no/ntnu-xmlui/bitstream/handle/11250/2777732/no.ntnu%3ainspera%3a57320302%3a31535683.pdf?sequence=1&isAllowed=y |website=Norwegian University of Science and Technology |publisher=NYNU Open |access-date=15 January 2022}}</ref>


[[File:YugabyteDBArchitecture.png|thumb|alt=Architecture Block Diagram for YugabyteDB|YugabyteDB Architecture]]
[[File:YugabyteDBArchitecture.png|thumb|alt=Architecture Block Diagram for YugabyteDB|YugabyteDB Architecture]]
Line 120: Line 91:
=== DocDB ===
=== DocDB ===


The storage engine consists of a customized [[RocksDB]]<ref name="ntnu" /><ref name="sisu" /> combined with sharding and load balancing algorithms for the data. In addition, the [[Raft (algorithm)|Raft consensus algorithm]] controls the replication of data between the nodes.<ref name="ntnu" /><ref name="sisu" /> There is also a [[Distributed transaction]] manager<ref name="ntnu" /><ref name="sisu" /> and [[Multiversion concurrency control]] (MVCC)<ref name="ntnu" /><ref name="sisu" /> to support distributed transactions<ref name="sisu">{{cite web |last1=Budholia |first1=Akash |title=NewSQL Monitoring System |url=https://scholarworks.sjsu.edu/cgi/viewcontent.cgi?article=1996&context=etd_projects |website=San Jose State University Scholar Works |access-date=15 January 2022}}</ref>.
The storage engine consists of a customized [[RocksDB]]<ref name="ntnu" /><ref name="sisu" /> combined with sharding and load balancing algorithms for the data. In addition, the [[Raft (algorithm)|Raft consensus algorithm]] controls the replication of data between the nodes.<ref name="ntnu" /><ref name="sisu" /> There is also a [[Distributed transaction]] manager<ref name="ntnu" /><ref name="sisu" /> and [[Multiversion concurrency control]] (MVCC)<ref name="ntnu" /><ref name="sisu" /> to support distributed transactions.<ref name="sisu">{{cite web |last1=Budholia |first1=Akash |title=NewSQL Monitoring System |url=https://scholarworks.sjsu.edu/cgi/viewcontent.cgi?article=1996&context=etd_projects |website=San Jose State University Scholar Works |access-date=15 January 2022}}</ref>


The engine also exploits a Hybrid Logical Clock<ref>{{cite web |title=Hybrid Clock |url=https://martinfowler.com/articles/patterns-of-distributed-systems/hybrid-clock.html |website=Martin Fowler |access-date=30 December 2021}}</ref><ref name="ntnu" /> that combines coarsely-synchronized physical clocks with [[Lamport timestamp|Lamport clocks]] to track causal relationships.
The engine also exploits a Hybrid Logical Clock<ref>{{cite web |title=Hybrid Clock |url=https://martinfowler.com/articles/patterns-of-distributed-systems/hybrid-clock.html |website=Martin Fowler |access-date=30 December 2021}}</ref><ref name="ntnu" /> that combines coarsely-synchronized physical clocks with [[Lamport timestamp|Lamport clocks]] to track causal relationships.<ref>{{cite web |title=Distributed Transactions without Atomic Clocks |url=https://www.yugabyte.com/wp-content/uploads/2021/05/Distributed-Transactions-Without-Atomic-Clocks.pdf |website=Yugabyte |access-date=15 January 2022}}</ref>


The DocDB layer is not directly accessible by users<ref name="ntnu" />.
The DocDB layer is not directly accessible by users.<ref name="ntnu" />


=== YugabyteDB Query Layer ===
=== YugabyteDB Query Layer ===


Yugabyte has a pluggable query layer that abstracts the query layer from the storage layer below. There are currently two APIs that can access the database:
Yugabyte has a pluggable query layer that abstracts the query layer from the storage layer below.<ref>{{cite web |title=Yugabyte DB 2.0 Ships Production-Ready Distributed SQL Database for Going Cloud Native |url=https://www.idevnews.com/stories/7298/Yugabyte-DB-20-Ships-Production-Ready-Distributed-SQL-Database-for-Going-Cloud-Native |website=Integration Developer News |access-date=15 January 2022}}</ref> There are currently two APIs that can access the database:<ref name="sisu" />


'''YSQL'''<ref>{{cite web |title=Yugabyte Structured Query Language (YSQL) |url=https://docs.yugabyte.com/latest/enwiki/api/ysql/ |website=Yugabyte |access-date=15 January 2022}}</ref> is a PostgreSQL code-compatible API based around v11.2. YSQL is accessed via standard PostgreSQL drivers using native protocols. It exploits the native PostgreSQL code for the query layer and replaces the storage engine with calls to the pluggable query layer. This re-use means that Yugabyte supports many features, including:
'''YSQL'''<ref>{{cite web |title=Yugabyte Structured Query Language (YSQL) |url=https://docs.yugabyte.com/latest/enwiki/api/ysql/ |website=Yugabyte |access-date=15 January 2022}}</ref> is a PostgreSQL code-compatible API<ref>{{cite web |title=Yugabyte Meets Developer Demand for Comprehensive PostgreSQL Compatibility with YugabyteDB 2.11 |url=https://www.businesswire.com/news/home/20211123005572/en/Yugabyte-Meets-Developer-Demand-for-Comprehensive-PostgreSQL-Compatibility-with-YugabyteDB-2.11 |website=BusinessWire |date=23 November 2021 |access-date=15 January 2022}}</ref><ref name="ysql">{{cite web |title=PostgreSQL Compatibility in YugabyteDB 2.0 |url=https://blog.yugabyte.com/postgresql-compatibility-in-yugabyte-db-2-0/ |website=Yugabyte|date=17 September 2019 }}</ref> based around v11.2. YSQL is accessed via standard PostgreSQL drivers using native protocols.<ref>{{cite web |title=Client Drivers for YSQL |url=https://docs.yugabyte.com/latest/reference/drivers/ysql-client-drivers/ |website=Yugabyte}}</ref> It exploits the native PostgreSQL code for the query layer<ref>{{cite web |title=Why We Built YugabyteDB by Reusing the PostgreSQL Query Layer |url=https://blog.yugabyte.com/why-we-built-yugabytedb-by-reusing-the-postgresql-query-layer/ |website=Yugabyte |date=24 April 2020 |access-date=15 January 2022}}</ref> and replaces the storage engine with calls to the pluggable query layer. This re-use means that Yugabyte supports many features, including:
* Triggers & Stored Procedures
* Triggers & Stored Procedures<ref name="ysql" />
* PostgreSQL extensions that operate in the query layer
* PostgreSQL extensions that operate in the query layer<ref name="ysql" />
* Native JSONB support
* Native JSONB support<ref name="ysql" />


'''YCQL'''<ref>{{cite web |title=Yugabyte Cloud Query Language (YCQL) |url=https://docs.yugabyte.com/latest/enwiki/api/ycql/ |website=Yugabyte |access-date=15 January 2022}}</ref> is a Cassandra-like API based around v3.10 and re-written in C++. YCQL is accessed via standard Cassandra drivers using the native protocol port of 9042. In addition to the 'vanilla' Cassandra components, YCQL is augmented with the following features:
'''YCQL'''<ref>{{cite web |title=Yugabyte Cloud Query Language (YCQL) |url=https://docs.yugabyte.com/latest/enwiki/api/ycql/ |website=Yugabyte |access-date=15 January 2022}}</ref> is a Cassandra-like API based around v3.10 and re-written in C++. YCQL is accessed via standard Cassandra drivers<ref>{{cite web |title=Client drivers for YCQL |url=https://docs.yugabyte.com/latest/reference/drivers/ycql-client-drivers/ |website=Yugabyte}}</ref> using the native protocol port of 9042. In addition to the 'vanilla' Cassandra components, YCQL is augmented with the following features:
* Transactional consistency - unlike Cassandra, Yugabyte YCQL is transactional.
* Transactional consistency - unlike Cassandra, Yugabyte YCQL is transactional.<ref>{{cite web |title=ACID Transactions |url=https://docs.yugabyte.com/latest/develop/learn/acid-transactions-ycql/ |website=Yugabyte}}</ref>
* [[JSON]] data types supported natively
* [[JSON]] data types supported natively<ref>{{cite web |title=YCQL JSONB Data Type |url=https://docs.yugabyte.com/latest/enwiki/api/ycql/type_jsonb/ |website=Yugabyte |access-date=15 January 2022}}</ref>
* Tables can have secondary indexes<ref>{{cite web |title=YCQL Secondary Indexes |url=https://docs.yugabyte.com/latest/develop/learn/data-modeling-ycql/#secondary-indexes |website=Yugabyte |access-date=15 January 2022}}</ref>
* Tables can have secondary indexes


Currently, data written to either API is not accessible via the other API, however YSQL can access YCQL using the PostgreSQL foreign data wrapper feature.<ref>{{cite web |title=YugabyteDB: Postgres foreign data wrapper |url=https://gruchalski.com/posts/2021-11-08-yugabytedb-postgres-foreign-data-wrapper/ |website=Gruchalski |date=8 November 2021 |access-date=15 January 2022}}</ref>
Currently, data written to either API is not accessible via the other API.


The security model for accessing the system is inherited from the API, so access controls for YSQL look like PostgreSQL, and YCQL looks like Cassandra access controls.
The security model for accessing the system is inherited from the API, so access controls for YSQL look like PostgreSQL,<ref>{{cite web |title=YSQL Access Control |url=https://docs.yugabyte.com/latest/secure/authorization/rbac-model/ |website=Yugabyte |access-date=15 January 2022}}</ref> and YCQL looks like Cassandra access controls.<ref>{{cite web |title=YCWL access Controls |url=https://docs.yugabyte.com/latest/secure/authorization/rbac-model-ycql/ |website=Yugabyte |access-date=15 January 2022}}</ref>


⚫
== Cluster-to-cluster replication ==
== Additional Functionality ==


In addition to its core functionality of distributing a single database, YugabyteDB has the ability to replicate between database instances.<ref>{{cite web |title=Yugabyte Expands Multi-Region Database Capabilities and Enterprise-Grade Security with YugabyteDB 2.5 |url=https://www.businesswire.com/news/home/20201112005160/en/Yugabyte-Expands-Multi-Region-Database-Capabilities-and-Enterprise-Grade-Security-with-YugabyteDB-2.5 |website=Business Wire |date=12 November 2020 |access-date=15 January 2022}}</ref><ref>{{cite web |title=xCLuster Replication |url=https://docs.yugabyte.com/latest/architecture/docdb-replication/async-replication/ |website=Yugabyte |access-date=15 January 2022}}</ref> The replication can be one-way or bi-directional and is asynchronous.
In addition to the core database functionality, there are some additional features of note

⚫
=== Cluster-to-cluster replication ===

YugabyteDB has the ability to replicate between database instances. The replication can be one-way or bi-directional and is asynchronous.
One-way replication is used either to create a read-only copy for workload off-loading or in a read-write mode to create an active-passive standby.
One-way replication is used either to create a read-only copy for workload off-loading or in a read-write mode to create an active-passive standby.
Bi-directional replication is generally used in read-write configurations and is used for active-active configurations, geo-distributed applications, etc.
Bi-directional replication is generally used in read-write configurations and is used for active-active configurations, geo-distributed applications, etc.


== Migration tooling ==
Cluster to cluster replication is relatively uncommon in distributed SQL solutions however YugabyteDB includes this capability in the core database distribution.

=== Smart driver ===

YugabyteDB can generally be accessed with either the native PostgreSQL driver or the native Cassandra driver due to its compatibility with those APIs.

However, Yugabyte also provides a distributed JDBC driver for YSQL that enhances YugabyteDB by eliminating the need for external load balancers. It features
* Cluster-awareness, eliminating the need for an external load balancer. The driver package uses an initial contact point for the YugabyteDB cluster as a means of discovering all the nodes and, if required, refreshing the list of live endpoints with every new connection attempt.
* Topology-awareness, which is essential for geographically distributed applications, where the driver uses nodes that are part of a set of geo-locations specified by topology keys.

This eliminates the need for external load balancers to manage connectivity to a distributed system<ref>{{cite web |title=YugabyteDB 2.9 eliminates the need for external load balancers |url=https://www.helpnetsecurity.com/2021/08/28/yugabytedb-2-9/ |website=Help Net Security |access-date=12 January 2022}}</ref>

=== Management console ===


Yugabyte also provides YugabyteDB Voyager, tooling to facilitate the [[Data_migration|migration]] of [[Oracle_Database|Oracle]] and other similar databases to YugabyteDB.<ref>{{cite web |title=Yugabyte simplifies SQL database migration with YugabyteDB Voyager |url=https://siliconangle.com/2023/01/24/yugabyte-simplifies-sql-database-migration-yugabytedb-voyager/?hss_channel=lcp-10643910 |website=siliconANGLE |date=24 January 2023 |access-date=15 March 2023}}</ref><ref>{{cite web |title=Yugabyte chomps into cloud migration |url=https://www.techzine.eu/blogs/data-management/101380/yugabyte-chomps-into-cloud-migration/ |website=Techzine|date=2 February 2023 |access-date=15 March 2023}}</ref> This tool supports the migration of schemas, procedural code and data from the source platform to YugabyteDB.
Yugabyte also has a management console that is available under a source available, a free-trial-only license from the Polyform Project.<ref>{{cite web |title=Free Trial Licence |url=https://polyformproject.org/licenses/free-trial/1.0.0/ |website=Polyform Project |access-date=31 December 2021}}</ref> This standalone package is provided to customers that have a support subscription with the company. The management console provides pre-built automation and monitoring for YugabyteDB features. The management console provides a user interface for human interaction and an API<ref>{{cite web |title=API Documentation |url=https://api-docs.yugabyte.com/docs/yugabyte-platform |website=Yugabyte |access-date=31 December 2021}}</ref> that allows the automation of common tasks into [[Continuous integration]] (CI)/[[Continuous delivery]] (CD) pipelines. The functionality can be broken down into three categories:
* Day 1 Operations - for example, the provisioning of nodes for the cluster, installation of databases, initial key instantiation, etc.
* Day 2 Operations - for example, database instance upgrades, backup and recovery including [[Point-in-time recovery]], key rotation, etc.
* Monitoring - for example, node and instance health, query performance, etc.


==See also==
==See also==
Line 192: Line 144:
* {{Official website|https://www.yugabyte.com/}}
* {{Official website|https://www.yugabyte.com/}}
* {{GitHub|yugabyte/yugabyte-db}}
* {{GitHub|yugabyte/yugabyte-db}}
* [http://yugabyte-db.slack.com Slack community]
* [https://yugabyte-db.slack.com/ Slack community]


[[Category:Cloud databases]]
[[Category:Database companies]]
[[Category:Database companies]]
[[Category:Databases]]
[[Category:Bigtable implementations]]
[[Category:Database-related software for Linux]]
[[Category:Database-related software for Linux]]
[[Category:NewSQL]]
[[Category:NewSQL]]

Latest revision as of 15:49, 30 November 2024

Original author(s)Kannan Muthukkaruppan, Karthik Ranganathan, Mikhail Bautin
Developer(s)Yugabyte, Inc.
Initial release2016; 9 years ago (2016)
Stable release
2.20 (Stable)
2.19 (Development) / January 25, 2024; 11 months ago (2024-01-25)
October 25, 2023; 14 months ago (2023-10-25)
Repository
Written inC++
Operating systemLinux RedHat 7.x and derivatives, MacOS
PlatformBare Metal, Virtual Machine, Docker, Kubernetes and various container management platforms
Available inEnglish
TypeRDBMS
LicenseApache 2.0
Websitewww.yugabyte.com Edit this on Wikidata
Yugabyte, Inc.
Company typePrivate
IndustrySoftware
Founded2016; 9 years ago (2016)
FounderKannan Muthukkaruppan, Karthik Ranganathan, Mikhail Bautin
HeadquartersSunnyvale, California, USA
Key people
Kannan Muthukkaruppan
(Co-Founder & President,
Product Development)
Karthik Ranganathan
(Co-Founder & CTO)
Mikhail Bautin
(Co-Founder &
Software Architect)
Bill Cook
(CEO)
ServicesCommercial database management systems
Websiteyugabyte.com

YugabyteDB is a high-performance transactional distributed SQL database for cloud-native applications, developed by Yugabyte.[1]

History

[edit]

Yugabyte was founded by ex-Facebook engineers Kannan Muthukkaruppan, Karthik Ranganathan, and Mikhail Bautin. At Facebook, they were part of the team that built and operated Cassandra and HBase[2][3] for workloads such as Facebook Messenger and Facebook's Operational Data Store.[4]

The founders came together in February 2016 to build YugabyteDB.[5][6]

YugabyteDB was initially available in two editions: community and enterprise. In July 2019, Yugabyte open-sourced previously commercial features and launched YugabyteDB as open-source under the Apache 2.0 license.[7]

Funding

[edit]

In October 2021, five years after the company's inception, Yugabyte closed a $188 Million Series C funding round to become a Unicorn start-up with a valuation of $1.3Bn[8]

Funding Rounds
Series Date Announced Amount Investors
A 10 Feb 2016 $8M Lightspeed Venture Partners, Jeff Rothschild[9][10]
A 12 Jun 2018 $16M Lightspeed Venture Partners, Dell Technology Capital[11][12]
B 09 Jun 2020 $30M Wipro Ventures, Lightspeed Venture Partners. Dell Technology Capital. 8VC [13][14]
B 03 Mar 2021 $48M Wipro Ventures. Lightspeed Venture Partners. Greenspring Associates, Dell Technology Capital, 8VC[15][16]
C 28 Oct 2021 $188M Wells Fargo Strategic Capital, Sapphire Ventures, Meritech Capital Partners, Lightspeed Venture Partners, Dell Technology Capital, 8VC[17][18][19]

Architecture

[edit]

YugabyteDB is a distributed SQL database that aims to be strongly transactionally consistent across failure zones (i.e. ACID compliance].[20][21] Jepsen testing, the de facto industry standard for verifying correctness, has never fully passed, mainly due to race conditions during schema changes.[22] In CAP Theorem terms YugabyteDB is a Consistent/Partition Tolerant (CP) database.[23][24][25]

YugabyteDB has two layers,[26] a storage engine known as DocDB and the Yugabyte Query Layer.[27]

Architecture Block Diagram for YugabyteDB
YugabyteDB Architecture

DocDB

[edit]

The storage engine consists of a customized RocksDB[27][28] combined with sharding and load balancing algorithms for the data. In addition, the Raft consensus algorithm controls the replication of data between the nodes.[27][28] There is also a Distributed transaction manager[27][28] and Multiversion concurrency control (MVCC)[27][28] to support distributed transactions.[28]

The engine also exploits a Hybrid Logical Clock[29][27] that combines coarsely-synchronized physical clocks with Lamport clocks to track causal relationships.[30]

The DocDB layer is not directly accessible by users.[27]

YugabyteDB Query Layer

[edit]

Yugabyte has a pluggable query layer that abstracts the query layer from the storage layer below.[31] There are currently two APIs that can access the database:[28]

YSQL[32] is a PostgreSQL code-compatible API[33][34] based around v11.2. YSQL is accessed via standard PostgreSQL drivers using native protocols.[35] It exploits the native PostgreSQL code for the query layer[36] and replaces the storage engine with calls to the pluggable query layer. This re-use means that Yugabyte supports many features, including:

  • Triggers & Stored Procedures[34]
  • PostgreSQL extensions that operate in the query layer[34]
  • Native JSONB support[34]

YCQL[37] is a Cassandra-like API based around v3.10 and re-written in C++. YCQL is accessed via standard Cassandra drivers[38] using the native protocol port of 9042. In addition to the 'vanilla' Cassandra components, YCQL is augmented with the following features:

  • Transactional consistency - unlike Cassandra, Yugabyte YCQL is transactional.[39]
  • JSON data types supported natively[40]
  • Tables can have secondary indexes[41]

Currently, data written to either API is not accessible via the other API, however YSQL can access YCQL using the PostgreSQL foreign data wrapper feature.[42]

The security model for accessing the system is inherited from the API, so access controls for YSQL look like PostgreSQL,[43] and YCQL looks like Cassandra access controls.[44]

Cluster-to-cluster replication

[edit]

In addition to its core functionality of distributing a single database, YugabyteDB has the ability to replicate between database instances.[45][46] The replication can be one-way or bi-directional and is asynchronous. One-way replication is used either to create a read-only copy for workload off-loading or in a read-write mode to create an active-passive standby. Bi-directional replication is generally used in read-write configurations and is used for active-active configurations, geo-distributed applications, etc.

Migration tooling

[edit]

Yugabyte also provides YugabyteDB Voyager, tooling to facilitate the migration of Oracle and other similar databases to YugabyteDB.[47][48] This tool supports the migration of schemas, procedural code and data from the source platform to YugabyteDB.

See also

[edit]

References

[edit]
  1. ^ "YugabyteDB System Properties". DB-Engines. Retrieved 30 December 2021.
  2. ^ "Karthik Ranganathan". Dataversity. Retrieved 30 December 2021.
  3. ^ Borthakur, Dhruba; Rash, Samuel; Schmidt, Rodrigo; Aiyer, Amitanand; Gray, Jonathan; Sarma, Joydeep Sen; Muthukkaruppan, Kannan; Spiegelberg, Nicolas; Kuang, Hairong; Ranganathan, Karthik; Molkov, Dmytro; Menon, Aravind (2011). "Apache hadoop goes realtime at Facebook". Proceedings of the 2011 ACM SIGMOD International Conference on Management of data. p. 1071. doi:10.1145/1989323.1989438. ISBN 9781450306614. S2CID 207188340. Retrieved 15 January 2022. {{cite book}}: |website= ignored (help)
  4. ^ "YugaByte Raises $8M in Series A Funding". FINSMES. 2 November 2017. Retrieved 30 December 2021.
  5. ^ "Yugabyte CTO outlines a PostgreSQL path to distributed cloud". VentureBeat. 26 July 2021. Retrieved 31 December 2021.
  6. ^ "Yugabyte expands its fully managed enterprise cloud service with $188M". VentureBeat. 28 October 2021. Retrieved 30 December 2021.
  7. ^ "Yugabyte Expands Multi-Region Database Capabilities and Enterprise-Grade Security with YugabyteDB 2.5". businesswire.com. 12 November 2020. Retrieved 30 November 2024.
  8. ^ "Another cloud native SQL database unicorn: Yugabyte raises $188M Series C funding at $1.3B valuation". ZDNet. Retrieved 12 January 2022.
  9. ^ "YugaByte Raises $8M in Series A Funding". Finsmes. 2 November 2017.
  10. ^ "YugaByte Receives $8M Series A Round". VC News Daily. Retrieved 12 January 2022.
  11. ^ "YugaByte raises $16 Million to combine SQL and NoSQL in a single database". Technologies.org. Retrieved 12 January 2022.
  12. ^ "YugaByte's new database software rakes in $16 million so developers can move to any cloud". TechCrunch. 12 June 2018. Retrieved 12 January 2022.
  13. ^ "Another globally distributed cloud native SQL database on the rise: Yugabyte Raises $30 million in Series B Funding". ZDNet. Retrieved 12 January 2022.
  14. ^ "Yugabyte raises $30M for its cloud-native distributed SQL database". SiliconAngle. 9 June 2020. Retrieved 12 January 2022.
  15. ^ "Yugabyte raises $48M for open source SQL database alternative". VentureBeat. 3 March 2021. Retrieved 12 January 2022.
  16. ^ "Yugabyte Raises $48 Million Funding Round to Accelerate Distributed SQL Enterprise Adoption and Fuel Global Expansion". YahoonFinance. Retrieved 12 January 2022.
  17. ^ "Yugabyte's latest funding round values the distributed SQL system at $1.3bn". The Register. Retrieved 12 January 2022.
  18. ^ "Another cloud native SQL database unicorn: Yugabyte raises $188M Series C funding at $1.3B valuation". ZDNet. Retrieved 12 January 2022.
  19. ^ "High-performance database startup Yugabyte raises $188M in new funding round". Silicon Angle. 28 October 2021. Retrieved 12 January 2022.
  20. ^ "ACID Transactions". Devopedia. 18 August 2019. Retrieved 12 January 2022.
  21. ^ "ICT Solutions for local flexibility markets" (PDF). Academia de Studii Economice din Bucuresti. Proceedings of the IE 2020 International Conference. Retrieved 15 January 2022.
  22. ^ "YugaByte DB 1.3.1". Jepsen.io. Retrieved 30 December 2021.
  23. ^ "YugaByteDB: A Distributed Cloud Native Database for a Highly Scalable Data Store". Open Source Foru. 14 September 2020. Retrieved 15 January 2022.
  24. ^ "Yugabyte Design Goals". Yugabyte.com. Retrieved 15 January 2022.
  25. ^ Galić, Zdravko; Vuzem, Mario (2020). "A Generic and Extensible Core and Prototype of Consistent, Distributed, and Resilient LIS". ISPRS International Journal of Geo-Information. 9 (7): 437. Bibcode:2020IJGI....9..437G. doi:10.3390/ijgi9070437.
  26. ^ "Yugabyte Layered Architecture". Yugabyte. Retrieved 15 January 2022.
  27. ^ a b c d e f g Hirsch, Orhan Henrik. "Scalability of NewSQL Databases in a Cloud Environment" (PDF). Norwegian University of Science and Technology. NYNU Open. Retrieved 15 January 2022.
  28. ^ a b c d e f Budholia, Akash. "NewSQL Monitoring System". San Jose State University Scholar Works. Retrieved 15 January 2022.
  29. ^ "Hybrid Clock". Martin Fowler. Retrieved 30 December 2021.
  30. ^ "Distributed Transactions without Atomic Clocks" (PDF). Yugabyte. Retrieved 15 January 2022.
  31. ^ "Yugabyte DB 2.0 Ships Production-Ready Distributed SQL Database for Going Cloud Native". Integration Developer News. Retrieved 15 January 2022.
  32. ^ "Yugabyte Structured Query Language (YSQL)". Yugabyte. Retrieved 15 January 2022.
  33. ^ "Yugabyte Meets Developer Demand for Comprehensive PostgreSQL Compatibility with YugabyteDB 2.11". BusinessWire. 23 November 2021. Retrieved 15 January 2022.
  34. ^ a b c d "PostgreSQL Compatibility in YugabyteDB 2.0". Yugabyte. 17 September 2019.
  35. ^ "Client Drivers for YSQL". Yugabyte.
  36. ^ "Why We Built YugabyteDB by Reusing the PostgreSQL Query Layer". Yugabyte. 24 April 2020. Retrieved 15 January 2022.
  37. ^ "Yugabyte Cloud Query Language (YCQL)". Yugabyte. Retrieved 15 January 2022.
  38. ^ "Client drivers for YCQL". Yugabyte.
  39. ^ "ACID Transactions". Yugabyte.
  40. ^ "YCQL JSONB Data Type". Yugabyte. Retrieved 15 January 2022.
  41. ^ "YCQL Secondary Indexes". Yugabyte. Retrieved 15 January 2022.
  42. ^ "YugabyteDB: Postgres foreign data wrapper". Gruchalski. 8 November 2021. Retrieved 15 January 2022.
  43. ^ "YSQL Access Control". Yugabyte. Retrieved 15 January 2022.
  44. ^ "YCWL access Controls". Yugabyte. Retrieved 15 January 2022.
  45. ^ "Yugabyte Expands Multi-Region Database Capabilities and Enterprise-Grade Security with YugabyteDB 2.5". Business Wire. 12 November 2020. Retrieved 15 January 2022.
  46. ^ "xCLuster Replication". Yugabyte. Retrieved 15 January 2022.
  47. ^ "Yugabyte simplifies SQL database migration with YugabyteDB Voyager". siliconANGLE. 24 January 2023. Retrieved 15 March 2023.
  48. ^ "Yugabyte chomps into cloud migration". Techzine. 2 February 2023. Retrieved 15 March 2023.
[edit]
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