Amazon Redshift
Amazon Redshift is a hosted data warehouse product, which is part of the larger cloud computing platform Amazon Web Services. It is built on top of technology from the massive parallel processing (MPP) data warehouse ParAccel by Actian.[1] Redshift differs from Amazon's other hosted database offering, Amazon RDS, by being able to handle analytics workloads on large scale datasets stored by a column-oriented DBMS principle. To be able to handle large scale datasets Amazon is making use of massive parallel processing.
Amazon Redshift "is based on PostgreSQL 8.0.2. [...] PostgreSQL 9.x includes some features that are not supported in Amazon Redshift. In addition, there are important differences between Amazon Redshift SQL and PostgreSQL 8.0.2".[2]
BI tools
In principle Amazon Redshift is able to handle all connections from other applications based upon ODBC and JDBC connections.[3] Amazon has listed a number of business intelligence tools as partners and tested tools.[4]
- Actian
- Actuate Corporation
- Birst
- Chartio
- ClearStory Data
- Dundas Data Visualization
- Infor
- Jaspersoft
- Jreport
- Keboola
- Logi Analytics
- Looker (Software)
- MicroStrategy
- Pentaho
- Periscope.io
- Qlik
- Redrock BI
- SAS (software)
- SiSense
- Spotfire
- Tableau Software
- datastage
Not included in the list, though capable of connecting to Amazon Redshift, are solutions that are capable of connecting to a database by making use of JDBC or ODBC.
Data integration tools
Amazon Redshift also has partners providing data integration tools.[4]
History
An initial preview beta was released on November 2012[5] and a full release was made available on February 15, 2013.
References
- ^ "Amazon Redshift: ParAccel in, costly appliances out". ZDNet. Retrieved July 8, 2013.
- ^ "Redshift and PostgreSQL". AWS. Amazon.
- ^ Louwers, Johan (February 2014), Amazon Redshift cloud based data warehouse service (Blogger) (World Wide Web log), NL: Google.
- ^ a b "Amazon Redshift Partners", AWS Partner Network, Amazon.
- ^ "Amazon Debuts Low-Cost, Big Data Warehousing". Information Week. Retrieved July 8, 2013.