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DBMS > Amazon Redshift vs. Citus vs. Drizzle vs. Sqrrl

System Properties Comparison Amazon Redshift vs. Citus vs. Drizzle vs. Sqrrl

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Editorial information provided by DB-Engines
NameAmazon Redshift  Xexclude from comparisonCitus  Xexclude from comparisonDrizzle  Xexclude from comparisonSqrrl  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.
DescriptionLarge scale data warehouse service for use with business intelligence toolsScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Adaptable, secure NoSQL built on Apache Accumulo
Primary database modelRelational DBMSRelational DBMSRelational DBMSDocument store
Graph DBMS
Key-value store
Wide column store
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score17.94
Rank#34  Overall
#21  Relational DBMS
Score2.21
Rank#118  Overall
#56  Relational DBMS
Websiteaws.amazon.com/­redshiftwww.citusdata.comsqrrl.com
Technical documentationdocs.aws.amazon.com/­redshiftdocs.citusdata.com
DeveloperAmazon (based on PostgreSQL)Drizzle project, originally started by Brian AkerAmazon infooriginally Sqrrl Data, Inc.
Initial release2012201020082012
Current release8.1, December 20187.2.4, September 2012
License infoCommercial or Open SourcecommercialOpen Source infoAGPL, commercial license also availableOpen Source infoGNU GPLcommercial
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCCC++Java
Server operating systemshostedLinuxFreeBSD
Linux
OS X
Linux
Data schemeyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.noyes infospecific XML type available, but no XML query functionality
Secondary indexesrestrictedyesyesyes
SQL infoSupport of SQLyes infodoes not fully support an SQL-standardyes infostandard, with numerous extensionsyes infowith proprietary extensionsno
APIs and other access methodsJDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBCAccumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
Supported programming languagesAll languages supporting JDBC/ODBC.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C
C++
Java
PHP
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
Server-side scripts infoStored proceduresuser defined functions infoin Pythonuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.nono
Triggersnoyesno infohooks for callbacks inside the server can be used.no
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding infomaking use of Hadoop
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replication infoother methods possible by using 3rd party extensionsMulti-source replication
Source-replica replication
selectable replication factor infomaking use of Hadoop
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.
Foreign keys infoReferential integrityyes infoinformational only, not enforced by the systemyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDAtomic updates per row, document, or graph entity
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardPluggable authentication mechanisms infoe.g. LDAP, HTTPCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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More resources
Amazon RedshiftCitusDrizzleSqrrl
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