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DBMS > Drizzle vs. IBM Cloudant vs. Kinetica vs. Microsoft Azure Synapse Analytics vs. Teradata Aster

System Properties Comparison Drizzle vs. IBM Cloudant vs. Kinetica vs. Microsoft Azure Synapse Analytics vs. Teradata Aster

Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonIBM Cloudant  Xexclude from comparisonKinetica  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonTeradata Aster  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.Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Database as a Service offering based on Apache CouchDBFully vectorized database across both GPUs and CPUsElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerPlatform for big data analytics on multistructured data sources and types
Primary database modelRelational DBMSDocument storeRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.68
Rank#106  Overall
#20  Document stores
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score20.56
Rank#31  Overall
#19  Relational DBMS
Websitewww.ibm.com/­products/­cloudantwww.kinetica.comazure.microsoft.com/­services/­synapse-analytics
Technical documentationcloud.ibm.com/­docs/­Cloudantdocs.kinetica.comdocs.microsoft.com/­azure/­synapse-analytics
DeveloperDrizzle project, originally started by Brian AkerIBM, Apache Software Foundation infoIBM acquired Cloudant in February 2014KineticaMicrosoftTeradata
Initial release20082010201220162005
Current release7.2.4, September 20127.1, August 2021
License infoCommercial or Open SourceOpen Source infoGNU GPLcommercialcommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++ErlangC, C++C++
Server operating systemsFreeBSD
Linux
OS X
hostedLinuxhostedLinux
Data schemeyesschema-freeyesyesFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
Typing infopredefined data types such as float or dateyesnoyesyesyes
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.nononoyes infoin Aster File Store
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLyes infowith proprietary extensionsnoSQL-like DML and DDL statementsyesyes
APIs and other access methodsJDBCRESTful HTTP/JSON APIJDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesC
C++
Java
PHP
C#
Java
JavaScript
Objective-C
PHP
Ruby
C++
Java
JavaScript (Node.js)
Python
C#
Java
PHP
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresnoView functions (Map-Reduce) in JavaScriptuser defined functionsTransact SQLR packages
Triggersno infohooks for callbacks inside the server can be used.yesyes infotriggers when inserted values for one or more columns fall within a specified rangenono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding, horizontal partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replication
Source-replica replication
Source-replica replicationyesyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnonoyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyesnoyesno infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDno infoatomic operations within a document possiblenoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoOptimistic lockingyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoGPU vRAM or System RAMno
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights for users can be defined per databaseAccess rights for users and roles on table levelyesfine grained access rights according to SQL-standard

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More resources
DrizzleIBM CloudantKineticaMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseTeradata Aster
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