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DBMS > IBM Db2 Event Store vs. Kinetica vs. Microsoft Azure SQL Database vs. Spark SQL

System Properties Comparison IBM Db2 Event Store vs. Kinetica vs. Microsoft Azure SQL Database vs. Spark SQL

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Editorial information provided by DB-Engines
NameIBM Db2 Event Store  Xexclude from comparisonKinetica  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionDistributed Event Store optimized for Internet of Things use casesFully vectorized database across both GPUs and CPUsDatabase as a Service offering with high compatibility to Microsoft SQL ServerSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelEvent Store
Time Series DBMS
Relational DBMSRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Document store
Graph DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.19
Rank#323  Overall
#2  Event Stores
#28  Time Series DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score77.99
Rank#16  Overall
#11  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.ibm.com/­products/­db2-event-storewww.kinetica.comazure.microsoft.com/­en-us/­products/­azure-sql/­databasespark.apache.org/­sql
Technical documentationwww.ibm.com/­docs/­en/­db2-event-storedocs.kinetica.comdocs.microsoft.com/­en-us/­azure/­azure-sqlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperIBMKineticaMicrosoftApache Software Foundation
Initial release2017201220102014
Current release2.07.1, August 2021V123.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercial infofree developer edition availablecommercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC and C++C, C++C++Scala
Server operating systemsLinux infoLinux, macOS, Windows for the developer additionLinuxhostedLinux
OS X
Windows
Data schemeyesyesyesyes
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.nonoyesno
Secondary indexesnoyesyesno
SQL infoSupport of SQLyes infothrough the embedded Spark runtimeSQL-like DML and DDL statementsyesSQL-like DML and DDL statements
APIs and other access methodsADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
JDBC
ODBC
Supported programming languagesC
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
C++
Java
JavaScript (Node.js)
Python
.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresyesuser defined functionsTransact SQLno
Triggersnoyes infotriggers when inserted values for one or more columns fall within a specified rangeyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesActive-active shard replicationSource-replica replicationyes, with always 3 replicas availablenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDno
Concurrency infoSupport for concurrent manipulation of dataNo - written data is immutableyesyesyes
Durability infoSupport for making data persistentYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infoGPU vRAM or System RAMno
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users and roles on table levelfine grained access rights according to SQL-standardno

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More resources
IBM Db2 Event StoreKineticaMicrosoft Azure SQL Database infoformerly SQL AzureSpark SQL
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