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DBMS > IBM Db2 Event Store vs. Kinetica vs. Spark SQL vs. Warp 10

System Properties Comparison IBM Db2 Event Store vs. Kinetica vs. Spark SQL vs. Warp 10

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Editorial information provided by DB-Engines
NameIBM Db2 Event Store  Xexclude from comparisonKinetica  Xexclude from comparisonSpark SQL  Xexclude from comparisonWarp 10  Xexclude from comparison
DescriptionDistributed Event Store optimized for Internet of Things use casesFully vectorized database across both GPUs and CPUsSpark SQL is a component on top of 'Spark Core' for structured data processingTimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase
Primary database modelEvent Store
Time Series DBMS
Relational DBMSRelational DBMSTime Series DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.27
Rank#309  Overall
#2  Event Stores
#28  Time Series DBMS
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.14
Rank#344  Overall
#32  Time Series DBMS
Websitewww.ibm.com/­products/­db2-event-storewww.kinetica.comspark.apache.org/­sqlwww.warp10.io
Technical documentationwww.ibm.com/­docs/­en/­db2-event-storedocs.kinetica.comspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.warp10.io/­content/­02_Getting_started
DeveloperIBMKineticaApache Software FoundationSenX
Initial release2017201220142015
Current release2.07.1, August 20213.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercial infofree developer edition availablecommercialOpen Source infoApache 2.0Open Source infoApache License 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC and C++C, C++ScalaJava
Server operating systemsLinux infoLinux, macOS, Windows for the developer additionLinuxLinux
OS X
Windows
Linux
OS X
Windows
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.nononono
Secondary indexesnoyesnono
SQL infoSupport of SQLyes infothrough the embedded Spark runtimeSQL-like DML and DDL statementsSQL-like DML and DDL statementsno
APIs and other access methodsADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
HTTP API
Jupyter
WebSocket
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
Java
Python
R
Scala
Server-side scripts infoStored proceduresyesuser defined functionsnoyes infoWarpScript
Triggersnoyes infotriggers when inserted values for one or more columns fall within a specified rangenono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark CoreSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesActive-active shard replicationSource-replica replicationnoneselectable replication factor infobased on HBase
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 infobased on HBase
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononono
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 RAMnoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users and roles on table levelnoMandatory use of cryptographic tokens, containing fine-grained authorizations

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More resources
IBM Db2 Event StoreKineticaSpark SQLWarp 10
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