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DBMS > Kinetica vs. Spark SQL vs. Speedb vs. Splice Machine vs. SQream DB

System Properties Comparison Kinetica vs. Spark SQL vs. Speedb vs. Splice Machine vs. SQream DB

Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonSpark SQL  Xexclude from comparisonSpeedb  Xexclude from comparisonSplice Machine  Xexclude from comparisonSQream DB  Xexclude from comparison
DescriptionFully vectorized database across both GPUs and CPUsSpark SQL is a component on top of 'Spark Core' for structured data processingAn embeddable, high performance key-value store optimized for write-intensive workloads, which can be used as a drop-in replacement for RocksDBOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Sparka GPU-based, columnar RDBMS for big data analytics workloads
Primary database modelRelational DBMSRelational DBMSKey-value storeRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.21
Rank#315  Overall
#45  Key-value stores
Score0.54
Rank#250  Overall
#114  Relational DBMS
Score0.70
Rank#227  Overall
#104  Relational DBMS
Websitewww.kinetica.comspark.apache.org/­sqlwww.speedb.iosplicemachine.comsqream.com
Technical documentationdocs.kinetica.comspark.apache.org/­docs/­latest/­sql-programming-guide.htmlsplicemachine.com/­how-it-worksdocs.sqream.com
DeveloperKineticaApache Software FoundationSpeedbSplice MachineSQream Technologies
Initial release20122014202020142017
Current release7.1, August 20213.5.0 ( 2.13), September 20233.1, March 20212022.1.6, December 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoApache Version 2.0; commercial license availableOpen Source infoAGPL 3.0, commercial license availablecommercial
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++ScalaC++JavaC++, CUDA, Haskell, Java, Scala
Server operating systemsLinuxLinux
OS X
Windows
Linux
Windows
Linux
OS X
Solaris
Windows
Linux
Data schemeyesyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesnoyesyes, ANSI Standard SQL Types
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.nonono
Secondary indexesyesnonoyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like DML and DDL statementsnoyesyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
JDBC
Native Spark Datasource
ODBC
.Net
JDBC
ODBC
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
C
C++
Go
Java
Perl
Python
Ruby
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresuser defined functionsnonoyes infoJavauser defined functions in Python
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangenoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark Corehorizontal partitioningShared Nothhing Auto-Sharding, Columnar Partitioninghorizontal and vertical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnoneyesMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoyesACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)yes
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.yes infoGPU vRAM or System RAMnoyesyes
User concepts infoAccess controlAccess rights for users and roles on table levelnonoAccess rights for users, groups and roles according to SQL-standard
More information provided by the system vendor
KineticaSpark SQLSpeedbSplice MachineSQream DB
Specific characteristicsSpeedb is an embedded key-value storage engine for versatile use cases. It was designed...
» more
Competitive advantagesSpeedb Open-source rebases on RocksDB's latest versions, with enhanced capabilities...
» more
Licensing and pricing modelsOpen source - Speedb OSS is released under an Apache license and can be found on...
» more

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More resources
KineticaSpark SQLSpeedbSplice MachineSQream DB
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