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DBMS > Kinetica vs. Spark SQL vs. Speedb

System Properties Comparison Kinetica vs. Spark SQL vs. Speedb

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Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonSpark SQL  Xexclude from comparisonSpeedb  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 RocksDB
Primary database modelRelational DBMSRelational DBMSKey-value store
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
Websitewww.kinetica.comspark.apache.org/­sqlwww.speedb.io
Technical documentationdocs.kinetica.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperKineticaApache Software FoundationSpeedb
Initial release201220142020
Current release7.1, August 20213.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoApache Version 2.0; commercial license available
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++ScalaC++
Server operating systemsLinuxLinux
OS X
Windows
Linux
Windows
Data schemeyesyesschema-free
Typing infopredefined data types such as float or dateyesyesno
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 indexesyesnono
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like DML and DDL statementsno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
C
C++
Go
Java
Perl
Python
Ruby
Server-side scripts infoStored proceduresuser defined functionsnono
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangeno
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark Corehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnoneyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoyes
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoGPU vRAM or System RAMnoyes
User concepts infoAccess controlAccess rights for users and roles on table levelnono
More information provided by the system vendor
KineticaSpark SQLSpeedb
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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KineticaSpark SQLSpeedb
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