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DBMS > Hazelcast vs. Kinetica vs. Spark SQL vs. Splice Machine

System Properties Comparison Hazelcast vs. Kinetica vs. Spark SQL vs. Splice Machine

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Editorial information provided by DB-Engines
NameHazelcast  Xexclude from comparisonKinetica  Xexclude from comparisonSpark SQL  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionA widely adopted in-memory data gridFully vectorized database across both GPUs and CPUsSpark SQL is a component on top of 'Spark Core' for structured data processingOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelKey-value storeRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store infoJSON support with IMDG 3.12Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score5.46
Rank#61  Overall
#7  Key-value stores
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitehazelcast.comwww.kinetica.comspark.apache.org/­sqlsplicemachine.com
Technical documentationhazelcast.org/­imdg/­docsdocs.kinetica.comspark.apache.org/­docs/­latest/­sql-programming-guide.htmlsplicemachine.com/­how-it-works
DeveloperHazelcastKineticaApache Software FoundationSplice Machine
Initial release2008201220142014
Current release5.3.6, November 20237.1, August 20213.5.0 ( 2.13), September 20233.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availablecommercialOpen Source infoApache 2.0Open Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC, C++ScalaJava
Server operating systemsAll OS with a Java VMLinuxLinux
OS X
Windows
Linux
OS X
Solaris
Windows
Data schemeschema-freeyesyesyes
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.yes infothe object must implement a serialization strategynono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLSQL-like query languageSQL-like DML and DDL statementsSQL-like DML and DDL statementsyes
APIs and other access methodsJCache
JPA
Memcached protocol
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
JDBC
Native Spark Datasource
ODBC
Supported programming languages.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C++
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyes infoEvent Listeners, Executor Servicesuser defined functionsnoyes infoJava
Triggersyes infoEventsyes infotriggers when inserted values for one or more columns fall within a specified rangenoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark CoreShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoReplicated MapSource-replica replicationnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataone or two-phase-commit; repeatable reads; read commitednonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyes
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 controlRole-based access controlAccess rights for users and roles on table levelnoAccess rights for users, groups and roles according to SQL-standard

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More resources
HazelcastKineticaSpark SQLSplice Machine
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