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DBMS > Drizzle vs. EJDB vs. HEAVY.AI vs. Kinetica vs. Splice Machine

System Properties Comparison Drizzle vs. EJDB vs. HEAVY.AI vs. Kinetica vs. Splice Machine

Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonEJDB  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonKinetica  Xexclude from comparisonSplice Machine  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Embeddable document-store database library with JSON representation of queries (in MongoDB style)A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareFully vectorized database across both GPUs and CPUsOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSDocument storeRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.30
Rank#302  Overall
#44  Document stores
Score2.30
Rank#127  Overall
#60  Relational DBMS
Score0.74
Rank#229  Overall
#105  Relational DBMS
Score0.54
Rank#257  Overall
#118  Relational DBMS
Websitegithub.com/­Softmotions/­ejdbgithub.com/­heavyai/­heavydb
www.heavy.ai
www.kinetica.comsplicemachine.com
Technical documentationgithub.com/­Softmotions/­ejdb/­blob/­master/­README.mddocs.heavy.aidocs.kinetica.comsplicemachine.com/­how-it-works
DeveloperDrizzle project, originally started by Brian AkerSoftmotionsHEAVY.AI, Inc.KineticaSplice Machine
Initial release20082012201620122014
Current release7.2.4, September 20125.10, January 20227.1, August 20213.1, March 2021
License infoCommercial or Open SourceOpen Source infoGNU GPLOpen Source infoGPLv2Open Source infoApache Version 2; enterprise edition availablecommercialOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++CC++ and CUDAC, C++Java
Server operating systemsFreeBSD
Linux
OS X
server-lessLinuxLinuxLinux
OS X
Solaris
Windows
Data schemeyesschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesyes infostring, integer, double, bool, date, object_idyesyesyes
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.nono
Secondary indexesyesnonoyesyes
SQL infoSupport of SQLyes infowith proprietary extensionsnoyesSQL-like DML and DDL statementsyes
APIs and other access methodsJDBCin-process shared libraryJDBC
ODBC
Thrift
Vega
JDBC
ODBC
RESTful HTTP API
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC
C++
Java
PHP
Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby
All languages supporting JDBC/ODBC/Thrift
Python
C++
Java
JavaScript (Node.js)
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnononouser defined functionsyes infoJava
Triggersno infohooks for callbacks inside the server can be used.nonoyes infotriggers when inserted values for one or more columns fall within a specified rangeyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding infoRound robinShardingShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
noneMulti-source replicationSource-replica replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonononoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integrityyesno infotypically not needed, however similar functionality with collection joins possiblenoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnononoACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoRead/Write Lockingyesyesyes, multi-version concurrency control (MVCC)
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.yesyes infoGPU vRAM or System RAMyes
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPnofine grained access rights according to SQL-standardAccess rights for users and roles on table levelAccess rights for users, groups and roles according to SQL-standard

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More resources
DrizzleEJDBHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022KineticaSplice Machine
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