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DBMS > Drizzle vs. Kinetica vs. Splice Machine vs. TerarkDB vs. TimesTen

System Properties Comparison Drizzle vs. Kinetica vs. Splice Machine vs. TerarkDB vs. TimesTen

Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonKinetica  Xexclude from comparisonSplice Machine  Xexclude from comparisonTerarkDB  Xexclude from comparisonTimesTen  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.Fully vectorized database across both GPUs and CPUsOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkA key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDBIn-Memory RDBMS compatible to Oracle
Primary database modelRelational DBMSRelational DBMSRelational DBMSKey-value storeRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.69
Rank#234  Overall
#107  Relational DBMS
Score0.54
Rank#255  Overall
#116  Relational DBMS
Score0.04
Rank#377  Overall
#58  Key-value stores
Score1.35
Rank#165  Overall
#75  Relational DBMS
Websitewww.kinetica.comsplicemachine.comgithub.com/­bytedance/­terarkdbwww.oracle.com/­database/­technologies/­related/­timesten.html
Technical documentationdocs.kinetica.comsplicemachine.com/­how-it-worksbytedance.larkoffice.com/­docs/­doccnZmYFqHBm06BbvYgjsHHcKcdocs.oracle.com/­database/­timesten-18.1
DeveloperDrizzle project, originally started by Brian AkerKineticaSplice MachineByteDance, originally TerarkOracle, TimesTen Performance Software, HP infooriginally founded in HP Labs it was acquired by Oracle in 2005
Initial release20082012201420161998
Current release7.2.4, September 20127.1, August 20213.1, March 202111 Release 2 (11.2.2.8.0)
License infoCommercial or Open SourceOpen Source infoGNU GPLcommercialOpen Source infoAGPL 3.0, commercial license availablecommercial inforestricted open source version 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, C++JavaC++
Server operating systemsFreeBSD
Linux
OS X
LinuxLinux
OS X
Solaris
Windows
AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Data schemeyesyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesnoyes
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 indexesyesyesyesnoyes
SQL infoSupport of SQLyes infowith proprietary extensionsSQL-like DML and DDL statementsyesnoyes
APIs and other access methodsJDBCJDBC
ODBC
RESTful HTTP API
JDBC
Native Spark Datasource
ODBC
C++ API
Java API
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Supported programming languagesC
C++
Java
PHP
C++
Java
JavaScript (Node.js)
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
C++
Java
C
C++
Java
PL/SQL
Server-side scripts infoStored proceduresnouser defined functionsyes infoJavanoPL/SQL
Triggersno infohooks for callbacks inside the server can be used.yes infotriggers when inserted values for one or more columns fall within a specified rangeyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShared Nothhing Auto-Sharding, Columnar Partitioningnonenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Source-replica replicationMulti-source replication
Source-replica replication
noneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoYes, via Full Spark Integrationnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyesyesyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yesyes
Durability infoSupport for making data persistentyesyesyesyesyes infoby means of logfiles and checkpoints
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoGPU vRAM or System RAMyesyesyes
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights for users and roles on table levelAccess rights for users, groups and roles according to SQL-standardnofine grained access rights according to SQL-standard

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More resources
DrizzleKineticaSplice MachineTerarkDBTimesTen
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