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DBMS > ArcadeDB vs. Kinetica vs. Sphinx vs. Splice Machine

System Properties Comparison ArcadeDB vs. Kinetica vs. Sphinx vs. Splice Machine

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Editorial information provided by DB-Engines
NameArcadeDB  Xexclude from comparisonKinetica  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionFast and scalable multi-model DBMS, originally forked from OrientDB but most of the code has been rewrittenFully vectorized database across both GPUs and CPUsOpen source search engine for searching in data from different sources, e.g. relational databasesOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelDocument store
Graph DBMS
Key-value store
Time Series DBMS infoin next version
Relational DBMSSearch engineRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.10
Rank#358  Overall
#48  Document stores
#38  Graph DBMS
#52  Key-value stores
#35  Time Series DBMS
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitearcadedb.comwww.kinetica.comsphinxsearch.comsplicemachine.com
Technical documentationdocs.arcadedb.comdocs.kinetica.comsphinxsearch.com/­docssplicemachine.com/­how-it-works
DeveloperArcade DataKineticaSphinx Technologies Inc.Splice Machine
Initial release2021201220012014
Current releaseSeptember 20217.1, August 20213.5.1, February 20233.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoGPL version 2, commercial licence availableOpen 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++C++Java
Server operating systemsAll OS with a Java VMLinuxFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesyesnoyes
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 indexesyesyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLSQL-like query language, no joinsSQL-like DML and DDL statementsSQL-like query language (SphinxQL)yes
APIs and other access methodsJDBC
MongoDB API
OpenCypher
PostgreSQL wire protocol
Redis API
RESTful HTTP/JSON API
TinkerPop Gremlin
JDBC
ODBC
RESTful HTTP API
Proprietary protocolJDBC
Native Spark Datasource
ODBC
Supported programming languagesJavaC++
Java
JavaScript (Node.js)
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsnoyes infoJava
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangenoyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationSource-replica replicationnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoYes, 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 integrityyes inforelationship in graphsyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoGPU vRAM or System RAMyes
User concepts infoAccess 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
ArcadeDBKineticaSphinxSplice Machine
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