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DBMS > Kinetica vs. openGemini vs. Sadas Engine vs. Sphinx vs. Splice Machine

System Properties Comparison Kinetica vs. openGemini vs. Sadas Engine vs. Sphinx vs. Splice Machine

Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonopenGemini  Xexclude from comparisonSadas Engine  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionFully vectorized database across both GPUs and CPUsAn open source distributed Time Series DBMS with high concurrency, high performance, and high scalabilitySADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environmentsOpen 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 modelRelational DBMSTime Series DBMSRelational DBMSSearch engineRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score0.09
Rank#361  Overall
#37  Time Series DBMS
Score0.07
Rank#373  Overall
#157  Relational DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitewww.kinetica.comwww.opengemini.org
github.com/­openGemini
www.sadasengine.comsphinxsearch.comsplicemachine.com
Technical documentationdocs.kinetica.comdocs.opengemini.org/­guidewww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentationsphinxsearch.com/­docssplicemachine.com/­how-it-works
DeveloperKineticaHuawei and openGemini communitySADAS s.r.l.Sphinx Technologies Inc.Splice Machine
Initial release20122022200620012014
Current release7.1, August 20211.1, July 20238.03.5.1, February 20233.1, March 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercial infofree trial version availableOpen Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license available
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++GoC++C++Java
Server operating systemsLinuxLinux
Windows
AIX
Linux
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeyesschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesInteger, Float, Boolean, Stringyesnoyes
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 indexesyesyesyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query languageyesSQL-like query language (SphinxQL)yes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
HTTP RESTJDBC
ODBC
Proprietary protocol
Proprietary protocolJDBC
Native Spark Datasource
ODBC
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
C
C++
Go
Java
JavaScript (Node.js)
Python
Rust
.Net
C
C#
C++
Groovy
Java
PHP
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 functionsnononoyes infoJava
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangenononoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioningSharding 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 replicationyesnonenoneMulti-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 Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyes 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 RAMyesyes infomanaged by 'Learn by Usage'yes
User concepts infoAccess controlAccess rights for users and roles on table levelAdministrators and common users accountsAccess rights for users, groups and roles according to SQL-standardnoAccess rights for users, groups and roles according to SQL-standard

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More resources
KineticaopenGeminiSadas EngineSphinxSplice Machine
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