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DBMS > Drizzle vs. Kinetica vs. Sphinx vs. Splice Machine vs. Stardog

System Properties Comparison Drizzle vs. Kinetica vs. Sphinx vs. Splice Machine vs. Stardog

Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonKinetica  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparisonStardog  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 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 SparkEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization
Primary database modelRelational DBMSRelational DBMSSearch engineRelational DBMSGraph DBMS
RDF store
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Score0.54
Rank#250  Overall
#114  Relational DBMS
Score2.02
Rank#123  Overall
#11  Graph DBMS
#6  RDF stores
Websitewww.kinetica.comsphinxsearch.comsplicemachine.comwww.stardog.com
Technical documentationdocs.kinetica.comsphinxsearch.com/­docssplicemachine.com/­how-it-worksdocs.stardog.com
DeveloperDrizzle project, originally started by Brian AkerKineticaSphinx Technologies Inc.Splice MachineStardog-Union
Initial release20082012200120142010
Current release7.2.4, September 20127.1, August 20213.5.1, February 20233.1, March 20217.3.0, May 2020
License infoCommercial or Open SourceOpen Source infoGNU GPLcommercialOpen Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license availablecommercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C, C++C++JavaJava
Server operating systemsFreeBSD
Linux
OS X
LinuxFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Linux
macOS
Windows
Data schemeyesyesyesyesschema-free and OWL/RDFS-schema support
Typing infopredefined data types such as float or dateyesyesnoyesyes
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 infoImport/export of XML data possible
Secondary indexesyesyesyes infofull-text index on all search fieldsyesyes infosupports real-time indexing in full-text and geospatial
SQL infoSupport of SQLyes infowith proprietary extensionsSQL-like DML and DDL statementsSQL-like query language (SphinxQL)yesYes, compatible with all major SQL variants through dedicated BI/SQL Server
APIs and other access methodsJDBCJDBC
ODBC
RESTful HTTP API
Proprietary protocolJDBC
Native Spark Datasource
ODBC
GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3
Supported programming languagesC
C++
Java
PHP
C++
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
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
Server-side scripts infoStored proceduresnouser defined functionsnoyes infoJavauser defined functions and aggregates, HTTP Server extensions in Java
Triggersno infohooks for callbacks inside the server can be used.yes infotriggers when inserted values for one or more columns fall within a specified rangenoyesyes infovia event handlers
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedShared Nothhing Auto-Sharding, Columnar Partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Source-replica replicationnoneMulti-source replication
Source-replica replication
Multi-source replication in HA-Cluster
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency in HA-Cluster
Foreign keys infoReferential integrityyesyesnoyesyes inforelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yesyes
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
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights for users and roles on table levelnoAccess rights for users, groups and roles according to SQL-standardAccess rights for users and roles

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More resources
DrizzleKineticaSphinxSplice MachineStardog
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