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DBMS > Citus vs. Ehcache vs. GridDB vs. Sphinx

System Properties Comparison Citus vs. Ehcache vs. GridDB vs. Sphinx

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Editorial information provided by DB-Engines
NameCitus  Xexclude from comparisonEhcache  Xexclude from comparisonGridDB  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLA widely adopted Java cache with tiered storage optionsScalable in-memory time series database optimized for IoT and Big DataOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelRelational DBMSKey-value storeTime Series DBMSSearch engine
Secondary database modelsDocument storeKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.21
Rank#118  Overall
#56  Relational DBMS
Score4.89
Rank#67  Overall
#8  Key-value stores
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Websitewww.citusdata.comwww.ehcache.orggriddb.netsphinxsearch.com
Technical documentationdocs.citusdata.comwww.ehcache.org/­documentationdocs.griddb.netsphinxsearch.com/­docs
DeveloperTerracotta Inc, owned by Software AGToshiba CorporationSphinx Technologies Inc.
Initial release2010200920132001
Current release8.1, December 20183.10.0, March 20225.1, August 20223.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoAGPL, commercial license also availableOpen Source infoApache Version 2; commercial licenses availableOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCJavaC++C++
Server operating systemsLinuxAll OS with a Java VMLinuxFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyes infonumerical, string, blob, geometry, boolean, timestampno
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.yes infospecific XML type available, but no XML query functionalitynono
Secondary indexesyesnoyesyes infofull-text index on all search fields
SQL infoSupport of SQLyes infostandard, with numerous extensionsnoSQL92, SQL-like TQL (Toshiba Query Language)SQL-like query language (SphinxQL)
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JCacheJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Proprietary protocol
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
JavaC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.nonono
Triggersyesyes infoCache Event Listenersyesno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoby using Terracotta ServerShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication infoother methods possible by using 3rd party extensionsyes infoby using Terracotta ServerSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyTunable Consistency (Strong, Eventual, Weak)Immediate consistency within container, eventual consistency across containers
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyes infosupports JTA and can work as an XA resourceACID at container levelno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infousing a tiered cache-storage approachyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardnoAccess rights for users can be defined per databaseno
More information provided by the system vendor
CitusEhcacheGridDBSphinx
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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CitusEhcacheGridDBSphinx
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