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DBMS > Citus vs. Ehcache vs. Google Cloud Datastore vs. SiriDB vs. Sphinx

System Properties Comparison Citus vs. Ehcache vs. Google Cloud Datastore vs. SiriDB vs. Sphinx

Editorial information provided by DB-Engines
NameCitus  Xexclude from comparisonEhcache  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonSiriDB  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 optionsAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformOpen Source Time Series DBMSOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelRelational DBMSKey-value storeDocument storeTime Series DBMSSearch engine
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.15
Rank#123  Overall
#60  Relational DBMS
Score5.23
Rank#68  Overall
#8  Key-value stores
Score4.49
Rank#79  Overall
#12  Document stores
Score0.11
Rank#346  Overall
#32  Time Series DBMS
Score6.03
Rank#60  Overall
#6  Search engines
Websitewww.citusdata.comwww.ehcache.orgcloud.google.com/­datastoresiridb.comsphinxsearch.com
Technical documentationdocs.citusdata.comwww.ehcache.org/­documentationcloud.google.com/­datastore/­docsdocs.siridb.comsphinxsearch.com/­docs
DeveloperTerracotta Inc, owned by Software AGGoogleCesbitSphinx Technologies Inc.
Initial release20102009200820172001
Current release8.1, December 20183.10.0, March 20223.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoAGPL, commercial license also availableOpen Source infoApache Version 2; commercial licenses availablecommercialOpen Source infoMIT LicenseOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCJavaCC++
Server operating systemsLinuxAll OS with a Java VMhostedLinuxFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyes, details hereyes infoNumeric datano
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 functionalitynonono
Secondary indexesyesnoyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLyes infostandard, with numerous extensionsnoSQL-like query language (GQL)noSQL-like query language (SphinxQL)
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JCachegRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP APIProprietary protocol
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Java.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
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.nousing Google App Enginenono
Triggersyesyes infoCache Event ListenersCallbacks using the Google Apps Enginenono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoby using Terracotta ServerShardingShardingSharding 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 ServerMulti-source replication using Paxosyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyTunable Consistency (Strong, Eventual, Weak)Immediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.
Foreign keys infoReferential integrityyesnoyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyes infosupports JTA and can work as an XA resourceACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyes infousing a tiered cache-storage approachyesyesyes 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.noyesnoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)simple rights management via user accountsno

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