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DBMS > Citus vs. Microsoft Azure Table Storage vs. SiriDB vs. Sphinx vs. Warp 10

System Properties Comparison Citus vs. Microsoft Azure Table Storage vs. SiriDB vs. Sphinx vs. Warp 10

Editorial information provided by DB-Engines
NameCitus  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonSiriDB  Xexclude from comparisonSphinx  Xexclude from comparisonWarp 10  Xexclude from comparison
DescriptionScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLA Wide Column Store for rapid development using massive semi-structured datasetsOpen Source Time Series DBMSOpen source search engine for searching in data from different sources, e.g. relational databasesTimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase
Primary database modelRelational DBMSWide column storeTime Series DBMSSearch engineTime Series DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.21
Rank#118  Overall
#56  Relational DBMS
Score4.48
Rank#75  Overall
#6  Wide column stores
Score0.00
Rank#383  Overall
#41  Time Series DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Score0.07
Rank#349  Overall
#32  Time Series DBMS
Websitewww.citusdata.comazure.microsoft.com/­en-us/­services/­storage/­tablessiridb.comsphinxsearch.comwww.warp10.io
Technical documentationdocs.citusdata.comdocs.siridb.comsphinxsearch.com/­docswww.warp10.io/­content/­02_Getting_started
DeveloperMicrosoftCesbitSphinx Technologies Inc.SenX
Initial release20102012201720012015
Current release8.1, December 20183.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoAGPL, commercial license also availablecommercialOpen Source infoMIT LicenseOpen Source infoGPL version 2, commercial licence availableOpen Source infoApache License 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCCC++Java
Server operating systemsLinuxhostedLinuxFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Windows
Data schemeyesschema-freeyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyes infoNumeric datanoyes
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 indexesyesnoyesyes infofull-text index on all search fieldsno
SQL infoSupport of SQLyes infostandard, with numerous extensionsnonoSQL-like query language (SphinxQL)no
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
RESTful HTTP APIHTTP APIProprietary protocolHTTP API
Jupyter
WebSocket
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
C#
C++
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.nononoyes infoWarpScript
Triggersyesnononono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud serviceShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication infoother methods possible by using 3rd party extensionsyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yesnoneselectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency infobased on HBase
Foreign keys infoReferential integrityyesnononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDoptimistic lockingnonono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.nonoyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights based on private key authentication or shared access signaturessimple rights management via user accountsnoMandatory use of cryptographic tokens, containing fine-grained authorizations

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More resources
CitusMicrosoft Azure Table StorageSiriDBSphinxWarp 10
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