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DBMS > Citus vs. Google Cloud Bigtable vs. MarkLogic vs. SiriDB vs. Sphinx

System Properties Comparison Citus vs. Google Cloud Bigtable vs. MarkLogic vs. SiriDB vs. Sphinx

Editorial information provided by DB-Engines
NameCitus  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonMarkLogic  Xexclude from comparisonSiriDB  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Operational and transactional Enterprise NoSQL databaseOpen Source Time Series DBMSOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelRelational DBMSKey-value store
Wide column store
Document store
Native XML DBMS
RDF store infoas of version 7
Search engine
Time Series DBMSSearch engine
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
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score5.92
Rank#58  Overall
#10  Document stores
#1  Native XML DBMS
#1  RDF stores
#6  Search engines
Score0.00
Rank#383  Overall
#41  Time Series DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Websitewww.citusdata.comcloud.google.com/­bigtablewww.marklogic.comsiridb.comsphinxsearch.com
Technical documentationdocs.citusdata.comcloud.google.com/­bigtable/­docsdocs.marklogic.comdocs.siridb.comsphinxsearch.com/­docs
DeveloperGoogleMarkLogic Corp.CesbitSphinx Technologies Inc.
Initial release20102015200120172001
Current release8.1, December 201811.0, December 20223.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoAGPL, commercial license also availablecommercialcommercial inforestricted free version is availableOpen Source infoMIT LicenseOpen Source infoGPL version 2, commercial licence available
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 languageCC++CC++
Server operating systemsLinuxhostedLinux
OS X
Windows
LinuxFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesschema-freeschema-free infoSchema can be enforcedyesyes
Typing infopredefined data types such as float or dateyesnoyesyes 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 functionalitynoyesno
Secondary indexesyesnoyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLyes infostandard, with numerous extensionsnoyes infoSQL92noSQL-like query language (SphinxQL)
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Java API
Node.js Client API
ODBC
proprietary Optic API infoProprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT
HTTP APIProprietary protocol
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C#
C++
Go
Java
JavaScript (Node.js)
Python
C
C#
C++
Java
JavaScript (Node.js)
Perl
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.noyes infovia XQuery or JavaScriptnono
Triggersyesnoyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingShardingSharding 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 extensionsInternal replication in Colossus, and regional replication between two clusters in different zonesyesyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency
Foreign keys infoReferential integrityyesnononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsACID infocan act as a resource manager in an XA/JTA transactionnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes 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.nonoyes, with Range Indexesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Role-based access control at the document and subdocument levelssimple rights management via user accountsno

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More resources
CitusGoogle Cloud BigtableMarkLogicSiriDBSphinx
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