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DBMS > GridDB vs. MarkLogic vs. Sphinx vs. Vitess

System Properties Comparison GridDB vs. MarkLogic vs. Sphinx vs. Vitess

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Editorial information provided by DB-Engines
NameGridDB  Xexclude from comparisonMarkLogic  Xexclude from comparisonSphinx  Xexclude from comparisonVitess  Xexclude from comparison
DescriptionScalable in-memory time series database optimized for IoT and Big DataOperational and transactional Enterprise NoSQL databaseOpen source search engine for searching in data from different sources, e.g. relational databasesScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelTime Series DBMSDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
Search engineRelational DBMS
Secondary database modelsKey-value store
Relational DBMS
Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#123  Overall
#10  Time Series DBMS
Score4.15
Rank#70  Overall
#11  Document stores
#1  Native XML DBMS
#1  RDF stores
#8  Search engines
Score5.97
Rank#56  Overall
#5  Search engines
Score0.86
Rank#202  Overall
#95  Relational DBMS
Websitegriddb.netwww.progress.com/­marklogicsphinxsearch.comvitess.io
Technical documentationdocs.griddb.netwww.progress.com/­marklogic/­documentationsphinxsearch.com/­docsvitess.io/­docs
DeveloperToshiba CorporationMarkLogic Corp.Sphinx Technologies Inc.The Linux Foundation, PlanetScale
Initial release2013200120012013
Current release5.1, August 202211.0, December 20223.5.1, February 202315.0.2, December 2022
License infoCommercial or Open SourceOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercial inforestricted free version is availableOpen Source infoGPL version 2, commercial licence availableOpen Source infoApache Version 2.0, commercial licenses 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 languageC++C++C++Go
Server operating systemsLinuxLinux
OS X
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Docker
Linux
macOS
Data schemeyesschema-free infoSchema can be enforcedyesyes
Typing infopredefined data types such as float or dateyes infonumerical, string, blob, geometry, boolean, timestampyesnoyes
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.noyes
Secondary indexesyesyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLSQL92, SQL-like TQL (Toshiba Query Language)yes infoSQL92SQL-like query language (SphinxQL)yes infowith proprietary extensions
APIs and other access methodsJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
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
Proprietary protocolADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnoyes infovia XQuery or JavaScriptnoyes infoproprietary syntax
Triggersyesyesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyesnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency within container, eventual consistency across containersImmediate ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynononoyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID at container levelACID infocan act as a resource manager in an XA/JTA transactionnoACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infotable locks or row locks depending on storage engine
Durability infoSupport for making data persistentyesyesyes 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.yesyes, with Range Indexesyes
User concepts infoAccess controlAccess rights for users can be defined per databaseRole-based access control at the document and subdocument levelsnoUsers with fine-grained authorization concept infono user groups or roles

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More resources
GridDBMarkLogicSphinxVitess
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