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DBMS > AgensGraph vs. GridDB vs. MarkLogic vs. TimescaleDB

System Properties Comparison AgensGraph vs. GridDB vs. MarkLogic vs. TimescaleDB

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Editorial information provided by DB-Engines
NameAgensGraph  Xexclude from comparisonGridDB  Xexclude from comparisonMarkLogic  Xexclude from comparisonTimescaleDB  Xexclude from comparison
DescriptionMulti-model database supporting relational and graph data models and built upon PostgreSQLScalable in-memory time series database optimized for IoT and Big DataOperational and transactional Enterprise NoSQL databaseA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelGraph DBMS
Relational DBMS
Time Series DBMSDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
Time Series DBMS
Secondary database modelsKey-value store
Relational DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.08
Rank#361  Overall
#37  Graph DBMS
#154  Relational DBMS
Score2.00
Rank#137  Overall
#11  Time Series DBMS
Score7.08
Rank#56  Overall
#10  Document stores
#1  Native XML DBMS
#1  RDF stores
#5  Search engines
Score5.33
Rank#72  Overall
#4  Time Series DBMS
Websitebitnine.net/­agensgraphgriddb.netwww.marklogic.comwww.timescale.com
Technical documentationbitnine.net/­documentationdocs.griddb.netdocs.marklogic.comdocs.timescale.com
DeveloperBitnine Global Inc.Toshiba CorporationMarkLogic Corp.Timescale
Initial release2016201320012017
Current release2.1, December 20185.1, August 202211.0, December 20222.13.0, November 2023
License infoCommercial or Open SourceOpen Source infoApache License 2.0Open Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercial inforestricted free version is availableOpen Source infoApache 2.0
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 languageCC++C++C
Server operating systemsLinux
OS X
Windows
LinuxLinux
OS X
Windows
Linux
OS X
Windows
Data schemedepending on used data modelyesschema-free infoSchema can be enforcedyes
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestampyesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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.nonoyesyes
Secondary indexesyesyesyesyes
SQL infoSupport of SQLyesSQL92, SQL-like TQL (Toshiba Query Language)yes infoSQL92yes infofull PostgreSQL SQL syntax
APIs and other access methodsCypher Query Language
JDBC
JDBC
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
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC
Java
JavaScript
Python
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyesnoyes infovia XQuery or JavaScriptuser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersnoyesyesyes
Partitioning methods infoMethods for storing different data on different nodesno, but can be realized using table inheritanceShardingShardingyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationSource-replica replicationyesSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency within container, eventual consistency across containersImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID at container levelACID infocan act as a resource manager in an XA/JTA transactionACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes, with Range Indexesno
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users can be defined per databaseRole-based access control at the document and subdocument levelsfine grained access rights according to SQL-standard
More information provided by the system vendor
AgensGraphGridDBMarkLogicTimescaleDB
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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More resources
AgensGraphGridDBMarkLogicTimescaleDB
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