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DBMS > GridDB vs. GridGain vs. TimescaleDB vs. Titan

System Properties Comparison GridDB vs. GridGain vs. TimescaleDB vs. Titan

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Editorial information provided by DB-Engines
NameGridDB  Xexclude from comparisonGridGain  Xexclude from comparisonTimescaleDB  Xexclude from comparisonTitan  Xexclude from comparison
Titan has been decommisioned after the takeover by Datastax. It will be removed from the DB-Engines ranking. A fork has been open-sourced as JanusGraph.
DescriptionScalable in-memory time series database optimized for IoT and Big DataGridGain is an in-memory computing platform, built on Apache IgniteA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQLTitan is a Graph DBMS optimized for distributed clusters.
Primary database modelTime Series DBMSColumnar
Key-value store
Object oriented DBMS
Relational DBMS
Time Series DBMSGraph DBMS
Secondary database modelsKey-value store
Relational DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#123  Overall
#10  Time Series DBMS
Score1.48
Rank#150  Overall
#1  Columnar
#26  Key-value stores
#2  Object oriented DBMS
#69  Relational DBMS
Score4.06
Rank#73  Overall
#5  Time Series DBMS
Websitegriddb.netwww.gridgain.comwww.timescale.comgithub.com/­thinkaurelius/­titan
Technical documentationdocs.griddb.netwww.gridgain.com/­docs/­index.htmldocs.timescale.comgithub.com/­thinkaurelius/­titan/­wiki
DeveloperToshiba CorporationGridGain Systems, Inc.TimescaleAurelius, owned by DataStax
Initial release2013200720172012
Current release5.1, August 2022GridGain 8.5.12.15.0, May 2024
License infoCommercial or Open SourceOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercial, open sourceOpen Source infoApache 2.0Open Source infoApache license, version 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Java, C++, .Net, Python, REST, SQLCJava
Server operating systemsLinuxLinux
OS X
Solaris
Windows
z/OS
Linux
OS X
Windows
Linux
OS X
Unix
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyes infonumerical, string, blob, geometry, boolean, timestampyesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data typesyes
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.noyesyes
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL92, SQL-like TQL (Toshiba Query Language)ANSI-99 for query and DML statements, subset of DDLyes infofull PostgreSQL SQL syntaxno
APIs and other access methodsJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C#
C++
Java
PHP
Python
Ruby
Scala
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Clojure
Java
Python
Server-side scripts infoStored proceduresnoyes (compute grid and cache interceptors can be used instead)user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shellyes
Triggersyesyes (cache interceptors and events)yesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, across time and space (hash partitioning) attributesyes infovia pluggable storage backends
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyes (replicated cache)Source-replica replication with hot standby and reads on replicas infoyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsyes (compute grid and hadoop accelerator)noyes infovia Faunus, a graph analytics engine
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency within container, eventual consistency across containersImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonoyesyes infoRelationships in graph
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID at container levelACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesno
User concepts infoAccess controlAccess rights for users can be defined per databaseRole-based access control
Security Hooks for custom implementations
fine grained access rights according to SQL-standardUser authentification and security via Rexster Graph Server

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GridDBGridGainTimescaleDBTitan
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