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DBMS > Graph Engine vs. GridDB vs. Realm vs. TimescaleDB

System Properties Comparison Graph Engine vs. GridDB vs. Realm vs. TimescaleDB

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Editorial information provided by DB-Engines
NameGraph Engine infoformer name: Trinity  Xexclude from comparisonGridDB  Xexclude from comparisonRealm  Xexclude from comparisonTimescaleDB  Xexclude from comparison
DescriptionA distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineScalable in-memory time series database optimized for IoT and Big DataA DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core DataA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelGraph DBMS
Key-value store
Time Series DBMSDocument storeTime Series DBMS
Secondary database modelsKey-value store
Relational DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.61
Rank#240  Overall
#21  Graph DBMS
#35  Key-value stores
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score7.60
Rank#52  Overall
#9  Document stores
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Websitewww.graphengine.iogriddb.netrealm.iowww.timescale.com
Technical documentationwww.graphengine.io/­docs/­manualdocs.griddb.netrealm.io/­docsdocs.timescale.com
DeveloperMicrosoftToshiba CorporationRealm, acquired by MongoDB in May 2019Timescale
Initial release2010201320142017
Current release5.1, August 20222.13.0, November 2023
License infoCommercial or Open SourceOpen Source infoMIT LicenseOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen SourceOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation language.NET and CC++C
Server operating systems.NETLinuxAndroid
Backend: server-less
iOS
Windows
Linux
OS X
Windows
Data schemeyesyesyesyes
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.nononoyes
Secondary indexesyesyesyes
SQL infoSupport of SQLnoSQL92, SQL-like TQL (Toshiba Query Language)noyes infofull PostgreSQL SQL syntax
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC#
C++
F#
Visual Basic
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
Java infowith Android only
Objective-C
React Native
Swift
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyesnono inforuns within the applications so server-side scripts are unnecessaryuser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersnoyesyes infoChange Listenersyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingnoneyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnoneSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency within container, eventual consistency across containersImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID at container levelACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes infoIn-Memory realmno
User concepts infoAccess controlAccess rights for users can be defined per databaseyesfine grained access rights according to SQL-standard
More information provided by the system vendor
Graph Engine infoformer name: TrinityGridDBRealmTimescaleDB
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
Graph Engine infoformer name: TrinityGridDBRealmTimescaleDB
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