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DBMS > Datomic vs. GridDB vs. TimescaleDB vs. VictoriaMetrics

System Properties Comparison Datomic vs. GridDB vs. TimescaleDB vs. VictoriaMetrics

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonGridDB  Xexclude from comparisonTimescaleDB  Xexclude from comparisonVictoriaMetrics  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityScalable in-memory time series database optimized for IoT and Big DataA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQLA fast, cost-effective and scalable Time Series DBMS and monitoring solution
Primary database modelRelational DBMSTime Series DBMSTime Series DBMSTime Series DBMS
Secondary database modelsKey-value store
Relational DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Score1.32
Rank#162  Overall
#14  Time Series DBMS
Websitewww.datomic.comgriddb.netwww.timescale.comvictoriametrics.com
Technical documentationdocs.datomic.comdocs.griddb.netdocs.timescale.comdocs.victoriametrics.com
github.com/­VictoriaMetrics/­VictoriaMetrics/­wiki
DeveloperCognitectToshiba CorporationTimescaleVictoriaMetrics
Initial release2012201320172018
Current release1.0.6735, June 20235.1, August 20222.15.0, May 2024v1.91, May 2023
License infoCommercial or Open Sourcecommercial infolimited edition freeOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoApache 2.0Open Source infoApache Version 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 languageJava, ClojureC++CGo
Server operating systemsAll OS with a Java VMLinuxLinux
OS X
Windows
FreeBSD
Linux
macOS
OpenBSD
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestampnumerics, 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.nonoyesno
Secondary indexesyesyesyes
SQL infoSupport of SQLnoSQL92, SQL-like TQL (Toshiba Query Language)yes infofull PostgreSQL SQL syntaxno
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
Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write
Supported programming languagesClojure
Java
C
C++
Go
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 proceduresyes infoTransaction Functionsnouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shellno
TriggersBy using transaction functionsyesyesno
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShardingyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersSource-replica replicationSource-replica replication with hot standby and reads on replicas infoSynchronous replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency within container, eventual consistency across containersImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID at container levelACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes inforecommended only for testing and developmentyesnono
User concepts infoAccess controlnoAccess rights for users can be defined per databasefine grained access rights according to SQL-standard
More information provided by the system vendor
DatomicGridDBTimescaleDBVictoriaMetrics
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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DatomicGridDBTimescaleDBVictoriaMetrics
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