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DBMS > GBase vs. GridDB vs. Ignite vs. SpatiaLite vs. VictoriaMetrics

System Properties Comparison GBase vs. GridDB vs. Ignite vs. SpatiaLite vs. VictoriaMetrics

Editorial information provided by DB-Engines
NameGBase  Xexclude from comparisonGridDB  Xexclude from comparisonIgnite  Xexclude from comparisonSpatiaLite  Xexclude from comparisonVictoriaMetrics  Xexclude from comparison
DescriptionWidely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.Scalable in-memory time series database optimized for IoT and Big DataApache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.Spatial extension of SQLiteA fast, cost-effective and scalable Time Series DBMS and monitoring solution
Primary database modelRelational DBMSTime Series DBMSKey-value store
Relational DBMS
Spatial 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
Score1.07
Rank#185  Overall
#86  Relational DBMS
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score3.16
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Score1.60
Rank#149  Overall
#3  Spatial DBMS
Score1.32
Rank#162  Overall
#14  Time Series DBMS
Websitewww.gbase.cngriddb.netignite.apache.orgwww.gaia-gis.it/­fossil/­libspatialite/­indexvictoriametrics.com
Technical documentationdocs.griddb.netapacheignite.readme.io/­docswww.gaia-gis.it/­gaia-sins/­spatialite_topics.htmldocs.victoriametrics.com
github.com/­VictoriaMetrics/­VictoriaMetrics/­wiki
DeveloperGeneral Data Technology Co., Ltd.Toshiba CorporationApache Software FoundationAlessandro FurieriVictoriaMetrics
Initial release20042013201520082018
Current releaseGBase 8a, GBase 8s, GBase 8c5.1, August 2022Apache Ignite 2.65.0.0, August 2020v1.91, May 2023
License infoCommercial or Open SourcecommercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoApache 2.0Open Source infoMPL 1.1, GPL v2.0 or LGPL v2.1Open Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, Java, PythonC++C++, Java, .NetC++Go
Server operating systemsLinuxLinuxLinux
OS X
Solaris
Windows
server-lessFreeBSD
Linux
macOS
OpenBSD
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestampyesyes
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.yesnoyesnono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLStandard with numerous extensionsSQL92, SQL-like TQL (Toshiba Query Language)ANSI-99 for query and DML statements, subset of DDLyesno
APIs and other access methodsADO.NET
C API
JDBC
ODBC
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write
Supported programming languagesC#C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C#
C++
Java
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresuser defined functionsnoyes (compute grid and cache interceptors can be used instead)nono
Triggersyesyesyes (cache interceptors and events)yesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by range, list and hash) and vertical partitioningShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationyes (replicated cache)noneSynchronous 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 (compute grid and hadoop accelerator)nono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency within container, eventual consistency across containersImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesnonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID at container levelACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesno
User concepts infoAccess controlyesAccess rights for users can be defined per databaseSecurity Hooks for custom implementationsno
More information provided by the system vendor
GBaseGridDBIgniteSpatiaLiteVictoriaMetrics
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
GBaseGridDBIgniteSpatiaLiteVictoriaMetrics
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