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DBMS > GridDB vs. ObjectBox vs. Quasardb vs. Splice Machine

System Properties Comparison GridDB vs. ObjectBox vs. Quasardb vs. Splice Machine

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Editorial information provided by DB-Engines
NameGridDB  Xexclude from comparisonObjectBox  Xexclude from comparisonQuasardb  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionScalable in-memory time series database optimized for IoT and Big DataLightweight, fast on-device database for IoT, Mobile and Embedded devices, persisting and synchronising objects and vectorsDistributed, high-performance timeseries databaseOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelTime Series DBMSObject oriented DBMS
Vector DBMS
Time Series DBMSRelational DBMS
Secondary database modelsKey-value store
Relational DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score1.29
Rank#166  Overall
#5  Object oriented DBMS
#7  Vector DBMS
Score0.21
Rank#322  Overall
#29  Time Series DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitegriddb.netgithub.com/­objectbox
objectbox.io
quasar.aisplicemachine.com
Technical documentationdocs.griddb.netdocs.objectbox.iodoc.quasar.ai/­mastersplicemachine.com/­how-it-works
DeveloperToshiba CorporationObjectBox LimitedquasardbSplice Machine
Initial release2013201720092014
Current release5.1, August 20224.0 (May 2024)3.14.1, January 20243.1, March 2021
License infoCommercial or Open SourceOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableBindings are released under Apache 2.0 infoApache License 2.0commercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensesOpen Source infoAGPL 3.0, commercial license available
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 languageC++C and C++C++Java
Server operating systemsLinuxAndroid
Any POSIX system
Docker
iOS
Linux
macOS
QNX
Windows
BSD
Linux
OS X
Windows
Linux
OS X
Solaris
Windows
Data schemeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyes infonumerical, string, blob, geometry, boolean, timestampyes, plus "flex" map-like typesyes infointeger and binaryyes
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.nonono
Secondary indexesyesyesyes infowith tagsyes
SQL infoSupport of SQLSQL92, SQL-like TQL (Toshiba Query Language)noSQL-like query languageyes
APIs and other access methodsJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Proprietary native APIHTTP APIJDBC
Native Spark Datasource
ODBC
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C
C++
Dart (Flutter)
Go
Java
Kotlin
Python
Swift
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnononoyes infoJava
Triggersyesnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding infoconsistent hashingShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationData sync between devices allowing occasional connected databases to work completely offlineSource-replica replication with selectable replication factorMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnowith Hadoop integrationYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency within container, eventual consistency across containersImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID at container levelACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyes infoby using LevelDByes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes infoTransient modeyes
User concepts infoAccess controlAccess rights for users can be defined per databaseyesCryptographically strong user authentication and audit trailAccess rights for users, groups and roles according to SQL-standard
More information provided by the system vendor
GridDBObjectBoxQuasardbSplice Machine
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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GridDBObjectBoxQuasardbSplice Machine
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