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DBMS > GridDB vs. HBase vs. Splice Machine vs. TimescaleDB

System Properties Comparison GridDB vs. HBase vs. Splice Machine vs. TimescaleDB

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Editorial information provided by DB-Engines
NameGridDB  Xexclude from comparisonHBase  Xexclude from comparisonSplice Machine  Xexclude from comparisonTimescaleDB  Xexclude from comparison
DescriptionScalable in-memory time series database optimized for IoT and Big DataWide-column store based on Apache Hadoop and on concepts of BigTableOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelTime Series DBMSWide column storeRelational 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
Score2.02
Rank#132  Overall
#11  Time Series DBMS
Score31.25
Rank#26  Overall
#2  Wide column stores
Score0.54
Rank#255  Overall
#116  Relational DBMS
Score4.87
Rank#74  Overall
#4  Time Series DBMS
Websitegriddb.nethbase.apache.orgsplicemachine.comwww.timescale.com
Technical documentationdocs.griddb.nethbase.apache.org/­book.htmlsplicemachine.com/­how-it-worksdocs.timescale.com
DeveloperToshiba CorporationApache Software Foundation infoApache top-level project, originally developed by PowersetSplice MachineTimescale
Initial release2013200820142017
Current release5.1, August 20222.3.4, January 20213.1, March 20212.13.0, November 2023
License infoCommercial or Open SourceOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoApache version 2Open Source infoAGPL 3.0, commercial license availableOpen 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 languageC++JavaJavaC
Server operating systemsLinuxLinux
Unix
Windows infousing Cygwin
Linux
OS X
Solaris
Windows
Linux
OS X
Windows
Data schemeyesschema-free, schema definition possibleyesyes
Typing infopredefined data types such as float or dateyes infonumerical, string, blob, geometry, boolean, timestampoptions to bring your own types, AVROyesnumerics, 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.nonoyes
Secondary indexesyesnoyesyes
SQL infoSupport of SQLSQL92, SQL-like TQL (Toshiba Query Language)noyesyes infofull PostgreSQL SQL syntax
APIs and other access methodsJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Java API
RESTful HTTP API
Thrift
JDBC
Native Spark Datasource
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C
C#
C++
Groovy
Java
PHP
Python
Scala
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnoyes infoCoprocessors in Javayes infoJavauser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersyesyesyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShared Nothhing Auto-Sharding, Columnar Partitioningyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication
Source-replica replication
Multi-source replication
Source-replica replication
Source-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 jobsyesYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency within container, eventual consistency across containersImmediate Consistency or Eventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID at container levelSingle row ACID (across millions of columns)ACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesno
User concepts infoAccess controlAccess rights for users can be defined per databaseAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACAccess rights for users, groups and roles according to SQL-standardfine grained access rights according to SQL-standard
More information provided by the system vendor
GridDBHBaseSplice MachineTimescaleDB
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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GridDBHBaseSplice MachineTimescaleDB
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