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DBMS > GridDB vs. HBase vs. Sphinx vs. TerarkDB

System Properties Comparison GridDB vs. HBase vs. Sphinx vs. TerarkDB

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Editorial information provided by DB-Engines
NameGridDB  Xexclude from comparisonHBase  Xexclude from comparisonSphinx  Xexclude from comparisonTerarkDB  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 search engine for searching in data from different sources, e.g. relational databasesA key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB
Primary database modelTime Series DBMSWide column storeSearch engineKey-value store
Secondary database modelsKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score30.50
Rank#26  Overall
#2  Wide column stores
Score5.98
Rank#56  Overall
#5  Search engines
Score0.00
Rank#383  Overall
#60  Key-value stores
Websitegriddb.nethbase.apache.orgsphinxsearch.comgithub.com/­bytedance/­terarkdb
Technical documentationdocs.griddb.nethbase.apache.org/­book.htmlsphinxsearch.com/­docsbytedance.larkoffice.com/­docs/­doccnZmYFqHBm06BbvYgjsHHcKc
DeveloperToshiba CorporationApache Software Foundation infoApache top-level project, originally developed by PowersetSphinx Technologies Inc.ByteDance, originally Terark
Initial release2013200820012016
Current release5.1, August 20222.3.4, January 20213.5.1, February 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 infoGPL version 2, commercial licence availablecommercial inforestricted open source version available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaC++C++
Server operating systemsLinuxLinux
Unix
Windows infousing Cygwin
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesschema-free, schema definition possibleyesschema-free
Typing infopredefined data types such as float or dateyes infonumerical, string, blob, geometry, boolean, timestampoptions to bring your own types, AVROnono
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 indexesyesnoyes infofull-text index on all search fieldsno
SQL infoSupport of SQLSQL92, SQL-like TQL (Toshiba Query Language)noSQL-like query language (SphinxQL)no
APIs and other access methodsJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Java API
RESTful HTTP API
Thrift
Proprietary protocolC++ API
Java API
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C
C#
C++
Groovy
Java
PHP
Python
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C++
Java
Server-side scripts infoStored proceduresnoyes infoCoprocessors in Javanono
Triggersyesyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supportednone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication
Source-replica replication
nonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency within container, eventual consistency across containersImmediate Consistency or Eventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID at container levelSingle row ACID (across millions of columns)nono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes
User concepts infoAccess controlAccess rights for users can be defined per databaseAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACnono
More information provided by the system vendor
GridDBHBaseSphinxTerarkDB
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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GridDBHBaseSphinxTerarkDB
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