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DBMS > GridDB vs. Hyprcubd vs. Sphinx vs. Splice Machine

System Properties Comparison GridDB vs. Hyprcubd vs. Sphinx vs. Splice Machine

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Editorial information provided by DB-Engines
NameGridDB  Xexclude from comparisonHyprcubd  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparison
Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.
DescriptionScalable in-memory time series database optimized for IoT and Big DataServerless Time Series DBMSOpen source search engine for searching in data from different sources, e.g. relational databasesOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelTime Series DBMSTime Series DBMSSearch engineRelational DBMS
Secondary database modelsKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.02
Rank#132  Overall
#11  Time Series DBMS
Score6.03
Rank#60  Overall
#6  Search engines
Score0.54
Rank#255  Overall
#116  Relational DBMS
Websitegriddb.nethyprcubd.com (offline)sphinxsearch.comsplicemachine.com
Technical documentationdocs.griddb.netsphinxsearch.com/­docssplicemachine.com/­how-it-works
DeveloperToshiba CorporationHyprcubd, Inc.Sphinx Technologies Inc.Splice Machine
Initial release201320012014
Current release5.1, August 20223.5.1, February 20233.1, March 2021
License infoCommercial or Open SourceOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercialOpen Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++GoC++Java
Server operating systemsLinuxhostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyes infonumerical, string, blob, geometry, boolean, timestampyes infotime, int, uint, float, stringnoyes
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.nono
Secondary indexesyesnoyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLSQL92, SQL-like TQL (Toshiba Query Language)SQL-like query languageSQL-like query language (SphinxQL)yes
APIs and other access methodsJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
gRPC (https)Proprietary protocolJDBC
Native Spark Datasource
ODBC
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
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 nodesShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnoneMulti-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 jobsnonoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency within container, eventual consistency across containersEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID at container levelnonoACID
Concurrency infoSupport for concurrent manipulation of datayesnoyesyes, multi-version concurrency control (MVCC)
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.yesnoyes
User concepts infoAccess controlAccess rights for users can be defined per databasetoken accessnoAccess rights for users, groups and roles according to SQL-standard
More information provided by the system vendor
GridDBHyprcubdSphinxSplice 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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GridDBHyprcubdSphinxSplice Machine
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