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DBMS > HEAVY.AI vs. Hypertable vs. Kinetica vs. Oracle Rdb vs. Sphinx

System Properties Comparison HEAVY.AI vs. Hypertable vs. Kinetica vs. Oracle Rdb vs. Sphinx

Editorial information provided by DB-Engines
NameHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonHypertable  Xexclude from comparisonKinetica  Xexclude from comparisonOracle Rdb  Xexclude from comparisonSphinx  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareAn open source BigTable implementation based on distributed file systems such as HadoopFully vectorized database across both GPUs and CPUsOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelRelational DBMSWide column storeRelational DBMSRelational DBMSSearch engine
Secondary database modelsSpatial DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.30
Rank#127  Overall
#60  Relational DBMS
Score0.74
Rank#229  Overall
#105  Relational DBMS
Score1.23
Rank#180  Overall
#82  Relational DBMS
Score6.06
Rank#61  Overall
#6  Search engines
Websitegithub.com/­heavyai/­heavydb
www.heavy.ai
www.kinetica.comwww.oracle.com/­database/­technologies/­related/­rdb.htmlsphinxsearch.com
Technical documentationdocs.heavy.aidocs.kinetica.comwww.oracle.com/­database/­technologies/­related/­rdb-doc.htmlsphinxsearch.com/­docs
DeveloperHEAVY.AI, Inc.Hypertable Inc.KineticaOracle, originally developed by Digital Equipment Corporation (DEC)Sphinx Technologies Inc.
Initial release20162009201219842001
Current release5.10, January 20220.9.8.11, March 20167.1, August 20217.4.1.1, 20213.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2; enterprise edition availableOpen Source infoGNU version 3. Commercial license availablecommercialcommercialOpen Source infoGPL version 2, commercial licence available
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++ and CUDAC++C, C++C++
Server operating systemsLinuxLinux
OS X
Windows infoan inofficial Windows port is available
LinuxHP Open VMSFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesschema-freeyesFlexible Schema (defined schema, partial schema, schema free)yes
Typing infopredefined data types such as float or dateyesnoyesyesno
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 indexesnorestricted infoonly exact value or prefix value scansyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLyesnoSQL-like DML and DDL statementsyesSQL-like query language (SphinxQL)
APIs and other access methodsJDBC
ODBC
Thrift
Vega
C++ API
Thrift
JDBC
ODBC
RESTful HTTP API
Proprietary protocol
Supported programming languagesAll languages supporting JDBC/ODBC/Thrift
Python
C++
Java
Perl
PHP
Python
Ruby
C++
Java
JavaScript (Node.js)
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnonouser defined functionsno
Triggersnonoyes infotriggers when inserted values for one or more columns fall within a specified rangeno
Partitioning methods infoMethods for storing different data on different nodesSharding infoRound robinShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationselectable replication factor on file system levelSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynonoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoyes, on a single nodeno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infoGPU vRAM or System RAMno
User concepts infoAccess controlfine grained access rights according to SQL-standardnoAccess rights for users and roles on table levelno

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More resources
HEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022HypertableKineticaOracle RdbSphinx
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