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DBMS > HEAVY.AI vs. Hypertable vs. Sphinx

System Properties Comparison HEAVY.AI vs. Hypertable vs. Sphinx

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Editorial information provided by DB-Engines
NameHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonHypertable  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 HadoopOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelRelational DBMSWide column storeSearch engine
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.10
Rank#126  Overall
#61  Relational DBMS
Score6.03
Rank#60  Overall
#6  Search engines
Websitegithub.com/­heavyai/­heavydb
www.heavy.ai
sphinxsearch.com
Technical documentationdocs.heavy.aisphinxsearch.com/­docs
DeveloperHEAVY.AI, Inc.Hypertable Inc.Sphinx Technologies Inc.
Initial release201620092001
Current release5.10, January 20220.9.8.11, March 20163.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2; enterprise edition availableOpen Source infoGNU version 3. Commercial license availableOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++ and CUDAC++C++
Server operating systemsLinuxLinux
OS X
Windows infoan inofficial Windows port is available
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesschema-freeyes
Typing infopredefined data types such as float or dateyesnono
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.no
Secondary indexesnorestricted infoonly exact value or prefix value scansyes infofull-text index on all search fields
SQL infoSupport of SQLyesnoSQL-like query language (SphinxQL)
APIs and other access methodsJDBC
ODBC
Thrift
Vega
C++ API
Thrift
Proprietary protocol
Supported programming languagesAll languages supporting JDBC/ODBC/Thrift
Python
C++
Java
Perl
PHP
Python
Ruby
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnonono
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesSharding infoRound robinShardingSharding 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 levelnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonono
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes 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.yes
User concepts infoAccess controlfine grained access rights according to SQL-standardnono

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