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DBMS > HEAVY.AI vs. Hypertable vs. IRONdb vs. Sphinx

System Properties Comparison HEAVY.AI vs. Hypertable vs. IRONdb 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 comparisonIRONdb  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 HadoopA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelRelational DBMSWide column storeTime Series DBMSSearch engine
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.73
Rank#136  Overall
#68  Relational DBMS
Score0.00
Rank#363  Overall
#34  Time Series DBMS
Score6.76
Rank#63  Overall
#8  Search engines
Websitegithub.com/­heavyai/­heavydb
www.heavy.ai
www.circonus.com/­solutions/­time-series-databasesphinxsearch.com
Technical documentationdocs.heavy.aidocs.circonus.com/­irondbsphinxsearch.com/­docs
DeveloperHEAVY.AI, Inc.Hypertable Inc.Circonus LLC.Sphinx Technologies Inc.
Initial release2016200920172001
Current release5.10, January 20220.9.8.11, March 2016V0.10.20, January 20183.4.1, July 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2; enterprise edition availableOpen Source infoGNU version 3. Commercial license availablecommercialOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++ and CUDAC++C and C++C++
Server operating systemsLinuxLinux
OS X
Windows infoan inofficial Windows port is available
LinuxFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesnoyes infotext, numeric, histogramsno
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 indexesnorestricted infoonly exact value or prefix value scansnoyes infofull-text index on all search fields
SQL infoSupport of SQLyesnoSQL-like query language (Circonus Analytics Query Language: CAQL)SQL-like query language (SphinxQL)
APIs and other access methodsJDBC
ODBC
Thrift
Vega
C++ API
Thrift
HTTP APIProprietary protocol
Supported programming languagesAll languages supporting JDBC/ODBC/Thrift
Python
C++
Java
Perl
PHP
Python
Ruby
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnonoyes, in Luano
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesSharding infoRound robinShardingAutomatic, metric affinity per nodeSharding 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 levelconfigurable replication factor, datacenter awarenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate consistency per node, eventual consistency across nodes
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes 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.yesno
User concepts infoAccess controlfine grained access rights according to SQL-standardnonono
More information provided by the system vendor
HEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022HypertableIRONdbSphinx
Specific characteristicsOptimizes memory and compute layers to deliver unprecedented performance. Natively...
» more
Competitive advantagesOnly HEAVY.AI allows users to visually and interactively discover high-value patterns,...
» more
Typical application scenariosAdvanced analytics, geospatial and time-series analytics, accelerated data science,...
» more
Licensing and pricing modelsHEAVY.AI Free (Free Forever), Foundations ($2k/month), and Enterprise Licensure (Inquire...
» more

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HEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022HypertableIRONdbSphinx
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