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DBMS > HEAVY.AI vs. OrigoDB vs. Riak KV vs. STSdb vs. Trafodion

System Properties Comparison HEAVY.AI vs. OrigoDB vs. Riak KV vs. STSdb vs. Trafodion

Editorial information provided by DB-Engines
NameHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonOrigoDB  Xexclude from comparisonRiak KV  Xexclude from comparisonSTSdb  Xexclude from comparisonTrafodion  Xexclude from comparison
Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.
DescriptionA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareA fully ACID in-memory object graph databaseDistributed, fault tolerant key-value storeKey-Value Store with special method for indexing infooptimized for high performance using a special indexing methodTransactional SQL-on-Hadoop DBMS
Primary database modelRelational DBMSDocument store
Object oriented DBMS
Key-value store infowith links between data sets and object tags for the creation of secondary indexesKey-value storeRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score0.00
Rank#383  Overall
#53  Document stores
#20  Object oriented DBMS
Score4.10
Rank#82  Overall
#9  Key-value stores
Score0.04
Rank#360  Overall
#52  Key-value stores
Websitegithub.com/­heavyai/­heavydb
www.heavy.ai
origodb.comgithub.com/­STSSoft/­STSdb4trafodion.apache.org
Technical documentationdocs.heavy.aiorigodb.com/­docswww.tiot.jp/­riak-docs/­riak/­kv/­latesttrafodion.apache.org/­documentation.html
DeveloperHEAVY.AI, Inc.Robert Friberg et alOpenSource, formerly Basho TechnologiesSTS Soft SCApache Software Foundation, originally developed by HP
Initial release20162009 infounder the name LiveDB200920112014
Current release5.10, January 20223.2.0, December 20224.0.8, September 20152.3.0, February 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2; enterprise edition availableOpen SourceOpen Source infoApache version 2, commercial enterprise editionOpen Source infoGPLv2, commercial license availableOpen Source infoApache 2.0
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#ErlangC#C++, Java
Server operating systemsLinuxLinux
Windows
Linux
OS X
WindowsLinux
Data schemeyesyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesUser defined using .NET types and collectionsnoyes infoprimitive types and user defined types (classes)yes
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 infocan be achieved using .NETnono
Secondary indexesnoyesrestrictednoyes
SQL infoSupport of SQLyesnononoyes
APIs and other access methodsJDBC
ODBC
Thrift
Vega
.NET Client API
HTTP API
LINQ
HTTP API
Native Erlang Interface
.NET Client APIADO.NET
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBC/Thrift
Python
.NetC infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
C#
Java
All languages supporting JDBC/ODBC/ADO.Net
Server-side scripts infoStored proceduresnoyesErlangnoJava Stored Procedures
Triggersnoyes infoDomain Eventsyes infopre-commit hooks and post-commit hooksnono
Partitioning methods infoMethods for storing different data on different nodesSharding infoRound robinhorizontal partitioning infoclient side managed; servers are not synchronizedSharding infono "single point of failure"noneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationSource-replica replicationselectable replication factornoneyes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesnoyes infovia user defined functions and HBase
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynodepending on modelno infolinks between data sets can be storednoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyes infoWrite ahead logyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardRole based authorizationyes, using Riak Securitynofine grained access rights according to SQL-standard

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More resources
HEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022OrigoDBRiak KVSTSdbTrafodion
Recent citations in the news

Big Data Analytics: A Game Changer for Infrastructure
13 July 2023, Spiceworks News and Insights

HEAVY.AI Launches HEAVY 7.0, Introducing Real-Time Machine Learning Capabilities
19 April 2023, businesswire.com

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HEAVY.AI Partners with Bain, Maxar, and Nvidia to Provide Digital Twins for Telecom Networks
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A Critique of Resizable Hash Tables: Riak Core & Random Slicing
26 August 2018, InfoQ.com

Riak NoSQL snapped up by Bet365
12 September 2017, ComputerWeekly.com

NoSQL pioneer Basho stamps its mark on time stamp data with Riak TS
6 October 2015, The Register

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Evaluating HTAP Databases for Machine Learning Applications
2 November 2016, KDnuggets

HP Throws Trafodion Hat into OLTP Hadoop Ring
14 July 2014, Datanami

Low-latency, distributed database architectures are critical for emerging fog applications
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