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DBMS > HEAVY.AI vs. Hypertable vs. Kinetica vs. Splice Machine vs. Teradata

System Properties Comparison HEAVY.AI vs. Hypertable vs. Kinetica vs. Splice Machine vs. Teradata

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 comparisonSplice Machine  Xexclude from comparisonTeradata  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 SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkA hybrid cloud data analytics software platform (Teradata Vantage)
Primary database modelRelational DBMSWide column storeRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMSSpatial DBMS
Time Series DBMS
Document store
Graph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Score45.33
Rank#21  Overall
#15  Relational DBMS
Websitegithub.com/­heavyai/­heavydb
www.heavy.ai
www.kinetica.comsplicemachine.comwww.teradata.com
Technical documentationdocs.heavy.aidocs.kinetica.comsplicemachine.com/­how-it-worksdocs.teradata.com
DeveloperHEAVY.AI, Inc.Hypertable Inc.KineticaSplice MachineTeradata
Initial release20162009201220141984
Current release5.10, January 20220.9.8.11, March 20167.1, August 20213.1, March 2021Teradata Vantage 1.0 MU2, January 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2; enterprise edition availableOpen Source infoGNU version 3. Commercial license availablecommercialOpen Source infoAGPL 3.0, commercial license availablecommercial
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++Java
Server operating systemsLinuxLinux
OS X
Windows infoan inofficial Windows port is available
LinuxLinux
OS X
Solaris
Windows
hosted
Linux
Data schemeyesschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesnoyesyesyes
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.nonoyes
Secondary indexesnorestricted infoonly exact value or prefix value scansyesyesyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash index
SQL infoSupport of SQLyesnoSQL-like DML and DDL statementsyesyes infoSQL 2016 + extensions
APIs and other access methodsJDBC
ODBC
Thrift
Vega
C++ API
Thrift
JDBC
ODBC
RESTful HTTP API
JDBC
Native Spark Datasource
ODBC
.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
Supported programming languagesAll languages supporting JDBC/ODBC/Thrift
Python
C++
Java
Perl
PHP
Python
Ruby
C++
Java
JavaScript (Node.js)
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
Server-side scripts infoStored proceduresnonouser defined functionsyes infoJavayes infoUDFs, stored procedures, table functions in parallel
Triggersnonoyes infotriggers when inserted values for one or more columns fall within a specified rangeyesyes
Partitioning methods infoMethods for storing different data on different nodesSharding infoRound robinShardingShardingShared Nothhing Auto-Sharding, Columnar PartitioningSharding infoHashing
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationselectable replication factor on file system levelSource-replica replicationMulti-source replication
Source-replica replication
Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnoYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infoGPU vRAM or System RAMyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardnoAccess rights for users and roles on table levelAccess rights for users, groups and roles according to SQL-standardfine grained access rights according to SQL-standard

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