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DBMS > HEAVY.AI vs. IBM Db2 Event Store vs. Kinetica vs. LevelDB vs. Teradata Aster

System Properties Comparison HEAVY.AI vs. IBM Db2 Event Store vs. Kinetica vs. LevelDB vs. Teradata Aster

Editorial information provided by DB-Engines
NameHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonKinetica  Xexclude from comparisonLevelDB  Xexclude from comparisonTeradata Aster  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareDistributed Event Store optimized for Internet of Things use casesFully vectorized database across both GPUs and CPUsEmbeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesPlatform for big data analytics on multistructured data sources and types
Primary database modelRelational DBMSEvent Store
Time Series DBMS
Relational DBMSKey-value storeRelational DBMS
Secondary database modelsSpatial DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.64
Rank#145  Overall
#67  Relational DBMS
Score0.27
Rank#309  Overall
#2  Event Stores
#28  Time Series DBMS
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score2.25
Rank#115  Overall
#19  Key-value stores
Websitegithub.com/­heavyai/­heavydb
www.heavy.ai
www.ibm.com/­products/­db2-event-storewww.kinetica.comgithub.com/­google/­leveldb
Technical documentationdocs.heavy.aiwww.ibm.com/­docs/­en/­db2-event-storedocs.kinetica.comgithub.com/­google/­leveldb/­blob/­main/­doc/­index.md
DeveloperHEAVY.AI, Inc.IBMKineticaGoogleTeradata
Initial release20162017201220112005
Current release5.10, January 20222.07.1, August 20211.23, February 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2; enterprise edition availablecommercial infofree developer edition availablecommercialOpen Source infoBSDcommercial
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 and C++C, C++C++
Server operating systemsLinuxLinux infoLinux, macOS, Windows for the developer additionLinuxIllumos
Linux
OS X
Windows
Linux
Data schemeyesyesyesschema-freeFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
Typing infopredefined data types such as float or dateyesyesyesnoyes
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.nonononoyes infoin Aster File Store
Secondary indexesnonoyesnoyes
SQL infoSupport of SQLyesyes infothrough the embedded Spark runtimeSQL-like DML and DDL statementsnoyes
APIs and other access methodsJDBC
ODBC
Thrift
Vega
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesAll languages supporting JDBC/ODBC/Thrift
Python
C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
C++
Java
JavaScript (Node.js)
Python
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresnoyesuser defined functionsnoR packages
Triggersnonoyes infotriggers when inserted values for one or more columns fall within a specified rangenono
Partitioning methods infoMethods for storing different data on different nodesSharding infoRound robinShardingShardingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationActive-active shard replicationSource-replica replicationnoneyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonononoyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynonoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonononoACID
Concurrency infoSupport for concurrent manipulation of datayesNo - written data is immutableyesyesyes
Durability infoSupport for making data persistentyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyesyes infowith automatic compression on writesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes infoGPU vRAM or System RAMno
User concepts infoAccess controlfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardAccess rights for users and roles on table levelnofine grained access rights according to SQL-standard

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More resources
HEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022IBM Db2 Event StoreKineticaLevelDBTeradata Aster
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