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DBMS > Apache Kylin vs. GridDB vs. Kinetica vs. Teradata

System Properties Comparison Apache Kylin vs. GridDB vs. Kinetica vs. Teradata

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Editorial information provided by DB-Engines
NameApache Kylin  Xexclude from comparisonGridDB  Xexclude from comparisonKinetica  Xexclude from comparisonTeradata  Xexclude from comparison
DescriptionA distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stackScalable in-memory time series database optimized for IoT and Big DataFully vectorized database across both GPUs and CPUsA hybrid cloud data analytics software platform (Teradata Vantage)
Primary database modelRelational DBMSTime Series DBMSRelational DBMSRelational DBMS
Secondary database modelsKey-value store
Relational DBMS
Spatial 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
Score1.18
Rank#172  Overall
#79  Relational DBMS
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score45.33
Rank#21  Overall
#15  Relational DBMS
Websitekylin.apache.orggriddb.netwww.kinetica.comwww.teradata.com
Technical documentationkylin.apache.org/­docsdocs.griddb.netdocs.kinetica.comdocs.teradata.com
DeveloperApache Software Foundation, originally contributed from eBay IncToshiba CorporationKineticaTeradata
Initial release2015201320121984
Current release3.1.0, July 20205.1, August 20227.1, August 2021Teradata Vantage 1.0 MU2, January 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++C, C++
Server operating systemsLinuxLinuxLinuxhosted
Linux
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestampyesyes
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.nononoyes
Secondary indexesyesyesyesyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash index
SQL infoSupport of SQLANSI SQL for queries (using Apache Calcite)SQL92, SQL-like TQL (Toshiba Query Language)SQL-like DML and DDL statementsyes infoSQL 2016 + extensions
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
JDBC
ODBC
RESTful HTTP API
.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C++
Java
JavaScript (Node.js)
Python
C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
Server-side scripts infoStored proceduresnouser defined functionsyes infoUDFs, stored procedures, table functions in parallel
Triggersyesyes infotriggers when inserted values for one or more columns fall within a specified rangeyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoHashing
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationSource-replica replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency within container, eventual consistency across containersImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID at container levelnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes infoGPU vRAM or System RAMyes
User concepts infoAccess controlAccess rights for users can be defined per databaseAccess rights for users and roles on table levelfine grained access rights according to SQL-standard
More information provided by the system vendor
Apache KylinGridDBKineticaTeradata
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
Apache KylinGridDBKineticaTeradata
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Overhauling Apache Kylin for the cloud
18 November 2021, InfoWorld

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9 December 2015, eBay Inc.

The Apache Software Foundation Announces Apache™ Kylin™ as a Top-Level Project
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