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DBMS > Apache Pinot vs. GridGain vs. Teradata

System Properties Comparison Apache Pinot vs. GridGain vs. Teradata

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Editorial information provided by DB-Engines
NameApache Pinot  Xexclude from comparisonGridGain  Xexclude from comparisonTeradata  Xexclude from comparison
DescriptionRealtime distributed OLAP datastore, designed to answer OLAP queries with low latencyGridGain is an in-memory computing platform, built on Apache IgniteA hybrid cloud data analytics software platform (Teradata Vantage)
Primary database modelRelational DBMSKey-value store
Relational DBMS
Relational DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.38
Rank#275  Overall
#126  Relational DBMS
Score1.55
Rank#150  Overall
#26  Key-value stores
#70  Relational DBMS
Score44.87
Rank#22  Overall
#15  Relational DBMS
Websitepinot.apache.orgwww.gridgain.comwww.teradata.com
Technical documentationdocs.pinot.apache.orgwww.gridgain.com/­docs/­index.htmldocs.teradata.com
DeveloperApache Software Foundation and contributorsGridGain Systems, Inc.Teradata
Initial release201520071984
Current release1.0.0, September 2023GridGain 8.5.1Teradata Vantage 1.0 MU2, January 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercial
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJava, C++, .Net
Server operating systemsAll OS with a Java JDK11 or higherLinux
OS X
Solaris
Windows
hosted
Linux
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyesyes
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.yesyes
Secondary indexesyesyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash index
SQL infoSupport of SQLSQL-like query languageANSI-99 for query and DML statements, subset of DDLyes infoSQL 2016 + extensions
APIs and other access methodsJDBCHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
Supported programming languagesGo
Java
Python
C#
C++
Java
PHP
Python
Ruby
Scala
C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
Server-side scripts infoStored proceduresyes (compute grid and cache interceptors can be used instead)yes infoUDFs, stored procedures, table functions in parallel
Triggersyes (cache interceptors and events)yes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingSharding infoHashing
Replication methods infoMethods for redundantly storing data on multiple nodesyes (replicated cache)Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes (compute grid and hadoop accelerator)no
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes
User concepts infoAccess controlSecurity Hooks for custom implementationsfine grained access rights according to SQL-standard

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More resources
Apache PinotGridGainTeradata
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