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DBMS > IBM Db2 Event Store vs. Spark SQL vs. Teradata vs. Valentina Server

System Properties Comparison IBM Db2 Event Store vs. Spark SQL vs. Teradata vs. Valentina Server

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Editorial information provided by DB-Engines
NameIBM Db2 Event Store  Xexclude from comparisonSpark SQL  Xexclude from comparisonTeradata  Xexclude from comparisonValentina Server  Xexclude from comparison
DescriptionDistributed Event Store optimized for Internet of Things use casesSpark SQL is a component on top of 'Spark Core' for structured data processingA hybrid cloud data analytics software platform (Teradata Vantage)Object-relational database and reports server
Primary database modelEvent Store
Time Series DBMS
Relational DBMSRelational DBMSRelational 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
Score0.27
Rank#309  Overall
#2  Event Stores
#28  Time Series DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score44.87
Rank#22  Overall
#15  Relational DBMS
Score0.21
Rank#325  Overall
#144  Relational DBMS
Websitewww.ibm.com/­products/­db2-event-storespark.apache.org/­sqlwww.teradata.comwww.valentina-db.net
Technical documentationwww.ibm.com/­docs/­en/­db2-event-storespark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.teradata.comvalentina-db.com/­docs/­dokuwiki/­v5/­doku.php
DeveloperIBMApache Software FoundationTeradataParadigma Software
Initial release2017201419841999
Current release2.03.5.0 ( 2.13), September 2023Teradata Vantage 1.0 MU2, January 20195.7.5
License infoCommercial or Open Sourcecommercial infofree developer edition availableOpen Source infoApache 2.0commercialcommercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC and C++Scala
Server operating systemsLinux infoLinux, macOS, Windows for the developer additionLinux
OS X
Windows
hosted
Linux
Linux
OS X
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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 indexesnonoyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash indexyes
SQL infoSupport of SQLyes infothrough the embedded Spark runtimeSQL-like DML and DDL statementsyes infoSQL 2016 + extensionsyes
APIs and other access methodsADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
ODBC
Supported programming languagesC
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
Java
Python
R
Scala
C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET
Server-side scripts infoStored proceduresyesnoyes infoUDFs, stored procedures, table functions in parallelyes
Triggersnonoyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark CoreSharding infoHashing
Replication methods infoMethods for redundantly storing data on multiple nodesActive-active shard replicationnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID
Concurrency infoSupport for concurrent manipulation of dataNo - written data is immutableyesyes
Durability infoSupport for making data persistentYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardnofine grained access rights according to SQL-standardfine grained access rights according to SQL-standard

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IBM Db2 Event StoreSpark SQLTeradataValentina Server
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