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DBMS > IBM Db2 Event Store vs. PouchDB vs. Spark SQL vs. Teradata

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

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Editorial information provided by DB-Engines
NameIBM Db2 Event Store  Xexclude from comparisonPouchDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonTeradata  Xexclude from comparison
DescriptionDistributed Event Store optimized for Internet of Things use casesJavaScript DBMS with an API inspired by CouchDBSpark SQL is a component on top of 'Spark Core' for structured data processingA hybrid cloud data analytics software platform (Teradata Vantage)
Primary database modelEvent Store
Time Series DBMS
Document storeRelational 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
Score2.34
Rank#112  Overall
#21  Document stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score44.87
Rank#22  Overall
#15  Relational DBMS
Websitewww.ibm.com/­products/­db2-event-storepouchdb.comspark.apache.org/­sqlwww.teradata.com
Technical documentationwww.ibm.com/­docs/­en/­db2-event-storepouchdb.com/­guidesspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.teradata.com
DeveloperIBMApache Software FoundationApache Software FoundationTeradata
Initial release2017201220141984
Current release2.07.1.1, June 20193.5.0 ( 2.13), September 2023Teradata Vantage 1.0 MU2, January 2019
License infoCommercial or Open Sourcecommercial infofree developer edition availableOpen SourceOpen Source infoApache 2.0commercial
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++JavaScriptScala
Server operating systemsLinux infoLinux, macOS, Windows for the developer additionserver-less, requires a JavaScript environment (browser, Node.js)Linux
OS X
Windows
hosted
Linux
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesnoyesyes
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 indexesnoyes infovia viewsnoyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash index
SQL infoSupport of SQLyes infothrough the embedded Spark runtimenoSQL-like DML and DDL statementsyes infoSQL 2016 + extensions
APIs and other access methodsADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
HTTP REST infoonly for PouchDB Server
JavaScript API
JDBC
ODBC
.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
Supported programming languagesC
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
JavaScriptJava
Python
R
Scala
C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
Server-side scripts infoStored proceduresyesView functions in JavaScriptnoyes infoUDFs, stored procedures, table functions in parallel
Triggersnoyesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infowith a proxy-based framework, named couchdb-loungeyes, utilizing Spark CoreSharding infoHashing
Replication methods infoMethods for redundantly storing data on multiple nodesActive-active shard replicationMulti-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
noneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACID
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 storageyes infoby using IndexedDB, WebSQL or LevelDB as backendyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardnonofine grained access rights according to SQL-standard

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More resources
IBM Db2 Event StorePouchDBSpark SQLTeradata
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