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DBMS > Citus vs. Databricks vs. IBM Db2 Event Store vs. PouchDB

System Properties Comparison Citus vs. Databricks vs. IBM Db2 Event Store vs. PouchDB

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Editorial information provided by DB-Engines
NameCitus  Xexclude from comparisonDatabricks  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonPouchDB  Xexclude from comparison
DescriptionScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.Distributed Event Store optimized for Internet of Things use casesJavaScript DBMS with an API inspired by CouchDB
Primary database modelRelational DBMSDocument store
Relational DBMS
Event Store
Time Series DBMS
Document store
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.21
Rank#118  Overall
#56  Relational DBMS
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.19
Rank#323  Overall
#2  Event Stores
#28  Time Series DBMS
Score2.28
Rank#115  Overall
#21  Document stores
Websitewww.citusdata.comwww.databricks.comwww.ibm.com/­products/­db2-event-storepouchdb.com
Technical documentationdocs.citusdata.comdocs.databricks.comwww.ibm.com/­docs/­en/­db2-event-storepouchdb.com/­guides
DeveloperDatabricksIBMApache Software Foundation
Initial release2010201320172012
Current release8.1, December 20182.07.1.1, June 2019
License infoCommercial or Open SourceOpen Source infoAGPL, commercial license also availablecommercialcommercial infofree developer edition availableOpen Source
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCC and C++JavaScript
Server operating systemsLinuxhostedLinux infoLinux, macOS, Windows for the developer additionserver-less, requires a JavaScript environment (browser, Node.js)
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)yesschema-free
Typing infopredefined data types such as float or dateyesyesno
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.yes infospecific XML type available, but no XML query functionalityyesnono
Secondary indexesyesyesnoyes infovia views
SQL infoSupport of SQLyes infostandard, with numerous extensionswith Databricks SQLyes infothrough the embedded Spark runtimeno
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
RESTful HTTP API
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
HTTP REST infoonly for PouchDB Server
JavaScript API
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Python
R
Scala
C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
JavaScript
Server-side scripts infoStored proceduresuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.user defined functions and aggregatesyesView functions in JavaScript
Triggersyesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infowith a proxy-based framework, named couchdb-lounge
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication infoother methods possible by using 3rd party extensionsyesActive-active shard replicationMulti-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesNo - written data is immutable
Durability infoSupport for making data persistentyesyesYes - 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 backend
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardno
More information provided by the system vendor
CitusDatabricksIBM Db2 Event StorePouchDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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CitusDatabricksIBM Db2 Event StorePouchDB
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