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DBMS > Citus vs. NSDb vs. PouchDB vs. Spark SQL vs. Transbase

System Properties Comparison Citus vs. NSDb vs. PouchDB vs. Spark SQL vs. Transbase

Editorial information provided by DB-Engines
NameCitus  Xexclude from comparisonNSDb  Xexclude from comparisonPouchDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonTransbase  Xexclude from comparison
DescriptionScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLScalable, High-performance Time Series DBMS designed for Real-time Analytics on top of KubernetesJavaScript DBMS with an API inspired by CouchDBSpark SQL is a component on top of 'Spark Core' for structured data processingA resource-optimized, high-performance, universally applicable RDBMS
Primary database modelRelational DBMSTime Series DBMSDocument storeRelational DBMSRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.15
Rank#117  Overall
#56  Relational DBMS
Score0.08
Rank#369  Overall
#40  Time Series DBMS
Score2.34
Rank#112  Overall
#21  Document stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.17
Rank#334  Overall
#148  Relational DBMS
Websitewww.citusdata.comnsdb.iopouchdb.comspark.apache.org/­sqlwww.transaction.de/­en/­products/­transbase.html
Technical documentationdocs.citusdata.comnsdb.io/­Architecturepouchdb.com/­guidesspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.transaction.de/­en/­products/­transbase/­features.html
DeveloperApache Software FoundationApache Software FoundationTransaction Software GmbH
Initial release20102017201220141987
Current release8.1, December 20187.1.1, June 20193.5.0 ( 2.13), September 2023Transbase 8.3, 2022
License infoCommercial or Open SourceOpen Source infoAGPL, commercial license also availableOpen Source infoApache Version 2.0Open SourceOpen Source infoApache 2.0commercial infofree development license
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCJava, ScalaJavaScriptScalaC and C++
Server operating systemsLinuxLinux
macOS
server-less, requires a JavaScript environment (browser, Node.js)Linux
OS X
Windows
FreeBSD
Linux
macOS
Solaris
Windows
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyes: int, bigint, decimal, stringnoyesyes
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 functionalitynononono
Secondary indexesyesall fields are automatically indexedyes infovia viewsnoyes
SQL infoSupport of SQLyes infostandard, with numerous extensionsSQL-like query languagenoSQL-like DML and DDL statementsyes
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
gRPC
HTTP REST
WebSocket
HTTP REST infoonly for PouchDB Server
JavaScript API
JDBC
ODBC
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Java
Scala
JavaScriptJava
Python
R
Scala
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.noView functions in JavaScriptnoyes
Triggersyesyesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infowith a proxy-based framework, named couchdb-loungeyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication infoother methods possible by using 3rd party extensionsMulti-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
noneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnononoyes
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesUsing Apache Luceneyes 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.noyesnono
User concepts infoAccess controlfine grained access rights according to SQL-standardnonofine grained access rights according to SQL-standard

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More resources
CitusNSDbPouchDBSpark SQLTransbase
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