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DBMS > Fujitsu Enterprise Postgres vs. PouchDB vs. Solr vs. Splice Machine

System Properties Comparison Fujitsu Enterprise Postgres vs. PouchDB vs. Solr vs. Splice Machine

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Editorial information provided by DB-Engines
NameFujitsu Enterprise Postgres  Xexclude from comparisonPouchDB  Xexclude from comparisonSolr  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionEnterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.JavaScript DBMS with an API inspired by CouchDBA widely used distributed, scalable search engine based on Apache LuceneOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSDocument storeSearch engineRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.37
Rank#278  Overall
#128  Relational DBMS
Score2.34
Rank#112  Overall
#21  Document stores
Score41.02
Rank#24  Overall
#3  Search engines
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitewww.postgresql.fastware.compouchdb.comsolr.apache.orgsplicemachine.com
Technical documentationwww.postgresql.fastware.com/­product-manualspouchdb.com/­guidessolr.apache.org/­resources.htmlsplicemachine.com/­how-it-works
DeveloperPostgreSQL Global Development Group, Fujitsu Australia Software TechnologyApache Software FoundationApache Software FoundationSplice Machine
Initial release201220062014
Current releaseFujitsu Enterprise Postgres 14, January 20227.1.1, June 20199.6.1, May 20243.1, March 2021
License infoCommercial or Open SourcecommercialOpen SourceOpen Source infoApache Version 2Open Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCJavaScriptJavaJava
Server operating systemsLinux
Windows
server-less, requires a JavaScript environment (browser, Node.js)All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
OS X
Solaris
Windows
Data schemeyesschema-freeyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateyesnoyes infosupports customizable data types and automatic typingyes
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.noyes
Secondary indexesyesyes infovia viewsyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLyesnoSolr Parallel SQL Interfaceyes
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
HTTP REST infoonly for PouchDB Server
JavaScript API
Java API
RESTful HTTP/JSON API
JDBC
Native Spark Datasource
ODBC
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
JavaScript.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsView functions in JavaScriptJava pluginsyes infoJava
Triggersyesyesyes infoUser configurable commands triggered on index changesyes
Partitioning methods infoMethods for storing different data on different nodespartitioning by range, list and by hashSharding infowith a proxy-based framework, named couchdb-loungeShardingShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
yesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnooptimistic lockingACID
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyes 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.yesyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardnoyesAccess rights for users, groups and roles according to SQL-standard

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