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DBMS > Fujitsu Enterprise Postgres vs. LMDB vs. Solr vs. Spark SQL

System Properties Comparison Fujitsu Enterprise Postgres vs. LMDB vs. Solr vs. Spark SQL

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Editorial information provided by DB-Engines
NameFujitsu Enterprise Postgres  Xexclude from comparisonLMDB  Xexclude from comparisonSolr  Xexclude from comparisonSpark SQL  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.A high performant, light-weight, embedded key-value database libraryA widely used distributed, scalable search engine based on Apache LuceneSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSKey-value 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
Score2.09
Rank#121  Overall
#20  Key-value stores
Score41.02
Rank#24  Overall
#3  Search engines
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websitewww.postgresql.fastware.comwww.symas.com/­symas-embedded-database-lmdbsolr.apache.orgspark.apache.org/­sql
Technical documentationwww.postgresql.fastware.com/­product-manualswww.lmdb.tech/­docsolr.apache.org/­resources.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperPostgreSQL Global Development Group, Fujitsu Australia Software TechnologySymasApache Software FoundationApache Software Foundation
Initial release201120062014
Current releaseFujitsu Enterprise Postgres 14, January 20220.9.32, January 20249.6.1, May 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen SourceOpen Source infoApache Version 2Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCCJavaScala
Server operating systemsLinux
Windows
Linux
Unix
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
OS X
Windows
Data schemeyesschema-freeyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateyesyes 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.noyesno
Secondary indexesyesnoyes infoAll search fields are automatically indexedno
SQL infoSupport of SQLyesnoSolr Parallel SQL InterfaceSQL-like DML and DDL statements
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Java API
RESTful HTTP/JSON API
JDBC
ODBC
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
C
C++
Clojure
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Nim
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Rust
Swift
Tcl
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsnoJava pluginsno
Triggersyesnoyes infoUser configurable commands triggered on index changesno
Partitioning methods infoMethods for storing different data on different nodespartitioning by range, list and by hashnoneShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnoneyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDoptimistic lockingno
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardnoyesno

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Fujitsu Enterprise PostgresLMDBSolrSpark SQL
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