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DBMS > Fujitsu Enterprise Postgres vs. GridGain vs. IBM Db2 warehouse vs. Solr

System Properties Comparison Fujitsu Enterprise Postgres vs. GridGain vs. IBM Db2 warehouse vs. Solr

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Editorial information provided by DB-Engines
NameFujitsu Enterprise Postgres  Xexclude from comparisonGridGain  Xexclude from comparisonIBM Db2 warehouse infoformerly named IBM dashDB  Xexclude from comparisonSolr  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.GridGain is an in-memory computing platform, built on Apache IgniteCloud-based data warehousing serviceA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelRelational DBMSKey-value store
Relational DBMS
Relational DBMSSearch engine
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
Score1.55
Rank#150  Overall
#26  Key-value stores
#70  Relational DBMS
Score1.37
Rank#160  Overall
#74  Relational DBMS
Score41.02
Rank#24  Overall
#3  Search engines
Websitewww.postgresql.fastware.comwww.gridgain.comwww.ibm.com/­products/­db2/­warehousesolr.apache.org
Technical documentationwww.postgresql.fastware.com/­product-manualswww.gridgain.com/­docs/­index.htmlsolr.apache.org/­resources.html
DeveloperPostgreSQL Global Development Group, Fujitsu Australia Software TechnologyGridGain Systems, Inc.IBMApache Software Foundation
Initial release200720142006
Current releaseFujitsu Enterprise Postgres 14, January 2022GridGain 8.5.19.6.1, May 2024
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCJava, C++, .NetJava
Server operating systemsLinux
Windows
Linux
OS X
Solaris
Windows
hostedAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeyesyesyesyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesyesyesyes infosupports customizable data types and automatic typing
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.yesno infoImport/export of XML data possibleyes
Secondary indexesyesyesyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLyesANSI-99 for query and DML statements, subset of DDLyesSolr Parallel SQL Interface
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
.NET Client API
JDBC
ODBC
OLE DB
Java API
RESTful HTTP/JSON API
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C#
C++
Java
PHP
Python
Ruby
Scala
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresuser defined functionsyes (compute grid and cache interceptors can be used instead)PL/SQL, SQL PLJava plugins
Triggersyesyes (cache interceptors and events)yesyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodespartitioning by range, list and by hashShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyes (replicated cache)yesyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes (compute grid and hadoop accelerator)nospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDoptimistic locking
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.yesyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardSecurity Hooks for custom implementationsfine grained access rights according to SQL-standardyes

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More resources
Fujitsu Enterprise PostgresGridGainIBM Db2 warehouse infoformerly named IBM dashDBSolr
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