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DBMS > Fujitsu Enterprise Postgres vs. Solr vs. Sqrrl vs. Yanza

System Properties Comparison Fujitsu Enterprise Postgres vs. Solr vs. Sqrrl vs. Yanza

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Editorial information provided by DB-Engines
NameFujitsu Enterprise Postgres  Xexclude from comparisonSolr  Xexclude from comparisonSqrrl  Xexclude from comparisonYanza  Xexclude from comparison
Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionEnterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.A widely used distributed, scalable search engine based on Apache LuceneAdaptable, secure NoSQL built on Apache AccumuloTime Series DBMS for IoT Applications
Primary database modelRelational DBMSSearch engineDocument store
Graph DBMS
Key-value store
Wide column store
Time Series DBMS
Secondary database modelsDocument store
Spatial DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.31
Rank#285  Overall
#129  Relational DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Websitewww.postgresql.fastware.comsolr.apache.orgsqrrl.comyanza.com
Technical documentationwww.postgresql.fastware.com/­product-manualssolr.apache.org/­resources.html
DeveloperPostgreSQL Global Development Group, Fujitsu Australia Software TechnologyApache Software FoundationAmazon infooriginally Sqrrl Data, Inc.Yanza
Initial release200620122015
Current releaseFujitsu Enterprise Postgres 14, January 20229.6.0, April 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2commercialcommercial infofree version available
Cloud-based only infoOnly available as a cloud servicenononono infobut mainly used as a service provided by Yanza
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCJavaJava
Server operating systemsLinux
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)LinuxWindows
Data schemeyesyes infoDynamic Fields enables on-the-fly addition of new fieldsschema-freeschema-free
Typing infopredefined data types such as float or dateyesyes infosupports customizable data types and automatic typingyesno
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
Secondary indexesyesyes infoAll search fields are automatically indexedyesno
SQL infoSupport of SQLyesSolr Parallel SQL Interfacenono
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Java API
RESTful HTTP/JSON API
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
HTTP API
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
any language that supports HTTP calls
Server-side scripts infoStored proceduresuser defined functionsJava pluginsnono
Triggersyesyes infoUser configurable commands triggered on index changesnoyes infoTimer and event based
Partitioning methods infoMethods for storing different data on different nodespartitioning by range, list and by hashShardingSharding infomaking use of Hadoopnone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyesselectable replication factor infomaking use of Hadoopnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.Immediate Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDoptimistic lockingAtomic updates per row, document, or graph entityno
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.yes
User concepts infoAccess controlfine grained access rights according to SQL-standardyesCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)no
More information provided by the system vendor
Fujitsu Enterprise PostgresSolrSqrrlYanza
Specific characteristics100% compatible with community PostgreSQL
» more
Competitive advantagesBuilt-in TDE and Data Masking security. In-Memory Columnar Index, and a high speed...
» more
Typical application scenariosTransactional payments applications, reporting and mixed workloads.
» more
Market metricsOver 30 years experience in database technology. Over 20 years in Postgres development...
» more
Licensing and pricing modelsCore based licensing
» more

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Fujitsu Enterprise PostgresSolrSqrrlYanza
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