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DBMS > Apache Druid vs. Fujitsu Enterprise Postgres vs. Solr vs. Sphinx

System Properties Comparison Apache Druid vs. Fujitsu Enterprise Postgres vs. Solr vs. Sphinx

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonFujitsu Enterprise Postgres  Xexclude from comparisonSolr  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataEnterprise-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 LuceneOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSSearch engineSearch engine
Secondary database modelsDocument store
Spatial DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.34
Rank#88  Overall
#48  Relational DBMS
#7  Time Series DBMS
Score0.31
Rank#285  Overall
#129  Relational DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Score5.98
Rank#56  Overall
#5  Search engines
Websitedruid.apache.orgwww.postgresql.fastware.comsolr.apache.orgsphinxsearch.com
Technical documentationdruid.apache.org/­docs/­latest/­designwww.postgresql.fastware.com/­product-manualssolr.apache.org/­resources.htmlsphinxsearch.com/­docs
DeveloperApache Software Foundation and contributorsPostgreSQL Global Development Group, Fujitsu Australia Software TechnologyApache Software FoundationSphinx Technologies Inc.
Initial release201220062001
Current release29.0.1, April 2024Fujitsu Enterprise Postgres 14, January 20229.6.0, April 20243.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache license v2commercialOpen Source infoApache Version 2Open Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaCJavaC++
Server operating systemsLinux
OS X
Unix
Linux
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyes infoschema-less columns are supportedyesyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateyesyesyes infosupports customizable data types and automatic typingno
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 indexesyesyesyes infoAll search fields are automatically indexedyes infofull-text index on all search fields
SQL infoSupport of SQLSQL for queryingyesSolr Parallel SQL InterfaceSQL-like query language (SphinxQL)
APIs and other access methodsJDBC
RESTful HTTP/JSON API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Java API
RESTful HTTP/JSON API
Proprietary protocol
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
.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
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnouser defined functionsJava pluginsno
Triggersnoyesyes infoUser configurable commands triggered on index changesno
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedpartitioning by range, list and by hashShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesSource-replica replicationyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDoptimistic lockingno
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemfine grained access rights according to SQL-standardyesno
More information provided by the system vendor
Apache DruidFujitsu Enterprise PostgresSolrSphinx
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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Apache DruidFujitsu Enterprise PostgresSolrSphinx
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