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DBMS > Elasticsearch vs. Fujitsu Enterprise Postgres vs. Graph Engine vs. HugeGraph vs. Sphinx

System Properties Comparison Elasticsearch vs. Fujitsu Enterprise Postgres vs. Graph Engine vs. HugeGraph vs. Sphinx

Editorial information provided by DB-Engines
NameElasticsearch  Xexclude from comparisonFujitsu Enterprise Postgres  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonHugeGraph  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionA distributed, RESTful modern search and analytics engine based on Apache Lucene infoElasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metricEnterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineA fast-speed and highly-scalable Graph DBMSOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelSearch engineRelational DBMSGraph DBMS
Key-value store
Graph DBMSSearch engine
Secondary database modelsDocument store
Spatial DBMS
Vector DBMS
Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score135.35
Rank#7  Overall
#1  Search engines
Score0.31
Rank#285  Overall
#129  Relational DBMS
Score0.61
Rank#240  Overall
#21  Graph DBMS
#35  Key-value stores
Score0.13
Rank#336  Overall
#32  Graph DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Websitewww.elastic.co/­elasticsearchwww.postgresql.fastware.comwww.graphengine.iogithub.com/­hugegraph
hugegraph.apache.org
sphinxsearch.com
Technical documentationwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmlwww.postgresql.fastware.com/­product-manualswww.graphengine.io/­docs/­manualhugegraph.apache.org/­docssphinxsearch.com/­docs
DeveloperElasticPostgreSQL Global Development Group, Fujitsu Australia Software TechnologyMicrosoftBaiduSphinx Technologies Inc.
Initial release2010201020182001
Current release8.6, January 2023Fujitsu Enterprise Postgres 14, January 20220.93.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoElastic LicensecommercialOpen Source infoMIT LicenseOpen Source infoApache Version 2.0Open Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC.NET and CJavaC++
Server operating systemsAll OS with a Java VMLinux
Windows
.NETLinux
macOS
Unix
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-free infoFlexible type definitions. Once a type is defined, it is persistentyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyesno
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.nonono
Secondary indexesyes infoAll search fields are automatically indexedyesyes infoalso supports composite index and range indexyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-like query languageyesnonoSQL-like query language (SphinxQL)
APIs and other access methodsJava API
RESTful HTTP/JSON API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
RESTful HTTP APIJava API
RESTful HTTP API
TinkerPop Gremlin
Proprietary protocol
Supported programming languages.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C#
C++
F#
Visual Basic
Groovy
Java
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresyesuser defined functionsyesasynchronous Gremlin script jobsno
Triggersyes infoby using the 'percolation' featureyesnonono
Partitioning methods infoMethods for storing different data on different nodesShardingpartitioning by range, list and by hashhorizontal partitioningyes infodepending on used storage backend, e.g. Cassandra and HBaseSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationyes infodepending on used storage backend, e.g. Cassandra and HBasenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsES-Hadoop Connectornovia hugegraph-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infoSynchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, allImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyesnoyes infoedges in graphno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyesyes
Durability infoSupport for making data persistentyesyesoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyesyes 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.Memcached and Redis integrationyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardUsers, roles and permissionsno
More information provided by the system vendor
ElasticsearchFujitsu Enterprise PostgresGraph Engine infoformer name: TrinityHugeGraphSphinx
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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More resources
ElasticsearchFujitsu Enterprise PostgresGraph Engine infoformer name: TrinityHugeGraphSphinx
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