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DBMS > EsgynDB vs. PostgreSQL vs. Sphinx vs. Splice Machine

System Properties Comparison EsgynDB vs. PostgreSQL vs. Sphinx vs. Splice Machine

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Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonPostgreSQL  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionWidely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQLOpen source search engine for searching in data from different sources, e.g. relational databasesOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSRelational DBMS infowith object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.Search engineRelational DBMS
Secondary database modelsDocument store
Graph DBMS infowith Apache Age
Spatial DBMS
Vector DBMS infowith pgvector extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score645.54
Rank#4  Overall
#4  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitewww.esgyn.cnwww.postgresql.orgsphinxsearch.comsplicemachine.com
Technical documentationwww.postgresql.org/­docssphinxsearch.com/­docssplicemachine.com/­how-it-works
DeveloperEsgynPostgreSQL Global Development Group infowww.postgresql.org/­developerSphinx Technologies Inc.Splice Machine
Initial release20151989 info1989: Postgres, 1996: PostgreSQL20012014
Current release16.3, May 20243.5.1, February 20233.1, March 2021
License infoCommercial or Open SourcecommercialOpen Source infoBSDOpen Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, JavaCC++Java
Server operating systemsLinuxFreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesnoyes
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 infospecific XML-type available, but no XML query functionality.
Secondary indexesyesyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLyesyes infostandard with numerous extensionsSQL-like query language (SphinxQL)yes
APIs and other access methodsADO.NET
JDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Proprietary protocolJDBC
Native Spark Datasource
ODBC
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.Net.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresJava Stored Proceduresuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.noyes infoJava
Triggersnoyesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingpartitioning by range, list and (since PostgreSQL 11) by hashSharding infoPartitioning is done manually, search queries against distributed index is supportedShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersSource-replica replication infoother methods possible by using 3rd party extensionsnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardnoAccess rights for users, groups and roles according to SQL-standard

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More resources
EsgynDBPostgreSQLSphinxSplice Machine
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