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DBMS > Hyprcubd vs. PostgreSQL vs. Sphinx vs. Splice Machine vs. Yanza

System Properties Comparison Hyprcubd vs. PostgreSQL vs. Sphinx vs. Splice Machine vs. Yanza

Editorial information provided by DB-Engines
NameHyprcubd  Xexclude from comparisonPostgreSQL  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparisonYanza  Xexclude from comparison
Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionServerless Time Series DBMSWidely 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 SparkTime Series DBMS for IoT Applications
Primary database modelTime Series DBMSRelational DBMS infowith object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.Search engineRelational DBMSTime Series 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
Score645.54
Rank#4  Overall
#4  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitehyprcubd.com (offline)www.postgresql.orgsphinxsearch.comsplicemachine.comyanza.com
Technical documentationwww.postgresql.org/­docssphinxsearch.com/­docssplicemachine.com/­how-it-works
DeveloperHyprcubd, Inc.PostgreSQL Global Development Group infowww.postgresql.org/­developerSphinx Technologies Inc.Splice MachineYanza
Initial release1989 info1989: Postgres, 1996: PostgreSQL200120142015
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 availablecommercial infofree version available
Cloud-based only infoOnly available as a cloud serviceyesnononono infobut mainly used as a service provided by Yanza
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoCC++Java
Server operating systemshostedFreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Windows
Data schemeyesyesyesyesschema-free
Typing infopredefined data types such as float or dateyes infotime, int, uint, float, stringyesnoyesno
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.no
Secondary indexesnoyesyes infofull-text index on all search fieldsyesno
SQL infoSupport of SQLSQL-like query languageyes infostandard with numerous extensionsSQL-like query language (SphinxQL)yesno
APIs and other access methodsgRPC (https)ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Proprietary protocolJDBC
Native Spark Datasource
ODBC
HTTP API
Supported programming languages.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
any language that supports HTTP calls
Server-side scripts infoStored proceduresnouser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.noyes infoJavano
Triggersnoyesnoyesyes infoTimer and event based
Partitioning methods infoMethods for storing different data on different nodespartitioning by range, list and (since PostgreSQL 11) by hashSharding infoPartitioning is done manually, search queries against distributed index is supportedShared Nothhing Auto-Sharding, Columnar Partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication infoother methods possible by using 3rd party extensionsnoneMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACIDno
Concurrency infoSupport for concurrent manipulation of datanoyesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controltoken accessfine grained access rights according to SQL-standardnoAccess rights for users, groups and roles according to SQL-standardno

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More resources
HyprcubdPostgreSQLSphinxSplice MachineYanza
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