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DBMS > Hive vs. HyperSQL vs. Microsoft Azure AI Search vs. Oracle Berkeley DB vs. Sphinx

System Properties Comparison Hive vs. HyperSQL vs. Microsoft Azure AI Search vs. Oracle Berkeley DB vs. Sphinx

Editorial information provided by DB-Engines
NameHive  Xexclude from comparisonHyperSQL infoalso known as HSQLDB  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonSphinx  Xexclude from comparison
Descriptiondata warehouse software for querying and managing large distributed datasets, built on HadoopMultithreaded, transactional RDBMS written in Java infoalso known as HSQLDBSearch-as-a-service for web and mobile app developmentWidely used in-process key-value storeOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelRelational DBMSRelational DBMSSearch engineKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Search engine
Secondary database modelsVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score3.23
Rank#93  Overall
#48  Relational DBMS
Score5.52
Rank#59  Overall
#6  Search engines
Score2.01
Rank#126  Overall
#21  Key-value stores
#3  Native XML DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Websitehive.apache.orghsqldb.orgazure.microsoft.com/­en-us/­services/­searchwww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlsphinxsearch.com
Technical documentationcwiki.apache.org/­confluence/­display/­Hive/­Homehsqldb.org/­web/­hsqlDocsFrame.htmllearn.microsoft.com/­en-us/­azure/­searchdocs.oracle.com/­cd/­E17076_05/­html/­index.htmlsphinxsearch.com/­docs
DeveloperApache Software Foundation infoinitially developed by FacebookMicrosoftOracle infooriginally developed by Sleepycat, which was acquired by OracleSphinx Technologies Inc.
Initial release20122001201519942001
Current release3.1.3, April 20222.7.2, June 2023V118.1.40, May 20203.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infobased on BSD licensecommercialOpen Source infocommercial license availableOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC, Java, C++ (depending on the Berkeley DB edition)C++
Server operating systemsAll OS with a Java VMAll OS with a Java VM infoEmbedded (into Java applications) and Client-Server operating modeshostedAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesnono
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.nonoyes infoonly with the Berkeley DB XML edition
Secondary indexesyesyesyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-like DML and DDL statementsyesnoyes infoSQL interfaced based on SQLite is availableSQL-like query language (SphinxQL)
APIs and other access methodsJDBC
ODBC
Thrift
HTTP API infoJDBC via HTTP
JDBC
ODBC
RESTful HTTP APIProprietary protocol
Supported programming languagesC++
Java
PHP
Python
All languages supporting JDBC/ODBC
Java
C#
Java
JavaScript
Python
.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceJava, SQLnonono
Triggersnoyesnoyes infoonly for the SQL APIno
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding infoImplicit feature of the cloud servicenoneSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornoneyes infoImplicit feature of the cloud serviceSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenononono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes 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.yesnoyes
User concepts infoAccess controlAccess rights for users, groups and rolesfine grained access rights according to SQL-standardyes infousing Azure authenticationnono

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More resources
HiveHyperSQL infoalso known as HSQLDBMicrosoft Azure AI SearchOracle Berkeley DBSphinx
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