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DBMS > Microsoft Azure AI Search vs. Oracle Berkeley DB vs. Sphinx vs. Splice Machine

System Properties Comparison Microsoft Azure AI Search vs. Oracle Berkeley DB vs. Sphinx vs. Splice Machine

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Editorial information provided by DB-Engines
NameMicrosoft Azure AI Search  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionSearch-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 databasesOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelSearch engineKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Search engineRelational DBMS
Secondary database modelsVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score5.59
Rank#63  Overall
#7  Search engines
Score2.21
Rank#117  Overall
#20  Key-value stores
#3  Native XML DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websiteazure.microsoft.com/­en-us/­services/­searchwww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlsphinxsearch.comsplicemachine.com
Technical documentationlearn.microsoft.com/­en-us/­azure/­searchdocs.oracle.com/­cd/­E17076_05/­html/­index.htmlsphinxsearch.com/­docssplicemachine.com/­how-it-works
DeveloperMicrosoftOracle infooriginally developed by Sleepycat, which was acquired by OracleSphinx Technologies Inc.Splice Machine
Initial release2015199420012014
Current releaseV118.1.40, May 20203.5.1, February 20233.1, March 2021
License infoCommercial or Open SourcecommercialOpen Source infocommercial license availableOpen Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, Java, C++ (depending on the Berkeley DB edition)C++Java
Server operating systemshostedAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesnonoyes
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 infoonly with the Berkeley DB XML edition
Secondary indexesyesyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLnoyes infoSQL interfaced based on SQLite is availableSQL-like query language (SphinxQL)yes
APIs and other access methodsRESTful HTTP APIProprietary protocolJDBC
Native Spark Datasource
ODBC
Supported programming languagesC#
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
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnononoyes infoJava
Triggersnoyes infoonly for the SQL APInoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud servicenoneSharding 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 nodesyes infoImplicit feature of the cloud serviceSource-replica replicationnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, 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.noyesyes
User concepts infoAccess controlyes infousing Azure authenticationnonoAccess rights for users, groups and roles according to SQL-standard

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More resources
Microsoft Azure AI SearchOracle Berkeley DBSphinxSplice Machine
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