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DBMS > atoti vs. Microsoft Azure AI Search vs. OpenMLDB vs. Sphinx

System Properties Comparison atoti vs. Microsoft Azure AI Search vs. OpenMLDB vs. Sphinx

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Editorial information provided by DB-Engines
Nameatoti  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonOpenMLDB  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionAn in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.Search-as-a-service for web and mobile app developmentAn open-source machine learning database that provides a feature platform for training and inferenceOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelObject oriented DBMSSearch engineTime Series DBMSSearch engine
Secondary database modelsVector DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.61
Rank#243  Overall
#10  Object oriented DBMS
Score5.52
Rank#59  Overall
#6  Search engines
Score0.10
Rank#359  Overall
#36  Time Series DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Websiteatoti.ioazure.microsoft.com/­en-us/­services/­searchopenmldb.aisphinxsearch.com
Technical documentationdocs.atoti.iolearn.microsoft.com/­en-us/­azure/­searchopenmldb.ai/­docs/­zh/­mainsphinxsearch.com/­docs
DeveloperActiveViamMicrosoft4 Paradigm Inc.Sphinx Technologies Inc.
Initial release201520202001
Current releaseV12024-2 February 20243.5.1, February 2023
License infoCommercial or Open Sourcecommercial infofree versions availablecommercialOpen SourceOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++, Java, ScalaC++
Server operating systemshostedLinuxFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesFixed schemayes
Typing infopredefined data types such as float or dateyesyesno
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.nono
Secondary indexesyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLMultidimensional Expressions (MDX)noyesSQL-like query language (SphinxQL)
APIs and other access methodsRESTful HTTP APIJDBC
SQLAlchemy
Proprietary protocol
Supported programming languagesC#
Java
JavaScript
Python
C++
Go
Java
Python
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresPythonnonono
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesSharding, horizontal partitioningSharding infoImplicit feature of the cloud servicehorizontal partitioningSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud serviceSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonono
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yesyesyes
Durability infoSupport for making data persistentyesyesyes 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 controlyes infousing Azure authenticationfine grained access rights according to SQL-standardno

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More resources
atotiMicrosoft Azure AI SearchOpenMLDBSphinx
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