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DBMS > Databricks vs. Microsoft Azure AI Search vs. Sphinx vs. Valentina Server

System Properties Comparison Databricks vs. Microsoft Azure AI Search vs. Sphinx vs. Valentina Server

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonSphinx  Xexclude from comparisonValentina Server  Xexclude from comparison
DescriptionThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.Search-as-a-service for web and mobile app developmentOpen source search engine for searching in data from different sources, e.g. relational databasesObject-relational database and reports server
Primary database modelDocument store
Relational DBMS
Search engineSearch engineRelational DBMS
Secondary database modelsVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score84.24
Rank#14  Overall
#2  Document stores
#9  Relational DBMS
Score5.75
Rank#58  Overall
#7  Search engines
Score5.97
Rank#56  Overall
#5  Search engines
Score0.18
Rank#313  Overall
#140  Relational DBMS
Websitewww.databricks.comazure.microsoft.com/­en-us/­services/­searchsphinxsearch.comwww.valentina-db.net
Technical documentationdocs.databricks.comlearn.microsoft.com/­en-us/­azure/­searchsphinxsearch.com/­docsvalentina-db.com/­docs/­dokuwiki/­v5/­doku.php
DeveloperDatabricksMicrosoftSphinx Technologies Inc.Paradigma Software
Initial release2013201520011999
Current releaseV13.5.1, February 20235.7.5
License infoCommercial or Open SourcecommercialcommercialOpen Source infoGPL version 2, commercial licence availablecommercial
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++
Server operating systemshostedhostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyesyes
Typing infopredefined data types such as float or dateyesnoyes
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.yesno
Secondary indexesyesyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLwith Databricks SQLnoSQL-like query language (SphinxQL)yes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
RESTful HTTP APIProprietary protocolODBC
Supported programming languagesPython
R
Scala
C#
Java
JavaScript
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET
Server-side scripts infoStored proceduresuser defined functions and aggregatesnonoyes
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infoImplicit feature of the cloud servicenone
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 integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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 controlyes infousing Azure authenticationnofine grained access rights according to SQL-standard
More information provided by the system vendor
DatabricksMicrosoft Azure AI SearchSphinxValentina Server
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksMicrosoft Azure AI SearchSphinxValentina Server
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