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DBMS > Databricks vs. Kdb vs. Microsoft Azure AI Search vs. Sphinx

System Properties Comparison Databricks vs. Kdb vs. Microsoft Azure AI Search vs. Sphinx

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonKdb  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonSphinx  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.High performance Time Series DBMSSearch-as-a-service for web and mobile app developmentOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument store
Relational DBMS
Time Series DBMS
Vector DBMS
Search engineSearch engine
Secondary database modelsRelational DBMSVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score7.71
Rank#49  Overall
#2  Time Series DBMS
#1  Vector DBMS
Score5.52
Rank#59  Overall
#6  Search engines
Score5.95
Rank#55  Overall
#5  Search engines
Websitewww.databricks.comkx.comazure.microsoft.com/­en-us/­services/­searchsphinxsearch.com
Technical documentationdocs.databricks.comcode.kx.comlearn.microsoft.com/­en-us/­azure/­searchsphinxsearch.com/­docs
DeveloperDatabricksKx Systems, a division of First Derivatives plcMicrosoftSphinx Technologies Inc.
Initial release20132000 infokdb was released 2000, kdb+ in 200320152001
Current release3.6, May 2018V13.5.1, February 2023
License infoCommercial or Open Sourcecommercialcommercial infofree 32-bit versioncommercialOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageqC++
Server operating systemshostedLinux
OS X
Solaris
Windows
hostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyesyes
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.yesyesno
Secondary indexesyesyes infotable attribute 'grouped'yesyes infofull-text index on all search fields
SQL infoSupport of SQLwith Databricks SQLSQL-like query language (q)noSQL-like query language (SphinxQL)
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
RESTful HTTP APIProprietary protocol
Supported programming languagesPython
R
Scala
C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala
C#
Java
JavaScript
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresuser defined functions and aggregatesuser defined functionsnono
Triggersyes infowith viewsnono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningSharding 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 nodesyesSource-replica replicationyes infoImplicit feature of the cloud servicenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infosimilar paradigm used for internal processingnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes 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.noyesno
User concepts infoAccess controlrights management via user accountsyes infousing Azure authenticationno
More information provided by the system vendor
DatabricksKdbMicrosoft Azure AI SearchSphinx
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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Integrated columnar database & programming system for streaming, real time and historical...
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Competitive advantagesprovides seamless scalability; runs on industry standard server platforms; is top-ranked...
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Typical application scenariostick database streaming sensor data massive intelligence applications oil and gas...
» more
Key customersGoldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
» more
Market metricskdb+ performance and reliability proven by our customers in critical infrastructure...
» more
Licensing and pricing modelsupon request
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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DatabricksKdbMicrosoft Azure AI SearchSphinx
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