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DBMS > Databricks vs. EDB Postgres vs. Microsoft Azure AI Search vs. Microsoft Azure Data Explorer vs. Sphinx

System Properties Comparison Databricks vs. EDB Postgres vs. Microsoft Azure AI Search vs. Microsoft Azure Data Explorer vs. Sphinx

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonEDB Postgres  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonMicrosoft Azure Data Explorer  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.The EDB Postgres Platform is an enterprise-class data management platform based on the open source database PostgreSQL with flexible deployment options and Oracle compatibility features, complemented by tool kits for management, integration, and migration.Search-as-a-service for web and mobile app developmentFully managed big data interactive analytics platformOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument store
Relational DBMS
Relational DBMSSearch engineRelational DBMS infocolumn orientedSearch engine
Secondary database modelsDocument store
Spatial DBMS
Vector DBMSDocument store infoIf a column is of type dynamic docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types/­dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store infothis is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine infosupport for complex search expressions docs.microsoft.com/­en-us/­azure/­kusto/­query/­parseoperator FTS, Geospatial docs.microsoft.com/­en-us/­azure/­kusto/­query/­geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score1.90
Rank#135  Overall
#63  Relational DBMS
Score5.59
Rank#63  Overall
#7  Search engines
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Websitewww.databricks.comwww.enterprisedb.comazure.microsoft.com/­en-us/­services/­searchazure.microsoft.com/­services/­data-explorersphinxsearch.com
Technical documentationdocs.databricks.comwww.enterprisedb.com/­docslearn.microsoft.com/­en-us/­azure/­searchdocs.microsoft.com/­en-us/­azure/­data-explorersphinxsearch.com/­docs
DeveloperDatabricksEnterpriseDBMicrosoftMicrosoftSphinx Technologies Inc.
Initial release20132005201520192001
Current release14, December 2021V1cloud service with continuous releases3.5.1, February 2023
License infoCommercial or Open Sourcecommercialcommercial infoBSD for PostgreSQL-componentscommercialcommercialOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesnoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCC++
Server operating systemshostedLinux
Windows
hostedhostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyesFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or dateyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesno
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.yesyes infospecific XML-type available, but no XML query functionality.noyes
Secondary indexesyesyesyesall fields are automatically indexedyes infofull-text index on all search fields
SQL infoSupport of SQLwith Databricks SQLyes infostandard with numerous extensionsnoKusto Query Language (KQL), SQL subsetSQL-like query language (SphinxQL)
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
RESTful HTTP APIMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Proprietary protocol
Supported programming languagesPython
R
Scala
.Net
C
C++
Delphi
Java
Perl
PHP
Python
Tcl
C#
Java
JavaScript
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
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 functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.noYes, possible languages: KQL, Python, Rno
Triggersyesnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning infoby hash, list or rangeSharding infoImplicit feature of the cloud serviceSharding 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 nodesyesMulti-source replicationyes infoImplicit feature of the cloud serviceyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnonono
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyesyes
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.nononono
User concepts infoAccess controlfine grained access rights according to SQL-standardyes infousing Azure authenticationAzure Active Directory Authenticationno
More information provided by the system vendor
DatabricksEDB PostgresMicrosoft Azure AI SearchMicrosoft Azure Data ExplorerSphinx
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksEDB PostgresMicrosoft Azure AI SearchMicrosoft Azure Data ExplorerSphinx
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