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DBMS > Databricks vs. EDB Postgres vs. Hazelcast vs. Microsoft Azure Data Explorer vs. Microsoft Azure SQL Database

System Properties Comparison Databricks vs. EDB Postgres vs. Hazelcast vs. Microsoft Azure Data Explorer vs. Microsoft Azure SQL Database

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonEDB Postgres  Xexclude from comparisonHazelcast  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  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.A widely adopted in-memory data gridFully managed big data interactive analytics platformDatabase as a Service offering with high compatibility to Microsoft SQL Server
Primary database modelDocument store
Relational DBMS
Relational DBMSKey-value storeRelational DBMS infocolumn orientedRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
Document store infoJSON support with IMDG 3.12Document 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
Document store
Graph DBMS
Spatial DBMS
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
Score5.97
Rank#57  Overall
#6  Key-value stores
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score77.99
Rank#16  Overall
#11  Relational DBMS
Websitewww.databricks.comwww.enterprisedb.comhazelcast.comazure.microsoft.com/­services/­data-explorerazure.microsoft.com/­en-us/­products/­azure-sql/­database
Technical documentationdocs.databricks.comwww.enterprisedb.com/­docshazelcast.org/­imdg/­docsdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.microsoft.com/­en-us/­azure/­azure-sql
DeveloperDatabricksEnterpriseDBHazelcastMicrosoftMicrosoft
Initial release20132005200820192010
Current release14, December 20215.3.6, November 2023cloud service with continuous releasesV12
License infoCommercial or Open Sourcecommercialcommercial infoBSD for PostgreSQL-componentsOpen Source infoApache Version 2; commercial licenses availablecommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnonoyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCJavaC++
Server operating systemshostedLinux
Windows
All OS with a Java VMhostedhosted
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesschema-freeFixed 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-typesyes
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.yes infothe object must implement a serialization strategyyesyes
Secondary indexesyesyesyesall fields are automatically indexedyes
SQL infoSupport of SQLwith Databricks SQLyes infostandard with numerous extensionsSQL-like query languageKusto Query Language (KQL), SQL subsetyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JCache
JPA
Memcached protocol
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
ADO.NET
JDBC
ODBC
Supported programming languagesPython
R
Scala
.Net
C
C++
Delphi
Java
Perl
PHP
Python
Tcl
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
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.yes infoEvent Listeners, Executor ServicesYes, possible languages: KQL, Python, RTransact SQL
Triggersyesyes infoEventsyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning infoby hash, list or rangeShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replicationyes infoReplicated Mapyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes, with always 3 replicas available
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDone or two-phase-commit; repeatable reads; read commitednoACID
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardRole-based access controlAzure Active Directory Authenticationfine grained access rights according to SQL-standard
More information provided by the system vendor
DatabricksEDB PostgresHazelcastMicrosoft Azure Data ExplorerMicrosoft Azure SQL Database infoformerly SQL Azure
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksEDB PostgresHazelcastMicrosoft Azure Data ExplorerMicrosoft Azure SQL Database infoformerly SQL Azure
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