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DBMS > Databricks vs. IBM Db2 vs. Microsoft Azure Data Explorer vs. Solr vs. UniData,UniVerse

System Properties Comparison Databricks vs. IBM Db2 vs. Microsoft Azure Data Explorer vs. Solr vs. UniData,UniVerse

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonIBM Db2 infoformerly named DB2 or IBM Database 2  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSolr  Xexclude from comparisonUniData,UniVerse  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.Common in IBM host environments, 2 different versions for host and Windows/LinuxFully managed big data interactive analytics platformA widely used distributed, scalable search engine based on Apache LuceneMultiValue database and application server with SQL mapping layer and meta database capabilities
Primary database modelDocument store
Relational DBMS
Relational DBMS infoSince Version 10.5 support for JSON/BSON documents compatible with MongoDBRelational DBMS infocolumn orientedSearch engineMultivalue DBMS
Secondary database modelsDocument store
RDF store infoin Db2 LUW (Linux, Unix, Windows)
Spatial DBMS infowith Db2 Spatial Extender
Document 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
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
Score128.46
Rank#8  Overall
#5  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Score3.16
Rank#97  Overall
#2  Multivalue DBMS
Websitewww.databricks.comwww.ibm.com/­products/­db2azure.microsoft.com/­services/­data-explorersolr.apache.orgwww.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-unidata
Technical documentationdocs.databricks.comwww.ibm.com/­docs/­en/­db2docs.microsoft.com/­en-us/­azure/­data-explorersolr.apache.org/­resources.htmldocs.rocketsoftware.com/­bundle?cluster=true&labelkey=unidata&labelkey=prod_unidata
DeveloperDatabricksIBMMicrosoftApache Software FoundationRocket Software
Initial release20131983 infohost version201920061985
Current release12.1, October 2016cloud service with continuous releases9.6.0, April 2024
License infoCommercial or Open Sourcecommercialcommercial infofree version is availablecommercialOpen Source infoApache Version 2commercial
Cloud-based only infoOnly available as a cloud serviceyesnoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC and C++JavaC
Server operating systemshostedAIX
HP-UX
Linux
Solaris
Windows
z/OS
hostedAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)AIX
HP-UX
Linux
Solaris
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesFixed schema with schema-less datatypes (dynamic)yes infoDynamic Fields enables on-the-fly addition of new fieldsschema-free
Typing infopredefined data types such as float or dateyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyes infosupports customizable data types and automatic typingoptional
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.yesyesyes
Secondary indexesyesyesall fields are automatically indexedyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLwith Databricks SQLyesKusto Query Language (KQL), SQL subsetSolr Parallel SQL Interfaceyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
JSON style queries infoMongoDB compatible
ODBC
XQuery
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Java API
RESTful HTTP/JSON API
Java API infoJPA
JDBC
ODBC
OLE DB
Proprietary protocol
RESTful HTTP API
SOAP-based API
Supported programming languagesPython
R
Scala
C
C#
C++
Cobol
Delphi
Fortran
Java
Perl
PHP
Python
Ruby
Visual Basic
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
.Net
Basic infoU2 Basic
C
Java
Server-side scripts infoStored proceduresuser defined functions and aggregatesyesYes, possible languages: KQL, Python, RJava pluginsyes
Triggersyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infoUser configurable commands triggered on index changesyes infoU2 Basic
Partitioning methods infoMethods for storing different data on different nodesSharding infoonly with Windows/Unix/Linux VersionSharding infoImplicit feature of the cloud serviceShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infowith separate tools (MQ, InfoSphere)yes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnooptimistic lockingACID infoconfigurable
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.nonoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAzure Active Directory AuthenticationyesAccess rights according to SQL-standard and operating system based
More information provided by the system vendor
DatabricksIBM Db2 infoformerly named DB2 or IBM Database 2Microsoft Azure Data ExplorerSolrUniData,UniVerse
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksIBM Db2 infoformerly named DB2 or IBM Database 2Microsoft Azure Data ExplorerSolrUniData,UniVerse
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