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DBMS > Databricks vs. IBM Db2 vs. Microsoft Azure Data Explorer vs. PouchDB vs. SQLite

System Properties Comparison Databricks vs. IBM Db2 vs. Microsoft Azure Data Explorer vs. PouchDB vs. SQLite

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 comparisonPouchDB  Xexclude from comparisonSQLite  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 platformJavaScript DBMS with an API inspired by CouchDBWidely used embeddable, in-process RDBMS
Primary database modelDocument store
Relational DBMS
Relational DBMS infoSince Version 10.5 support for JSON/BSON documents compatible with MongoDBRelational DBMS infocolumn orientedDocument storeRelational 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
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score84.24
Rank#14  Overall
#2  Document stores
#9  Relational DBMS
Score123.05
Rank#9  Overall
#6  Relational DBMS
Score3.28
Rank#83  Overall
#45  Relational DBMS
Score2.18
Rank#114  Overall
#21  Document stores
Score103.35
Rank#10  Overall
#7  Relational DBMS
Websitewww.databricks.comwww.ibm.com/­products/­db2azure.microsoft.com/­services/­data-explorerpouchdb.comwww.sqlite.org
Technical documentationdocs.databricks.comwww.ibm.com/­docs/­en/­db2docs.microsoft.com/­en-us/­azure/­data-explorerpouchdb.com/­guideswww.sqlite.org/­docs.html
DeveloperDatabricksIBMMicrosoftApache Software FoundationDwayne Richard Hipp
Initial release20131983 infohost version201920122000
Current release12.1, October 2016cloud service with continuous releases7.1.1, June 20193.46.1  (13 August 2024), August 2024
License infoCommercial or Open Sourcecommercialcommercial infofree version is availablecommercialOpen SourceOpen Source infoPublic Domain
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++JavaScriptC
Server operating systemshostedAIX
HP-UX
Linux
Solaris
Windows
z/OS
hostedserver-less, requires a JavaScript environment (browser, Node.js)server-less
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesFixed schema with schema-less datatypes (dynamic)schema-freeyes infodynamic column types
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-typesnoyes infonot rigid because of 'dynamic typing' concept.
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.yesyesnono
Secondary indexesyesyesall fields are automatically indexedyes infovia viewsyes
SQL infoSupport of SQLwith Databricks SQLyesKusto Query Language (KQL), SQL subsetnoyes infoSQL-92 is not fully supported
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
HTTP REST infoonly for PouchDB Server
JavaScript API
ADO.NET infoinofficial driver
JDBC infoinofficial driver
ODBC infoinofficial driver
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
JavaScriptActionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl
Server-side scripts infoStored proceduresuser defined functions and aggregatesyesYes, possible languages: KQL, Python, RView functions in JavaScriptno
Triggersyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyesyes
Partitioning methods infoMethods for storing different data on different nodesSharding infoonly with Windows/Unix/Linux VersionSharding infoImplicit feature of the cloud serviceSharding infowith a proxy-based framework, named couchdb-loungenone
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.Multi-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency
Foreign keys infoReferential integrityyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infovia file-system locks
Durability infoSupport for making data persistentyesyesyesyes infoby using IndexedDB, WebSQL or LevelDB as backendyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAzure Active Directory Authenticationnono
More information provided by the system vendor
DatabricksIBM Db2 infoformerly named DB2 or IBM Database 2Microsoft Azure Data ExplorerPouchDBSQLite
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 ExplorerPouchDBSQLite
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