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DBMS > IBM Db2 Event Store vs. Microsoft Azure Data Explorer vs. PostgreSQL vs. SQLite vs. Stardog

System Properties Comparison IBM Db2 Event Store vs. Microsoft Azure Data Explorer vs. PostgreSQL vs. SQLite vs. Stardog

Editorial information provided by DB-Engines
NameIBM Db2 Event Store  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonPostgreSQL  Xexclude from comparisonSQLite  Xexclude from comparisonStardog  Xexclude from comparison
DescriptionDistributed Event Store optimized for Internet of Things use casesFully managed big data interactive analytics platformWidely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQLWidely used embeddable, in-process RDBMSEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization
Primary database modelEvent Store
Time Series DBMS
Relational DBMS infocolumn orientedRelational DBMS infowith object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.Relational DBMSGraph DBMS
RDF store
Secondary database modelsDocument 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 infowith Apache Age
Spatial DBMS
Vector DBMS infowith pgvector extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.18
Rank#315  Overall
#2  Event Stores
#26  Time Series DBMS
Score3.28
Rank#83  Overall
#45  Relational DBMS
Score644.36
Rank#4  Overall
#4  Relational DBMS
Score103.35
Rank#10  Overall
#7  Relational DBMS
Score1.93
Rank#121  Overall
#10  Graph DBMS
#6  RDF stores
Websitewww.ibm.com/­products/­db2-event-storeazure.microsoft.com/­services/­data-explorerwww.postgresql.orgwww.sqlite.orgwww.stardog.com
Technical documentationwww.ibm.com/­docs/­en/­db2-event-storedocs.microsoft.com/­en-us/­azure/­data-explorerwww.postgresql.org/­docswww.sqlite.org/­docs.htmldocs.stardog.com
DeveloperIBMMicrosoftPostgreSQL Global Development Group infowww.postgresql.org/­developerDwayne Richard HippStardog-Union
Initial release201720191989 info1989: Postgres, 1996: PostgreSQL20002010
Current release2.0cloud service with continuous releases16.4, August 20243.46.1  (13 August 2024), August 20247.3.0, May 2020
License infoCommercial or Open Sourcecommercial infofree developer edition availablecommercialOpen Source infoBSDOpen Source infoPublic Domaincommercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
PostgreSQL Flex @ STACKIT offers managed PostgreSQL Instances with adjustable CPU, RAM, storage amount and speed and several extensions available, in enterprise grade to perfectly match all application requirements. All 100% GDPR-compliant.
Implementation languageC and C++CCJava
Server operating systemsLinux infoLinux, macOS, Windows for the developer additionhostedFreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
server-lessLinux
macOS
Windows
Data schemeyesFixed schema with schema-less datatypes (dynamic)yesyes infodynamic column typesschema-free and OWL/RDFS-schema support
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-typesyesyes infonot rigid because of 'dynamic typing' concept.yes
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.noyesyes infospecific XML-type available, but no XML query functionality.nono infoImport/export of XML data possible
Secondary indexesnoall fields are automatically indexedyesyesyes infosupports real-time indexing in full-text and geospatial
SQL infoSupport of SQLyes infothrough the embedded Spark runtimeKusto Query Language (KQL), SQL subsetyes infostandard with numerous extensionsyes infoSQL-92 is not fully supportedYes, compatible with all major SQL variants through dedicated BI/SQL Server
APIs and other access methodsADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
ADO.NET infoinofficial driver
JDBC infoinofficial driver
ODBC infoinofficial driver
GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3
Supported programming languagesC
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Actionscript
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
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
Server-side scripts infoStored proceduresyesYes, possible languages: KQL, Python, Ruser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.nouser defined functions and aggregates, HTTP Server extensions in Java
Triggersnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyesyesyes infovia event handlers
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud servicepartitioning by range, list and (since PostgreSQL 11) by hashnonenone
Replication methods infoMethods for redundantly storing data on multiple nodesActive-active shard replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replication infoother methods possible by using 3rd party extensionsnoneMulti-source replication in HA-Cluster
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparknonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency in HA-Cluster
Foreign keys infoReferential integritynonoyesyesyes inforelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACIDACID
Concurrency infoSupport for concurrent manipulation of dataNo - written data is immutableyesyesyes infovia file-system locksyes
Durability infoSupport for making data persistentYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonoyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAzure Active Directory Authenticationfine grained access rights according to SQL-standardnoAccess rights for users and roles

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