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DBMS > Datomic vs. Microsoft Azure Cosmos DB vs. Microsoft Azure Data Explorer vs. PostgreSQL

System Properties Comparison Datomic vs. Microsoft Azure Cosmos DB vs. Microsoft Azure Data Explorer vs. PostgreSQL

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonPostgreSQL  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityGlobally distributed, horizontally scalable, multi-model database serviceFully managed big data interactive analytics platformWidely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL
Primary database modelRelational DBMSDocument store
Graph DBMS
Key-value store
Wide column store
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.
Secondary database modelsSpatial 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
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
Score1.55
Rank#144  Overall
#67  Relational DBMS
Score24.97
Rank#27  Overall
#4  Document stores
#2  Graph DBMS
#3  Key-value stores
#3  Wide column stores
Score3.28
Rank#83  Overall
#45  Relational DBMS
Score644.36
Rank#4  Overall
#4  Relational DBMS
Websitewww.datomic.comazure.microsoft.com/­services/­cosmos-dbazure.microsoft.com/­services/­data-explorerwww.postgresql.org
Technical documentationdocs.datomic.comlearn.microsoft.com/­azure/­cosmos-dbdocs.microsoft.com/­en-us/­azure/­data-explorerwww.postgresql.org/­docs
DeveloperCognitectMicrosoftMicrosoftPostgreSQL Global Development Group infowww.postgresql.org/­developer
Initial release2012201420191989 info1989: Postgres, 1996: PostgreSQL
Current release1.0.7180, July 2024cloud service with continuous releases16.4, August 2024
License infoCommercial or Open Sourcecommercial infolimited edition freecommercialcommercialOpen Source infoBSD
Cloud-based only infoOnly available as a cloud servicenoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
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Implementation languageJava, ClojureC
Server operating systemsAll OS with a Java VMhostedhostedFreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
Data schemeyesschema-freeFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or dateyesyes infoJSON typesyes 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.noyesyes infospecific XML-type available, but no XML query functionality.
Secondary indexesyesyes infoAll properties auto-indexed by defaultall fields are automatically indexedyes
SQL infoSupport of SQLnoSQL-like query languageKusto Query Language (KQL), SQL subsetyes infostandard with numerous extensions
APIs and other access methodsRESTful HTTP APIDocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesClojure
Java
.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresyes infoTransaction FunctionsJavaScriptYes, possible languages: KQL, Python, Ruser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.
TriggersBy using transaction functionsJavaScriptyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersSharding infoImplicit feature of the cloud serviceSharding infoImplicit feature of the cloud servicepartitioning by range, list and (since PostgreSQL 11) by hash
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersyes infoImplicit feature of the cloud serviceyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replication infoother methods possible by using 3rd party extensions
MapReduce infoOffers an API for user-defined Map/Reduce methodsnowith Hadoop integration infoIntegration with Hadoop/HDInsight on Azure*Spark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyBounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency infoConsistency level configurable on request level
Session Consistency
Eventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDMulti-item ACID transactions with snapshot isolation within a partitionnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes inforecommended only for testing and developmentnono
User concepts infoAccess controlnoAccess rights can be defined down to the item levelAzure Active Directory Authenticationfine grained access rights according to SQL-standard

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More resources
DatomicMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDBMicrosoft Azure Data ExplorerPostgreSQL
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