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DBMS > Datomic vs. Drizzle vs. Microsoft Azure Data Explorer vs. PostgreSQL vs. Trafodion

System Properties Comparison Datomic vs. Drizzle vs. Microsoft Azure Data Explorer vs. PostgreSQL vs. Trafodion

Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonDrizzle  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonPostgreSQL  Xexclude from comparisonTrafodion  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Fully managed big data interactive analytics platformWidely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQLTransactional SQL-on-Hadoop DBMS
Primary database modelRelational DBMSRelational DBMSRelational 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 DBMS
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
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score636.25
Rank#4  Overall
#4  Relational DBMS
Websitewww.datomic.comazure.microsoft.com/­services/­data-explorerwww.postgresql.orgtrafodion.apache.org
Technical documentationdocs.datomic.comdocs.microsoft.com/­en-us/­azure/­data-explorerwww.postgresql.org/­docstrafodion.apache.org/­documentation.html
DeveloperCognitectDrizzle project, originally started by Brian AkerMicrosoftPostgreSQL Global Development Group infowww.postgresql.org/­developerApache Software Foundation, originally developed by HP
Initial release2012200820191989 info1989: Postgres, 1996: PostgreSQL2014
Current release1.0.7075, December 20237.2.4, September 2012cloud service with continuous releases16.3, May 20242.3.0, February 2019
License infoCommercial or Open Sourcecommercial infolimited edition freeOpen Source infoGNU GPLcommercialOpen Source infoBSDOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesnono
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Implementation languageJava, ClojureC++CC++, Java
Server operating systemsAll OS with a Java VMFreeBSD
Linux
OS X
hostedFreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
Linux
Data schemeyesyesFixed schema with schema-less datatypes (dynamic)yesyes
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-typesyesyes
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.no
Secondary indexesyesyesall fields are automatically indexedyesyes
SQL infoSupport of SQLnoyes infowith proprietary extensionsKusto Query Language (KQL), SQL subsetyes infostandard with numerous extensionsyes
APIs and other access methodsRESTful HTTP APIJDBCMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
ADO.NET
JDBC
ODBC
Supported programming languagesClojure
Java
C
C++
Java
PHP
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
All languages supporting JDBC/ODBC/ADO.Net
Server-side scripts infoStored proceduresyes infoTransaction FunctionsnoYes, possible languages: KQL, Python, Ruser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.Java Stored Procedures
TriggersBy using transaction functionsno infohooks for callbacks inside the server can be used.yes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyesno
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShardingSharding infoImplicit feature of the cloud servicepartitioning by range, list and (since PostgreSQL 11) by hashSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersMulti-source replication
Source-replica replication
yes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replication infoother methods possible by using 3rd party extensionsyes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoSpark connector (open source): github.com/­Azure/­azure-kusto-sparknoyes infovia user defined functions and HBase
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyesyes
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 developmentnonono
User concepts infoAccess controlnoPluggable authentication mechanisms infoe.g. LDAP, HTTPAzure Active Directory Authenticationfine grained access rights according to SQL-standardfine grained access rights according to SQL-standard

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More resources
DatomicDrizzleMicrosoft Azure Data ExplorerPostgreSQLTrafodion
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