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DBMS > Drizzle vs. Microsoft Azure Data Explorer vs. PostgreSQL vs. Spark SQL vs. Trafodion

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

Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonPostgreSQL  Xexclude from comparisonSpark SQL  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.
DescriptionMySQL 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 SQLSpark SQL is a component on top of 'Spark Core' for structured data processingTransactional SQL-on-Hadoop DBMS
Primary database modelRelational 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 DBMSRelational 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
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score636.25
Rank#4  Overall
#4  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websiteazure.microsoft.com/­services/­data-explorerwww.postgresql.orgspark.apache.org/­sqltrafodion.apache.org
Technical documentationdocs.microsoft.com/­en-us/­azure/­data-explorerwww.postgresql.org/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.htmltrafodion.apache.org/­documentation.html
DeveloperDrizzle project, originally started by Brian AkerMicrosoftPostgreSQL Global Development Group infowww.postgresql.org/­developerApache Software FoundationApache Software Foundation, originally developed by HP
Initial release200820191989 info1989: Postgres, 1996: PostgreSQL20142014
Current release7.2.4, September 2012cloud service with continuous releases16.3, May 20243.5.0 ( 2.13), September 20232.3.0, February 2019
License infoCommercial or Open SourceOpen Source infoGNU GPLcommercialOpen Source infoBSDOpen Source infoApache 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnonono
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Implementation languageC++CScalaC++, Java
Server operating systemsFreeBSD
Linux
OS X
hostedFreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
Linux
OS X
Windows
Linux
Data schemeyesFixed schema with schema-less datatypes (dynamic)yesyesyes
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-typesyesyesyes
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.yesyes infospecific XML-type available, but no XML query functionality.nono
Secondary indexesyesall fields are automatically indexedyesnoyes
SQL infoSupport of SQLyes infowith proprietary extensionsKusto Query Language (KQL), SQL subsetyes infostandard with numerous extensionsSQL-like DML and DDL statementsyes
APIs and other access methodsJDBCMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
ADO.NET
JDBC
ODBC
Supported programming languagesC
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
Java
Python
R
Scala
All languages supporting JDBC/ODBC/ADO.Net
Server-side scripts infoStored proceduresnoYes, possible languages: KQL, Python, Ruser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.noJava Stored Procedures
Triggersno infohooks for callbacks inside the server can be used.yes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud servicepartitioning by range, list and (since PostgreSQL 11) by hashyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-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 extensionsnoneyes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparknoyes infovia user defined functions and HBase
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDnoACID
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.nononono
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPAzure Active Directory Authenticationfine grained access rights according to SQL-standardnofine grained access rights according to SQL-standard

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More resources
DrizzleMicrosoft Azure Data ExplorerPostgreSQLSpark SQLTrafodion
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