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DBMS > Kinetica vs. Microsoft Azure Data Explorer vs. Postgres-XL vs. PostgreSQL vs. Sqrrl

System Properties Comparison Kinetica vs. Microsoft Azure Data Explorer vs. Postgres-XL vs. PostgreSQL vs. Sqrrl

Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonPostgres-XL  Xexclude from comparisonPostgreSQL  Xexclude from comparisonSqrrl  Xexclude from comparison
Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.
DescriptionFully vectorized database across both GPUs and CPUsFully managed big data interactive analytics platformBased on PostgreSQL enhanced with MPP and write-scale-out cluster featuresWidely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQLAdaptable, secure NoSQL built on Apache Accumulo
Primary database modelRelational DBMSRelational DBMS infocolumn orientedRelational DBMSRelational DBMS infowith object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.Document store
Graph DBMS
Key-value store
Wide column store
Secondary database modelsSpatial DBMS
Time Series DBMS
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
Document store
Spatial DBMS
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
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score0.49
Rank#256  Overall
#117  Relational DBMS
Score645.54
Rank#4  Overall
#4  Relational DBMS
Websitewww.kinetica.comazure.microsoft.com/­services/­data-explorerwww.postgres-xl.orgwww.postgresql.orgsqrrl.com
Technical documentationdocs.kinetica.comdocs.microsoft.com/­en-us/­azure/­data-explorerwww.postgres-xl.org/­documentationwww.postgresql.org/­docs
DeveloperKineticaMicrosoftPostgreSQL Global Development Group infowww.postgresql.org/­developerAmazon infooriginally Sqrrl Data, Inc.
Initial release201220192014 infosince 2012, originally named StormDB1989 info1989: Postgres, 1996: PostgreSQL2012
Current release7.1, August 2021cloud service with continuous releases10 R1, October 201816.3, May 2024
License infoCommercial or Open SourcecommercialcommercialOpen Source infoMozilla public licenseOpen Source infoBSDcommercial
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++CCJava
Server operating systemsLinuxhostedLinux
macOS
FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
Linux
Data schemeyesFixed schema with schema-less datatypes (dynamic)yesyesschema-free
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.noyesyes infoXML type, but no XML query functionalityyes infospecific XML-type available, but no XML query functionality.
Secondary indexesyesall fields are automatically indexedyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsKusto Query Language (KQL), SQL subsetyes infodistributed, parallel query executionyes infostandard with numerous extensionsno
APIs and other access methodsJDBC
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
JDBC
native C library
ODBC
streaming API for large objects
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
Server-side scripts infoStored proceduresuser defined functionsYes, possible languages: KQL, Python, Ruser defined functionsuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.no
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangeyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyesyesno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud servicehorizontal partitioningpartitioning by range, list and (since PostgreSQL 11) by hashSharding infomaking use of Hadoop
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica 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 extensionsselectable replication factor infomaking use of Hadoop
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparknonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate ConsistencyImmediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.
Foreign keys infoReferential integrityyesnoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID infoMVCCACIDAtomic updates per row, document, or graph entity
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.yes infoGPU vRAM or System RAMnonono
User concepts infoAccess controlAccess rights for users and roles on table levelAzure Active Directory Authenticationfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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KineticaMicrosoft Azure Data ExplorerPostgres-XLPostgreSQLSqrrl
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