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DBMS > CouchDB vs. Hazelcast vs. Microsoft Azure Data Explorer vs. Microsoft Azure SQL Database vs. Postgres-XL

System Properties Comparison CouchDB vs. Hazelcast vs. Microsoft Azure Data Explorer vs. Microsoft Azure SQL Database vs. Postgres-XL

Editorial information provided by DB-Engines
NameCouchDB infostands for "Cluster Of Unreliable Commodity Hardware"  Xexclude from comparisonHazelcast  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparisonPostgres-XL  Xexclude from comparison
DescriptionA native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.A widely adopted in-memory data gridFully managed big data interactive analytics platformDatabase as a Service offering with high compatibility to Microsoft SQL ServerBased on PostgreSQL enhanced with MPP and write-scale-out cluster features
Primary database modelDocument storeKey-value storeRelational DBMS infocolumn orientedRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS infousing the Geocouch extensionDocument store infoJSON support with IMDG 3.12Document 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
Spatial DBMS
Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score8.30
Rank#47  Overall
#7  Document stores
Score5.46
Rank#61  Overall
#7  Key-value stores
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score76.78
Rank#16  Overall
#11  Relational DBMS
Score0.53
Rank#254  Overall
#117  Relational DBMS
Websitecouchdb.apache.orghazelcast.comazure.microsoft.com/­services/­data-explorerazure.microsoft.com/­en-us/­products/­azure-sql/­databasewww.postgres-xl.org
Technical documentationdocs.couchdb.org/­en/­stablehazelcast.org/­imdg/­docsdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.microsoft.com/­en-us/­azure/­azure-sqlwww.postgres-xl.org/­documentation
DeveloperApache Software Foundation infoApache top-level project, originally developed by Damien Katz, a former Lotus Notes developerHazelcastMicrosoftMicrosoft
Initial release20052008201920102014 infosince 2012, originally named StormDB
Current release3.3.3, December 20235.3.6, November 2023cloud service with continuous releasesV1210 R1, October 2018
License infoCommercial or Open SourceOpen Source infoApache version 2Open Source infoApache Version 2; commercial licenses availablecommercialcommercialOpen Source infoMozilla public license
Cloud-based only infoOnly available as a cloud servicenonoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageErlangJavaC++C
Server operating systemsAndroid
BSD
Linux
OS X
Solaris
Windows
All OS with a Java VMhostedhostedLinux
macOS
Data schemeschema-freeschema-freeFixed schema with schema-less datatypes (dynamic)yesyes
Typing infopredefined data types such as float or datenoyesyes 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.noyes infothe object must implement a serialization strategyyesyesyes infoXML type, but no XML query functionality
Secondary indexesyes infovia viewsyesall fields are automatically indexedyesyes
SQL infoSupport of SQLnoSQL-like query languageKusto Query Language (KQL), SQL subsetyesyes infodistributed, parallel query execution
APIs and other access methodsRESTful HTTP/JSON APIJCache
JPA
Memcached protocol
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
ADO.NET
JDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresView functions in JavaScriptyes infoEvent Listeners, Executor ServicesYes, possible languages: KQL, Python, RTransact SQLuser defined functions
Triggersyesyes infoEventsyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyesyes
Partitioning methods infoMethods for storing different data on different nodesSharding infoimproved architecture with release 2.0ShardingSharding infoImplicit feature of the cloud servicehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yes infoReplicated Mapyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes, with always 3 replicas available
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoatomic operations within a single document possibleone or two-phase-commit; repeatable reads; read commitednoACIDACID infoMVCC
Concurrency infoSupport for concurrent manipulation of datayes infostrategy: optimistic lockingyesyesyesyes
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.noyesnono
User concepts infoAccess controlAccess rights for users can be defined per databaseRole-based access controlAzure Active Directory Authenticationfine grained access rights according to SQL-standardfine grained access rights according to SQL-standard

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CouchDB infostands for "Cluster Of Unreliable Commodity Hardware"HazelcastMicrosoft Azure Data ExplorerMicrosoft Azure SQL Database infoformerly SQL AzurePostgres-XL
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