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DBMS > Hazelcast vs. IBM Db2 Event Store vs. Microsoft Azure Data Explorer vs. Microsoft Azure SQL Database vs. Postgres-XL

System Properties Comparison Hazelcast vs. IBM Db2 Event Store vs. Microsoft Azure Data Explorer vs. Microsoft Azure SQL Database vs. Postgres-XL

Editorial information provided by DB-Engines
NameHazelcast  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparisonPostgres-XL  Xexclude from comparison
DescriptionA widely adopted in-memory data gridDistributed Event Store optimized for Internet of Things use casesFully 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 modelKey-value storeEvent Store
Time Series DBMS
Relational DBMS infocolumn orientedRelational DBMSRelational DBMS
Secondary database modelsDocument 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
Score5.46
Rank#61  Overall
#7  Key-value stores
Score0.27
Rank#309  Overall
#2  Event Stores
#28  Time Series DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score76.78
Rank#16  Overall
#11  Relational DBMS
Score0.53
Rank#254  Overall
#117  Relational DBMS
Websitehazelcast.comwww.ibm.com/­products/­db2-event-storeazure.microsoft.com/­services/­data-explorerazure.microsoft.com/­en-us/­products/­azure-sql/­databasewww.postgres-xl.org
Technical documentationhazelcast.org/­imdg/­docswww.ibm.com/­docs/­en/­db2-event-storedocs.microsoft.com/­en-us/­azure/­data-explorerdocs.microsoft.com/­en-us/­azure/­azure-sqlwww.postgres-xl.org/­documentation
DeveloperHazelcastIBMMicrosoftMicrosoft
Initial release20082017201920102014 infosince 2012, originally named StormDB
Current release5.3.6, November 20232.0cloud service with continuous releasesV1210 R1, October 2018
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availablecommercial infofree developer edition 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 languageJavaC and C++C++C
Server operating systemsAll OS with a Java VMLinux infoLinux, macOS, Windows for the developer additionhostedhostedLinux
macOS
Data schemeschema-freeyesFixed 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.yes infothe object must implement a serialization strategynoyesyesyes infoXML type, but no XML query functionality
Secondary indexesyesnoall fields are automatically indexedyesyes
SQL infoSupport of SQLSQL-like query languageyes infothrough the embedded Spark runtimeKusto Query Language (KQL), SQL subsetyesyes infodistributed, parallel query execution
APIs and other access methodsJCache
JPA
Memcached protocol
RESTful HTTP API
ADO.NET
DB2 Connect
JDBC
ODBC
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 languages.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
.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 proceduresyes infoEvent Listeners, Executor ServicesyesYes, possible languages: KQL, Python, RTransact SQLuser defined functions
Triggersyes infoEventsnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud servicehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoReplicated MapActive-active shard replicationyes 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 methodsyesnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmEventual ConsistencyEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataone or two-phase-commit; repeatable reads; read commitednonoACIDACID infoMVCC
Concurrency infoSupport for concurrent manipulation of datayesNo - written data is immutableyesyesyes
Durability infoSupport for making data persistentyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnono
User concepts infoAccess controlRole-based access controlfine grained access rights according to SQL-standardAzure Active Directory Authenticationfine grained access rights according to SQL-standardfine grained access rights according to SQL-standard

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More resources
HazelcastIBM Db2 Event StoreMicrosoft Azure Data ExplorerMicrosoft Azure SQL Database infoformerly SQL AzurePostgres-XL
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