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DBMS > Hazelcast vs. Heroic vs. Microsoft Azure Cosmos DB vs. Microsoft Azure Data Explorer vs. PostgreSQL

System Properties Comparison Hazelcast vs. Heroic vs. Microsoft Azure Cosmos DB vs. Microsoft Azure Data Explorer vs. PostgreSQL

Editorial information provided by DB-Engines
NameHazelcast  Xexclude from comparisonHeroic  Xexclude from comparisonMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonPostgreSQL  Xexclude from comparison
DescriptionA widely adopted in-memory data gridTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchGlobally distributed, horizontally scalable, multi-model database serviceFully managed big data interactive analytics platformWidely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL
Primary database modelKey-value storeTime Series DBMSDocument store
Graph DBMS
Key-value store
Wide column store
Relational DBMS infocolumn orientedRelational DBMS infowith object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.
Secondary database modelsDocument store infoJSON support with IMDG 3.12Spatial DBMSDocument 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
Score5.97
Rank#57  Overall
#6  Key-value stores
Score0.51
Rank#255  Overall
#21  Time Series DBMS
Score29.04
Rank#27  Overall
#4  Document stores
#2  Graph DBMS
#3  Key-value stores
#3  Wide column stores
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score645.54
Rank#4  Overall
#4  Relational DBMS
Websitehazelcast.comgithub.com/­spotify/­heroicazure.microsoft.com/­services/­cosmos-dbazure.microsoft.com/­services/­data-explorerwww.postgresql.org
Technical documentationhazelcast.org/­imdg/­docsspotify.github.io/­heroiclearn.microsoft.com/­azure/­cosmos-dbdocs.microsoft.com/­en-us/­azure/­data-explorerwww.postgresql.org/­docs
DeveloperHazelcastSpotifyMicrosoftMicrosoftPostgreSQL Global Development Group infowww.postgresql.org/­developer
Initial release20082014201420191989 info1989: Postgres, 1996: PostgreSQL
Current release5.3.6, November 2023cloud service with continuous releases16.3, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availableOpen Source infoApache 2.0commercialcommercialOpen Source infoBSD
Cloud-based only infoOnly available as a cloud servicenonoyesyesno
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Implementation languageJavaJavaC
Server operating systemsAll OS with a Java VMhostedhostedFreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
Data schemeschema-freeschema-freeschema-freeFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or dateyesyesyes infoJSON typesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyes
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 strategynoyesyes infospecific XML-type available, but no XML query functionality.
Secondary indexesyesyes infovia Elasticsearchyes infoAll properties auto-indexed by defaultall fields are automatically indexedyes
SQL infoSupport of SQLSQL-like query languagenoSQL-like query languageKusto Query Language (KQL), SQL subsetyes infostandard with numerous extensions
APIs and other access methodsJCache
JPA
Memcached protocol
RESTful HTTP API
HQL (Heroic Query Language, a JSON-based language)
HTTP API
DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
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
.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresyes infoEvent Listeners, Executor ServicesnoJavaScriptYes, possible languages: KQL, Python, Ruser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.
Triggersyes infoEventsnoJavaScriptyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud serviceSharding infoImplicit feature of the cloud servicepartitioning by range, list and (since PostgreSQL 11) by hash
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoReplicated Mapyesyes infoImplicit feature of the cloud serviceyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replication infoother methods possible by using 3rd party extensions
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnowith Hadoop integration infoIntegration with Hadoop/HDInsight on Azure*Spark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmEventual Consistency
Immediate Consistency
Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency infoConsistency level configurable on request level
Session Consistency
Eventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataone or two-phase-commit; repeatable reads; read commitednoMulti-item ACID transactions with snapshot isolation within a partitionnoACID
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.yesnonono
User concepts infoAccess controlRole-based access controlAccess rights can be defined down to the item levelAzure Active Directory Authenticationfine grained access rights according to SQL-standard

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