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DBMS > Hazelcast vs. Linter vs. Microsoft Azure Data Explorer vs. PostgreSQL vs. Teradata Aster

System Properties Comparison Hazelcast vs. Linter vs. Microsoft Azure Data Explorer vs. PostgreSQL vs. Teradata Aster

Editorial information provided by DB-Engines
NameHazelcast  Xexclude from comparisonLinter  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonPostgreSQL  Xexclude from comparisonTeradata Aster  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionA widely adopted in-memory data gridRDBMS for high security requirementsFully managed big data interactive analytics platformWidely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQLPlatform for big data analytics on multistructured data sources and types
Primary database modelKey-value storeRelational 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 DBMS
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
Score0.09
Rank#346  Overall
#152  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score645.54
Rank#4  Overall
#4  Relational DBMS
Websitehazelcast.comlinter.ruazure.microsoft.com/­services/­data-explorerwww.postgresql.org
Technical documentationhazelcast.org/­imdg/­docsdocs.microsoft.com/­en-us/­azure/­data-explorerwww.postgresql.org/­docs
DeveloperHazelcastrelex.ruMicrosoftPostgreSQL Global Development Group infowww.postgresql.org/­developerTeradata
Initial release2008199020191989 info1989: Postgres, 1996: PostgreSQL2005
Current release5.3.6, November 2023cloud service with continuous releases16.3, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availablecommercialcommercialOpen Source infoBSDcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC and C++C
Server operating systemsAll OS with a Java VMAIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
hostedFreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
Linux
Data schemeschema-freeyesFixed schema with schema-less datatypes (dynamic)yesFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
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 strategynoyesyes infospecific XML-type available, but no XML query functionality.yes infoin Aster File Store
Secondary indexesyesyesall fields are automatically indexedyesyes
SQL infoSupport of SQLSQL-like query languageyesKusto Query Language (KQL), SQL subsetyes infostandard with numerous extensionsyes
APIs and other access methodsJCache
JPA
Memcached protocol
RESTful HTTP API
ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
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
ODBC
OLE DB
Supported programming languages.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresyes infoEvent Listeners, Executor Servicesyes infoproprietary syntax with the possibility to convert from PL/SQLYes, possible languages: KQL, Python, Ruser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.R packages
Triggersyes infoEventsyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyesno
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding infoImplicit feature of the cloud servicepartitioning by range, list and (since PostgreSQL 11) by hashSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoReplicated MapSource-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 extensionsyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparknoyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyesnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataone or two-phase-commit; repeatable reads; read commitedACIDnoACIDACID
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 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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HazelcastLinterMicrosoft Azure Data ExplorerPostgreSQLTeradata Aster
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