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DBMS > HEAVY.AI vs. Microsoft Azure Data Explorer vs. PostgreSQL vs. TimesTen vs. TinkerGraph

System Properties Comparison HEAVY.AI vs. Microsoft Azure Data Explorer vs. PostgreSQL vs. TimesTen vs. TinkerGraph

Editorial information provided by DB-Engines
NameHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonPostgreSQL  Xexclude from comparisonTimesTen  Xexclude from comparisonTinkerGraph  Xexclude from comparison
DescriptionA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareFully managed big data interactive analytics platformWidely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQLIn-Memory RDBMS compatible to OracleA lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API
Primary database modelRelational 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 DBMSGraph DBMS
Secondary database modelsSpatial 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
Score2.10
Rank#126  Overall
#61  Relational DBMS
Score5.16
Rank#69  Overall
#37  Relational DBMS
Score645.05
Rank#4  Overall
#4  Relational DBMS
Score1.35
Rank#165  Overall
#75  Relational DBMS
Score0.12
Rank#344  Overall
#34  Graph DBMS
Websitegithub.com/­heavyai/­heavydb
www.heavy.ai
azure.microsoft.com/­services/­data-explorerwww.postgresql.orgwww.oracle.com/­database/­technologies/­related/­timesten.htmltinkerpop.apache.org/­docs/­current/­reference/­#tinkergraph-gremlin
Technical documentationdocs.heavy.aidocs.microsoft.com/­en-us/­azure/­data-explorerwww.postgresql.org/­docsdocs.oracle.com/­database/­timesten-18.1
DeveloperHEAVY.AI, Inc.MicrosoftPostgreSQL Global Development Group infowww.postgresql.org/­developerOracle, TimesTen Performance Software, HP infooriginally founded in HP Labs it was acquired by Oracle in 2005
Initial release201620191989 info1989: Postgres, 1996: PostgreSQL19982009
Current release5.10, January 2022cloud service with continuous releases16.2, February 202411 Release 2 (11.2.2.8.0)
License infoCommercial or Open SourceOpen Source infoApache Version 2; enterprise edition availablecommercialOpen Source infoBSDcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Aiven for PostgreSQL: Fully managed PostgreSQL for developers with 70+ extensions and flexible orchestration tools.
Implementation languageC++ and CUDACJava
Server operating systemsLinuxhostedFreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
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 infospecific XML-type available, but no XML query functionality.nono
Secondary indexesnoall fields are automatically indexedyesyesno
SQL infoSupport of SQLyesKusto Query Language (KQL), SQL subsetyes infostandard with numerous extensionsyesno
APIs and other access methodsJDBC
ODBC
Thrift
Vega
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
TinkerPop 3
Supported programming languagesAll languages supporting JDBC/ODBC/Thrift
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C
C++
Java
PL/SQL
Groovy
Java
Server-side scripts infoStored proceduresnoYes, possible languages: KQL, Python, Ruser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.PL/SQLno
Triggersnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyesnono
Partitioning methods infoMethods for storing different data on different nodesSharding infoRound robinSharding infoImplicit feature of the cloud servicepartitioning by range, list and (since PostgreSQL 11) by hashnonenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source 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 extensionsMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparknonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationnone
Foreign keys infoReferential integritynonoyesyesyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesno
Durability infoSupport for making data persistentyesyesyesyes infoby means of logfiles and checkpointsoptional
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonoyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAzure Active Directory Authenticationfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardno

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More resources
HEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Microsoft Azure Data ExplorerPostgreSQLTimesTenTinkerGraph
DB-Engines blog posts

PostgreSQL is the DBMS of the Year 2023
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3 January 2023, Matthias Gelbmann, Paul Andlinger

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Conferences, events and webinars

Monitoring PostgreSQL with Redgate Monitor
Webinar, 10-11am CT / 4-5pm BST, 22 May 2024

Recent citations in the news

Big Data Analytics: A Game Changer for Infrastructure
13 July 2023, Spiceworks News and Insights

HEAVY.AI Launches HEAVY 7.0, Introducing Real-Time Machine Learning Capabilities
19 April 2023, Business Wire

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14 April 2023, InfoWorld

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9 February 2024, InfoWorld

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Automated testing of Amazon Neptune data access with Apache TinkerPop Gremlin | Amazon Web Services
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Simple Deployment of a Graph Database: JanusGraph | by Edward Elson Kosasih
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