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DBMS > GridGain vs. HEAVY.AI vs. Microsoft Azure Data Explorer vs. STSdb

System Properties Comparison GridGain vs. HEAVY.AI vs. Microsoft Azure Data Explorer vs. STSdb

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Editorial information provided by DB-Engines
NameGridGain  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSTSdb  Xexclude from comparison
DescriptionGridGain is an in-memory computing platform, built on Apache IgniteA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareFully managed big data interactive analytics platformKey-Value Store with special method for indexing infooptimized for high performance using a special indexing method
Primary database modelKey-value store
Relational DBMS
Relational DBMSRelational DBMS infocolumn orientedKey-value store
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
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score0.04
Rank#360  Overall
#52  Key-value stores
Websitewww.gridgain.comgithub.com/­heavyai/­heavydb
www.heavy.ai
azure.microsoft.com/­services/­data-explorergithub.com/­STSSoft/­STSdb4
Technical documentationwww.gridgain.com/­docs/­index.htmldocs.heavy.aidocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperGridGain Systems, Inc.HEAVY.AI, Inc.MicrosoftSTS Soft SC
Initial release2007201620192011
Current releaseGridGain 8.5.15.10, January 2022cloud service with continuous releases4.0.8, September 2015
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; enterprise edition availablecommercialOpen Source infoGPLv2, commercial license available
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, C++, .NetC++ and CUDAC#
Server operating systemsLinux
OS X
Solaris
Windows
LinuxhostedWindows
Data schemeyesyesFixed schema with schema-less datatypes (dynamic)yes
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-typesyes infoprimitive types and user defined types (classes)
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.yesnoyes
Secondary indexesyesnoall fields are automatically indexedno
SQL infoSupport of SQLANSI-99 for query and DML statements, subset of DDLyesKusto Query Language (KQL), SQL subsetno
APIs and other access methodsHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JDBC
ODBC
Thrift
Vega
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
.NET Client API
Supported programming languagesC#
C++
Java
PHP
Python
Ruby
Scala
All languages supporting JDBC/ODBC/Thrift
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C#
Java
Server-side scripts infoStored proceduresyes (compute grid and cache interceptors can be used instead)noYes, possible languages: KQL, Python, Rno
Triggersyes (cache interceptors and events)noyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoRound robinSharding infoImplicit feature of the cloud servicenone
Replication methods infoMethods for redundantly storing data on multiple nodesyes (replicated cache)Multi-source replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes (compute grid and hadoop accelerator)noSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesno
User concepts infoAccess controlSecurity Hooks for custom implementationsfine grained access rights according to SQL-standardAzure Active Directory Authenticationno

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More resources
GridGainHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Microsoft Azure Data ExplorerSTSdb
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