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DBMS > HEAVY.AI vs. Ignite vs. InfinityDB vs. Microsoft Azure Data Explorer vs. MySQL

System Properties Comparison HEAVY.AI vs. Ignite vs. InfinityDB vs. Microsoft Azure Data Explorer vs. MySQL

Editorial information provided by DB-Engines
NameHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonIgnite  Xexclude from comparisonInfinityDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonMySQL  Xexclude from comparison
DescriptionA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareApache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.A Java embedded Key-Value Store which extends the Java Map interfaceFully managed big data interactive analytics platformWidely used open source RDBMS
Primary database modelRelational DBMSKey-value store
Relational DBMS
Key-value storeRelational DBMS infocolumn orientedRelational DBMS infoKey/Value like access via memcached API
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
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.30
Rank#127  Overall
#60  Relational DBMS
Score4.04
Rank#86  Overall
#12  Key-value stores
#46  Relational DBMS
Score0.09
Rank#357  Overall
#53  Key-value stores
Score5.82
Rank#65  Overall
#37  Relational DBMS
Score1101.50
Rank#2  Overall
#2  Relational DBMS
Websitegithub.com/­heavyai/­heavydb
www.heavy.ai
ignite.apache.orgboilerbay.comazure.microsoft.com/­services/­data-explorerwww.mysql.com
Technical documentationdocs.heavy.aiapacheignite.readme.io/­docsboilerbay.com/­infinitydb/­manualdocs.microsoft.com/­en-us/­azure/­data-explorerdev.mysql.com/­doc
DeveloperHEAVY.AI, Inc.Apache Software FoundationBoiler Bay Inc.MicrosoftOracle infosince 2010, originally MySQL AB, then Sun
Initial release20162015200220191995
Current release5.10, January 2022Apache Ignite 2.64.0cloud service with continuous releases8.3.0, January 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2; enterprise edition availableOpen Source infoApache 2.0commercialcommercialOpen Source infoGPL version 2. Commercial licenses with extended functionallity are available
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
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Implementation languageC++ and CUDAC++, Java, .NetJavaC and C++
Server operating systemsLinuxLinux
OS X
Solaris
Windows
All OS with a Java VMhostedFreeBSD
Linux
OS X
Solaris
Windows
Data schemeyesyesyes infonested virtual Java Maps, multi-value, logical ‘tuple space’ runtime Schema upgradeFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or dateyesyesyes infoall Java primitives, Date, CLOB, BLOB, huge sparse arraysyes 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.noyesnoyesyes
Secondary indexesnoyesno infomanual creation possible, using inversions based on multi-value capabilityall fields are automatically indexedyes
SQL infoSupport of SQLyesANSI-99 for query and DML statements, subset of DDLnoKusto Query Language (KQL), SQL subsetyes infowith proprietary extensions
APIs and other access methodsJDBC
ODBC
Thrift
Vega
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/­docs/­ItemSpaceDataStructures.htm)
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languagesAll languages supporting JDBC/ODBC/Thrift
Python
C#
C++
Java
PHP
Python
Ruby
Scala
Java.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnoyes (compute grid and cache interceptors can be used instead)noYes, possible languages: KQL, Python, Ryes infoproprietary syntax
Triggersnoyes (cache interceptors and events)noyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes
Partitioning methods infoMethods for storing different data on different nodesSharding infoRound robinShardingnoneSharding infoImplicit feature of the cloud servicehorizontal partitioning, sharding with MySQL Cluster or MySQL Fabric
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationyes (replicated cache)noneyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes (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 ConsistencyImmediate Consistency infoREAD-COMMITTED or SERIALIZEDEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynonono infomanual creation possible, using inversions based on multi-value capabilitynoyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID infoOptimistic locking for transactions; no isolation for bulk loadsnoACID infonot for MyISAM storage engine
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes infotable locks or row locks depending on storage engine
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.yesyesnonoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardSecurity Hooks for custom implementationsnoAzure Active Directory AuthenticationUsers with fine-grained authorization concept infono user groups or roles

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More resources
HEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022IgniteInfinityDBMicrosoft Azure Data ExplorerMySQL
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