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DBMS > Alibaba Cloud AnalyticDB for MySQL vs. eXtremeDB vs. HEAVY.AI vs. Heroic vs. Microsoft Azure Data Explorer

System Properties Comparison Alibaba Cloud AnalyticDB for MySQL vs. eXtremeDB vs. HEAVY.AI vs. Heroic vs. Microsoft Azure Data Explorer

Editorial information provided by DB-Engines
NameAlibaba Cloud AnalyticDB for MySQL  Xexclude from comparisoneXtremeDB  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonHeroic  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
DescriptionA real-time data warehousing service that can process petabytes of data with high concurrency and low latency. It is fully compatible with the MySQL protocol.Natively in-memory DBMS with options for persistency, high-availability and clusteringA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchFully managed big data interactive analytics platform
Primary database modelRelational DBMSRelational DBMS
Time Series DBMS
Relational DBMSTime Series DBMSRelational DBMS infocolumn oriented
Secondary database modelsDocument storeSpatial 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
Score0.85
Rank#207  Overall
#96  Relational DBMS
Score0.74
Rank#223  Overall
#103  Relational DBMS
#18  Time Series DBMS
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score0.51
Rank#255  Overall
#21  Time Series DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Websitewww.alibabacloud.com/­product/­analyticdb-for-mysqlwww.mcobject.comgithub.com/­heavyai/­heavydb
www.heavy.ai
github.com/­spotify/­heroicazure.microsoft.com/­services/­data-explorer
Technical documentationwww.alibabacloud.com/­help/­doc-detail/­93776.htmwww.mcobject.com/­docs/­extremedb.htmdocs.heavy.aispotify.github.io/­heroicdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperAlibabaMcObjectHEAVY.AI, Inc.SpotifyMicrosoft
Initial release2001201620142019
Current release8.2, 20215.10, January 2022cloud service with continuous releases
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2; enterprise edition availableOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud serviceyesnononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC and C++C++ and CUDAJava
Server operating systemshostedAIX
HP-UX
Linux
macOS
Solaris
Windows
Linuxhosted
Data schemeyesyesyesschema-freeFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyesyesyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types
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.yesno infosupport of XML interfaces availablenonoyes
Secondary indexesyesyesnoyes infovia Elasticsearchall fields are automatically indexed
SQL infoSupport of SQLyesyes infowith the option: eXtremeSQLyesnoKusto Query Language (KQL), SQL subset
APIs and other access methodsJDBC
ODBC
.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API
JDBC
ODBC
Thrift
Vega
HQL (Heroic Query Language, a JSON-based language)
HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesC#
Java
PHP
Python
.Net
C
C#
C++
Java
Lua
Python
Scala
All languages supporting JDBC/ODBC/Thrift
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresyesyesnonoYes, possible languages: KQL, Python, R
Triggersyesyes infoby defining eventsnonoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud servicehorizontal partitioning / shardingSharding infoRound robinShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud serviceActive Replication Fabricâ„¢ for IoT
Multi-source replication infoby means of eXtremeDB Cluster option
Source-replica replication infoby means of eXtremeDB High Availability option
Multi-source replicationyesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonononoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnonono
Concurrency infoSupport for concurrent manipulation of datayesyes infoOptimistic (MVCC) and pessimistic (locking) strategies availableyesyesyes
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.yesyesyesnono
User concepts infoAccess controlfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardAzure Active Directory Authentication
More information provided by the system vendor
Alibaba Cloud AnalyticDB for MySQLeXtremeDBHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022HeroicMicrosoft Azure Data Explorer
Specific characteristicsA real-time data warehousing service that can process PB data with high concurrency...
» more
eXtremeDB is an in-memory and/or persistent database system that offers an ultra-small...
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Competitive advantagesTPC Benchmark: The world leading result in TPC-DS benchmark . TPC-H benchmark for...
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eXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
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Typical application scenariosIoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
» more
Key customersSchneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
» more
Market metricsWith hundreds of customers and over 30 million devices/applications using the product...
» more
Licensing and pricing modelsAvailable regions: America US Virginia US Silicon Valley Asia China Hong Kong India...
» more
For server use cases, there is a simple per-server license irrespective of the number...
» more

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More resources
Alibaba Cloud AnalyticDB for MySQLeXtremeDBHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022HeroicMicrosoft Azure Data Explorer
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