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DBMS > Atos Standard Common Repository vs. HEAVY.AI vs. IRONdb vs. Microsoft Azure Data Explorer

System Properties Comparison Atos Standard Common Repository vs. HEAVY.AI vs. IRONdb vs. Microsoft Azure Data Explorer

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Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonIRONdb  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityFully managed big data interactive analytics platform
Primary database modelDocument store
Key-value store
Relational DBMSTime Series DBMSRelational DBMS infocolumn oriented
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
Score1.41
Rank#153  Overall
#71  Relational DBMS
Score3.28
Rank#83  Overall
#45  Relational DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorygithub.com/­heavyai/­heavydb
www.heavy.ai
www.circonus.com/solutions/time-series-database/azure.microsoft.com/­services/­data-explorer
Technical documentationdocs.heavy.aidocs.circonus.com/irondb/category/getting-starteddocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperAtos Convergence CreatorsHEAVY.AI, Inc.Circonus LLC.Microsoft
Initial release2016201620172019
Current release17035.10, January 2022V0.10.20, January 2018cloud service with continuous releases
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; enterprise edition availablecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++ and CUDAC and C++
Server operating systemsLinuxLinuxLinuxhosted
Data schemeSchema and schema-less with LDAP viewsyesschema-freeFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateoptionalyesyes infotext, numeric, histogramsyes 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.yesnonoyes
Secondary indexesyesnonoall fields are automatically indexed
SQL infoSupport of SQLnoyesSQL-like query language (Circonus Analytics Query Language: CAQL)Kusto Query Language (KQL), SQL subset
APIs and other access methodsLDAPJDBC
ODBC
Thrift
Vega
HTTP APIMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesAll languages with LDAP bindingsAll languages supporting JDBC/ODBC/Thrift
Python
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresnonoyes, in LuaYes, possible languages: KQL, Python, R
Triggersyesnonoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionSharding infoRound robinAutomatic, metric affinity per nodeSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replicationconfigurable replication factor, datacenter awareyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate consistency per node, eventual consistency across nodesEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsnonono
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.yesyesnono
User concepts infoAccess controlLDAP bind authenticationfine grained access rights according to SQL-standardnoAzure Active Directory Authentication

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More resources
Atos Standard Common RepositoryHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022IRONdbMicrosoft Azure Data Explorer
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