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

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

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 comparisonKinetica  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonOrientDB  Xexclude from comparison
This system has been discontinued and will be removed 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 hardwareFully vectorized database across both GPUs and CPUsFully managed big data interactive analytics platformMulti-model DBMS (Document, Graph, Key/Value)
Primary database modelDocument store
Key-value store
Relational DBMSRelational DBMSRelational DBMS infocolumn orientedDocument store
Graph DBMS
Key-value store
Secondary database modelsSpatial DBMSSpatial DBMS
Time Series DBMS
Document 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
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score3.19
Rank#93  Overall
#16  Document stores
#7  Graph DBMS
#14  Key-value stores
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorygithub.com/­heavyai/­heavydb
www.heavy.ai
www.kinetica.comazure.microsoft.com/­services/­data-explorerorientdb.org
Technical documentationdocs.heavy.aidocs.kinetica.comdocs.microsoft.com/­en-us/­azure/­data-explorerwww.orientdb.com/­docs/­last/­index.html
DeveloperAtos Convergence CreatorsHEAVY.AI, Inc.KineticaMicrosoftOrientDB LTD; CallidusCloud; SAP
Initial release20162016201220192010
Current release17035.10, January 20227.1, August 2021cloud service with continuous releases3.2.29, March 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; enterprise edition availablecommercialcommercialOpen Source infoApache version 2
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.
Implementation languageJavaC++ and CUDAC, C++Java
Server operating systemsLinuxLinuxLinuxhostedAll OS with a Java JDK (>= JDK 6)
Data schemeSchema and schema-less with LDAP viewsyesyesFixed schema with schema-less datatypes (dynamic)schema-free infoSchema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")
Typing infopredefined data types such as float or dateoptionalyesyesyes 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.yesnonoyesno
Secondary indexesyesnoyesall fields are automatically indexedyes
SQL infoSupport of SQLnoyesSQL-like DML and DDL statementsKusto Query Language (KQL), SQL subsetSQL-like query language, no joins
APIs and other access methodsLDAPJDBC
ODBC
Thrift
Vega
JDBC
ODBC
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API
Supported programming languagesAll languages with LDAP bindingsAll languages supporting JDBC/ODBC/Thrift
Python
C++
Java
JavaScript (Node.js)
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresnonouser defined functionsYes, possible languages: KQL, Python, RJava, Javascript
Triggersyesnoyes infotriggers when inserted values for one or more columns fall within a specified rangeyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyHooks
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionSharding infoRound robinShardingSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replicationSource-replica replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno infocould be achieved with distributed queries
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonoyesnoyes inforelationship in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsnononoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.yesyesyes infoGPU vRAM or System RAMno
User concepts infoAccess controlLDAP bind authenticationfine grained access rights according to SQL-standardAccess rights for users and roles on table levelAzure Active Directory AuthenticationAccess rights for users and roles; record level security configurable

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