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DBMS > Atos Standard Common Repository vs. Faircom DB vs. GeoMesa vs. InterSystems IRIS vs. Microsoft Azure Data Explorer

System Properties Comparison Atos Standard Common Repository vs. Faircom DB vs. GeoMesa vs. InterSystems IRIS vs. Microsoft Azure Data Explorer

Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonGeoMesa  Xexclude from comparisonInterSystems IRIS  Xexclude from comparisonMicrosoft Azure Data Explorer  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 networksNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.A containerised multi-model DBMS, interoperability and analytics data platform with wide capabilities for vertical and horizontal scalabilityFully managed big data interactive analytics platform
Primary database modelDocument store
Key-value store
Key-value store
Relational DBMS
Spatial DBMSDocument store
Key-value store
Object oriented DBMS
Relational DBMS
Relational DBMS infocolumn oriented
Secondary database modelsDocument 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
Score0.20
Rank#318  Overall
#48  Key-value stores
#141  Relational DBMS
Score0.78
Rank#213  Overall
#4  Spatial DBMS
Score4.05
Rank#83  Overall
#14  Document stores
#10  Key-value stores
#1  Object oriented DBMS
#45  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.faircom.com/­products/­faircom-dbwww.geomesa.orgwww.intersystems.com/­products/­intersystems-irisazure.microsoft.com/­services/­data-explorer
Technical documentationdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmlwww.geomesa.org/­documentation/­stable/­user/­index.htmldocs.intersystems.com/­irislatest/­csp/­docbook/­DocBook.UI.Page.clsdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperAtos Convergence CreatorsFairCom CorporationCCRi and othersInterSystemsMicrosoft
Initial release20161979201420182019
Current release1703V12, November 20204.0.5, February 20242023.3, June 2023cloud service with continuous releases
License infoCommercial or Open Sourcecommercialcommercial infoRestricted, free version availableOpen Source infoApache License 2.0commercialcommercial
Cloud-based only infoOnly available as a cloud servicenonononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaANSI C, C++Scala
Server operating systemsLinuxAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
AIX
Linux
macOS
Ubuntu
Windows
hosted
Data schemeSchema and schema-less with LDAP viewsschema free, schema optional, schema required, partial schema,yesdepending on used data modelFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateoptionalyes, ANSI SQL Types, JSON, typed binary structuresyesyesyes 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.yesnonoyesyes
Secondary indexesyesyesyesyesall fields are automatically indexed
SQL infoSupport of SQLnoyes, ANSI SQL with proprietary extensionsnoyesKusto Query Language (KQL), SQL subset
APIs and other access methodsLDAPADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
JDBC
ODBC
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesAll languages with LDAP bindings.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
.Net
C++
Java
JavaScript (Node.js)
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresnoyes info.Net, JavaScript, C/C++noyesYes, possible languages: KQL, Python, R
Triggersyesyesnoyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningdepending on storage layerShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).depending on storage layerSource-replica replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnoSpark 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 configurationEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
depending on storage layerImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationstunable from ACID to Eventually ConsistentnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesYes, tunable from durable to delayed durability to in-memoryyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesdepending on storage layeryesno
User concepts infoAccess controlLDAP bind authenticationFine grained access rights according to SQL-standard with additional protections for filesyes infodepending on the DBMS used for storageyesAzure Active Directory Authentication
More information provided by the system vendor
Atos Standard Common RepositoryFaircom DB infoformerly c-treeACEGeoMesaInterSystems IRISMicrosoft Azure Data Explorer
Specific characteristicsInterSystems IRIS is a complete cloud-first data platform which includes a multi-model...
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More resources
Atos Standard Common RepositoryFaircom DB infoformerly c-treeACEGeoMesaInterSystems IRISMicrosoft Azure Data Explorer
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