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DBMS > Atos Standard Common Repository vs. IBM Cloudant vs. Microsoft Access vs. Microsoft Azure Data Explorer vs. Milvus

System Properties Comparison Atos Standard Common Repository vs. IBM Cloudant vs. Microsoft Access vs. Microsoft Azure Data Explorer vs. Milvus

Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonIBM Cloudant  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonMilvus  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 networksDatabase as a Service offering based on Apache CouchDBMicrosoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries. infoThe Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)Fully managed big data interactive analytics platformA DBMS designed for efficient storage of vector data and vector similarity searches
Primary database modelDocument store
Key-value store
Document storeRelational DBMSRelational DBMS infocolumn orientedVector DBMS
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
Score2.68
Rank#106  Overall
#20  Document stores
Score104.92
Rank#11  Overall
#8  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score2.31
Rank#113  Overall
#3  Vector DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.ibm.com/­products/­cloudantwww.microsoft.com/­en-us/­microsoft-365/­accessazure.microsoft.com/­services/­data-explorermilvus.io
Technical documentationcloud.ibm.com/­docs/­Cloudantdeveloper.microsoft.com/­en-us/­accessdocs.microsoft.com/­en-us/­azure/­data-explorermilvus.io/­docs/­overview.md
DeveloperAtos Convergence CreatorsIBM, Apache Software Foundation infoIBM acquired Cloudant in February 2014MicrosoftMicrosoft
Initial release20162010199220192019
Current release17031902 (16.0.11328.20222), March 2019cloud service with continuous releases2.3.4, January 2024
License infoCommercial or Open Sourcecommercialcommercialcommercial infoBundled with Microsoft OfficecommercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Zilliz Cloud – Cloud-native service for Milvus
Implementation languageJavaErlangC++C++, Go
Server operating systemsLinuxhostedWindows infoNot a real database server, but making use of DLLshostedLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
Data schemeSchema and schema-less with LDAP viewsschema-freeyesFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateoptionalnoyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesVector, Numeric and String
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.yesnoyesno
Secondary indexesyesyesyesall fields are automatically indexedno
SQL infoSupport of SQLnonoyes infobut not compliant to any SQL standardKusto Query Language (KQL), SQL subsetno
APIs and other access methodsLDAPRESTful HTTP/JSON APIADO.NET
DAO
ODBC
OLE DB
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
RESTful HTTP API
Supported programming languagesAll languages with LDAP bindingsC#
Java
JavaScript
Objective-C
PHP
Ruby
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnoView functions (Map-Reduce) in JavaScriptyes infosince Access 2010 using the ACE-engineYes, possible languages: KQL, Python, Rno
Triggersyesyesyes infosince Access 2010 using the ACE-engineyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionShardingnoneSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication
Source-replica replication
noneyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationEventual ConsistencyEventual Consistency
Immediate Consistency
Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Foreign keys infoReferential integritynonoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsno infoatomic operations within a document possibleACID infobut no files for transaction loggingnono
Concurrency infoSupport for concurrent manipulation of datayesyes infoOptimistic lockingyesyesyes
Durability infoSupport for making data persistentyesyesyes infobut no files for transaction loggingyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonoyes
User concepts infoAccess controlLDAP bind authenticationAccess rights for users can be defined per databaseno infoa simple user-level security was built in till version Access 2003Azure Active Directory AuthenticationRole based access control and fine grained access rights
More information provided by the system vendor
Atos Standard Common RepositoryIBM CloudantMicrosoft AccessMicrosoft Azure Data ExplorerMilvus
Specific characteristicsMilvus is an open-source and cloud-native vector database built for production-ready...
» more
Competitive advantagesHighly available, versatile, and robust with millisecond latency. Supports batch...
» more
Typical application scenariosRAG: retrieval augmented generation Video media : video understanding, video deduplication....
» more
Key customersMilvus is trusted by thousands of enterprises, including PayPal, eBay, IKEA, LINE,...
» more
Market metricsAs of January 2024, 25k+ GitHub stars 10M+ downloads and installations​ ​ 3k+ enterprise...
» more
Licensing and pricing modelsMilvus was released under the open-source Apache License 2.0 in October 2019. Fully-managed...
» more

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More resources
Atos Standard Common RepositoryIBM CloudantMicrosoft AccessMicrosoft Azure Data ExplorerMilvus
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