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

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

Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonMilvus  Xexclude from comparisonXTDB infoformerly named Crux  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 networksMicrosoft 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 searchesA general purpose database with bitemporal SQL and Datalog and graph queries
Primary database modelDocument store
Key-value store
Relational DBMSRelational DBMS infocolumn orientedVector DBMSDocument store
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
Score104.92
Rank#11  Overall
#8  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score2.31
Rank#113  Overall
#3  Vector DBMS
Score0.11
Rank#343  Overall
#46  Document stores
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.microsoft.com/­en-us/­microsoft-365/­accessazure.microsoft.com/­services/­data-explorermilvus.iogithub.com/­xtdb/­xtdb
www.xtdb.com
Technical documentationdeveloper.microsoft.com/­en-us/­accessdocs.microsoft.com/­en-us/­azure/­data-explorermilvus.io/­docs/­overview.mdwww.xtdb.com/­docs
DeveloperAtos Convergence CreatorsMicrosoftMicrosoftJuxt Ltd.
Initial release20161992201920192019
Current release17031902 (16.0.11328.20222), March 2019cloud service with continuous releases2.3.4, January 20241.19, September 2021
License infoCommercial or Open Sourcecommercialcommercial infoBundled with Microsoft OfficecommercialOpen Source infoApache Version 2.0Open Source infoMIT License
Cloud-based only infoOnly available as a cloud servicenonoyesnono
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 languageJavaC++C++, GoClojure
Server operating systemsLinuxWindows infoNot a real database server, but making use of DLLshostedLinux
macOS info10.14 or later
Windows infowith WSL 2 enabled
All OS with a Java 8 (and higher) VM
Linux
Data schemeSchema and schema-less with LDAP viewsyesFixed schema with schema-less datatypes (dynamic)schema-free
Typing infopredefined data types such as float or dateoptionalyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesVector, Numeric and Stringyes, extensible-data-notation format
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.yesyesnono
Secondary indexesyesyesall fields are automatically indexednoyes
SQL infoSupport of SQLnoyes infobut not compliant to any SQL standardKusto Query Language (KQL), SQL subsetnolimited SQL, making use of Apache Calcite
APIs and other access methodsLDAPADO.NET
DAO
ODBC
OLE DB
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
RESTful HTTP APIHTTP REST
JDBC
Supported programming languagesAll languages with LDAP bindingsC
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
Clojure
Java
Server-side scripts infoStored proceduresnoyes infosince Access 2010 using the ACE-engineYes, possible languages: KQL, Python, Rnono
Triggersyesyes infosince Access 2010 using the ACE-engineyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynono
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionnoneSharding infoImplicit feature of the cloud serviceShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesnoneyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes, each node contains all data
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Immediate Consistency
Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Foreign keys infoReferential integritynoyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsACID infobut no files for transaction loggingnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyes infobut no files for transaction loggingyesyesyes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes
User concepts infoAccess controlLDAP bind authenticationno 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 RepositoryMicrosoft AccessMicrosoft Azure Data ExplorerMilvusXTDB infoformerly named Crux
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 RepositoryMicrosoft AccessMicrosoft Azure Data ExplorerMilvusXTDB infoformerly named Crux
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