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DBMS > Atos Standard Common Repository vs. Cloudflare Workers KV vs. Databricks vs. Microsoft Access vs. Microsoft Azure AI Search

System Properties Comparison Atos Standard Common Repository vs. Cloudflare Workers KV vs. Databricks vs. Microsoft Access vs. Microsoft Azure AI Search

Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonCloudflare Workers KV  Xexclude from comparisonDatabricks  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonMicrosoft Azure AI Search  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 global, low-latency, key-value store for applications on Cloudflare with exceptionally high read volumes and low-latency.The Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.Microsoft 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.)Search-as-a-service for web and mobile app development
Primary database modelDocument store
Key-value store
Key-value storeDocument store
Relational DBMS
Relational DBMSSearch engine
Secondary database modelsVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.32
Rank#283  Overall
#40  Key-value stores
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score104.92
Rank#11  Overall
#8  Relational DBMS
Score5.59
Rank#63  Overall
#7  Search engines
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.cloudflare.com/­developer-platform/­workers-kvwww.databricks.comwww.microsoft.com/­en-us/­microsoft-365/­accessazure.microsoft.com/­en-us/­services/­search
Technical documentationdevelopers.cloudflare.com/­kv/­apidocs.databricks.comdeveloper.microsoft.com/­en-us/­accesslearn.microsoft.com/­en-us/­azure/­search
DeveloperAtos Convergence CreatorsCloudflareDatabricksMicrosoftMicrosoft
Initial release20162018201319922015
Current release17031902 (16.0.11328.20222), March 2019V1
License infoCommercial or Open Sourcecommercialcommercialcommercialcommercial infoBundled with Microsoft Officecommercial
Cloud-based only infoOnly available as a cloud servicenoyesyesnoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++
Server operating systemsLinuxhostedhostedWindows infoNot a real database server, but making use of DLLshosted
Data schemeSchema and schema-less with LDAP viewsschema-freeFlexible Schema (defined schema, partial schema, schema free)yesyes
Typing infopredefined data types such as float or dateoptionalnoyesyes
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 indexesyesnoyesyesyes
SQL infoSupport of SQLnonowith Databricks SQLyes infobut not compliant to any SQL standardno
APIs and other access methodsLDAPHTTP REST
Proprietary protocol
JDBC
ODBC
RESTful HTTP API
ADO.NET
DAO
ODBC
OLE DB
RESTful HTTP API
Supported programming languagesAll languages with LDAP bindingsC
C++
Dart
JavaScript
Kotlin
Python
Rust
Scala
Python
R
Scala
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
C#
Java
JavaScript
Python
Server-side scripts infoStored proceduresnonouser defined functions and aggregatesyes infosince Access 2010 using the ACE-engineno
Triggersyesnoyes infosince Access 2010 using the ACE-engineno
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionnoneSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesyesnoneyes infoImplicit feature of the cloud service
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsnoACIDACID infobut no files for transaction loggingno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infobut no files for transaction loggingyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonono
User concepts infoAccess controlLDAP bind authenticationno infoa simple user-level security was built in till version Access 2003yes infousing Azure authentication
More information provided by the system vendor
Atos Standard Common RepositoryCloudflare Workers KVDatabricksMicrosoft AccessMicrosoft Azure AI Search
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
Atos Standard Common RepositoryCloudflare Workers KVDatabricksMicrosoft AccessMicrosoft Azure AI Search
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