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DBMS > AlaSQL vs. Atos Standard Common Repository vs. Databricks vs. Microsoft Access vs. Microsoft Azure AI Search

System Properties Comparison AlaSQL vs. Atos Standard Common Repository vs. Databricks vs. Microsoft Access vs. Microsoft Azure AI Search

Editorial information provided by DB-Engines
NameAlaSQL  Xexclude from comparisonAtos Standard Common Repository  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.
DescriptionJavaScript DBMS libraryHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksThe 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
Relational DBMS
Document store
Key-value store
Document store
Relational DBMS
Relational DBMSSearch engine
Secondary database modelsVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.51
Rank#256  Overall
#40  Document stores
#118  Relational DBMS
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score101.16
Rank#11  Overall
#8  Relational DBMS
Score5.52
Rank#59  Overall
#6  Search engines
Websitealasql.orgatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.databricks.comwww.microsoft.com/­en-us/­microsoft-365/­accessazure.microsoft.com/­en-us/­services/­search
Technical documentationgithub.com/­AlaSQL/­alasqldocs.databricks.comdeveloper.microsoft.com/­en-us/­accesslearn.microsoft.com/­en-us/­azure/­search
DeveloperAndrey Gershun & Mathias R. WulffAtos Convergence CreatorsDatabricksMicrosoftMicrosoft
Initial release20142016201319922015
Current release17031902 (16.0.11328.20222), March 2019V1
License infoCommercial or Open SourceOpen Source infoMIT-Licensecommercialcommercialcommercial infoBundled with Microsoft Officecommercial
Cloud-based only infoOnly available as a cloud servicenonoyesnoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaScriptJavaC++
Server operating systemsserver-less, requires a JavaScript environment (browser, Node.js)LinuxhostedWindows infoNot a real database server, but making use of DLLshosted
Data schemeschema-freeSchema and schema-less with LDAP viewsFlexible Schema (defined schema, partial schema, schema free)yesyes
Typing infopredefined data types such as float or datenooptionalyesyes
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.noyesyesno
Secondary indexesnoyesyesyesyes
SQL infoSupport of SQLClose to SQL99, but no user access control, stored procedures and host language bindings.nowith Databricks SQLyes infobut not compliant to any SQL standardno
APIs and other access methodsJavaScript APILDAPJDBC
ODBC
RESTful HTTP API
ADO.NET
DAO
ODBC
OLE DB
RESTful HTTP API
Supported programming languagesJavaScriptAll languages with LDAP bindingsPython
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
Triggersyesyesyes infosince Access 2010 using the ACE-engineno
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infocell divisionnoneSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyesyesnoneyes 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 systemnoneImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayes infoonly for local storage and DOM-storageAtomic execution of specific operationsACIDACID infobut no files for transaction loggingno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infoby using IndexedDB, SQL.JS or proprietary FileStorageyesyesyes 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.yesyesnono
User concepts infoAccess controlnoLDAP bind authenticationno infoa simple user-level security was built in till version Access 2003yes infousing Azure authentication
More information provided by the system vendor
AlaSQLAtos Standard Common RepositoryDatabricksMicrosoft AccessMicrosoft Azure AI Search
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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AlaSQLAtos Standard Common RepositoryDatabricksMicrosoft AccessMicrosoft Azure AI Search
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