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DBMS > Atos Standard Common Repository vs. Google Cloud Bigtable vs. Microsoft Access vs. Quasardb vs. Yaacomo

System Properties Comparison Atos Standard Common Repository vs. Google Cloud Bigtable vs. Microsoft Access vs. Quasardb vs. Yaacomo

Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonQuasardb  Xexclude from comparisonYaacomo  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.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.)Distributed, high-performance timeseries databaseOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelDocument store
Key-value store
Key-value store
Wide column store
Relational DBMSTime Series DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score104.92
Rank#11  Overall
#8  Relational DBMS
Score0.14
Rank#332  Overall
#29  Time Series DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorycloud.google.com/­bigtablewww.microsoft.com/­en-us/­microsoft-365/­accessquasar.aiyaacomo.com
Technical documentationcloud.google.com/­bigtable/­docsdeveloper.microsoft.com/­en-us/­accessdoc.quasar.ai/­master
DeveloperAtos Convergence CreatorsGoogleMicrosoftquasardbQ2WEB GmbH
Initial release20162015199220092009
Current release17031902 (16.0.11328.20222), March 20193.14.1, January 2024
License infoCommercial or Open Sourcecommercialcommercialcommercial infoBundled with Microsoft Officecommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensescommercial
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++C++
Server operating systemsLinuxhostedWindows infoNot a real database server, but making use of DLLsBSD
Linux
OS X
Windows
Android
Linux
Windows
Data schemeSchema and schema-less with LDAP viewsschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateoptionalnoyesyes infointeger and binaryyes
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.yesnonono
Secondary indexesyesnoyesyes infowith tagsyes
SQL infoSupport of SQLnonoyes infobut not compliant to any SQL standardSQL-like query languageyes
APIs and other access methodsLDAPgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
ADO.NET
DAO
ODBC
OLE DB
HTTP APIJDBC
ODBC
Supported programming languagesAll languages with LDAP bindingsC#
C++
Go
Java
JavaScript (Node.js)
Python
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Server-side scripts infoStored proceduresnonoyes infosince Access 2010 using the ACE-engineno
Triggersyesnoyes infosince Access 2010 using the ACE-enginenoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionShardingnoneSharding infoconsistent hashinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesInternal replication in Colossus, and regional replication between two clusters in different zonesnoneSource-replica replication with selectable replication factorSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnowith Hadoop integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsAtomic single-row operationsACID infobut no files for transaction loggingACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes infobut no files for transaction loggingyes infoby using LevelDByes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes infoTransient modeyes
User concepts infoAccess controlLDAP bind authenticationAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)no infoa simple user-level security was built in till version Access 2003Cryptographically strong user authentication and audit trailfine grained access rights according to SQL-standard

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More resources
Atos Standard Common RepositoryGoogle Cloud BigtableMicrosoft AccessQuasardbYaacomo
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