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DBMS > Atos Standard Common Repository vs. Google Cloud Bigtable vs. IBM Db2 Event Store vs. Microsoft Access vs. SQream DB

System Properties Comparison Atos Standard Common Repository vs. Google Cloud Bigtable vs. IBM Db2 Event Store vs. Microsoft Access vs. SQream DB

Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonSQream DB  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 networksGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Distributed Event Store optimized for Internet of Things use casesMicrosoft 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.)a GPU-based, columnar RDBMS for big data analytics workloads
Primary database modelDocument store
Key-value store
Key-value store
Wide column store
Event Store
Time Series DBMS
Relational 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
Score0.19
Rank#323  Overall
#2  Event Stores
#28  Time Series DBMS
Score104.92
Rank#11  Overall
#8  Relational DBMS
Score0.70
Rank#227  Overall
#104  Relational DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorycloud.google.com/­bigtablewww.ibm.com/­products/­db2-event-storewww.microsoft.com/­en-us/­microsoft-365/­accesssqream.com
Technical documentationcloud.google.com/­bigtable/­docswww.ibm.com/­docs/­en/­db2-event-storedeveloper.microsoft.com/­en-us/­accessdocs.sqream.com
DeveloperAtos Convergence CreatorsGoogleIBMMicrosoftSQream Technologies
Initial release20162015201719922017
Current release17032.01902 (16.0.11328.20222), March 20192022.1.6, December 2022
License infoCommercial or Open Sourcecommercialcommercialcommercial infofree developer edition availablecommercial infoBundled with Microsoft Officecommercial
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 and C++C++C++, CUDA, Haskell, Java, Scala
Server operating systemsLinuxhostedLinux infoLinux, macOS, Windows for the developer additionWindows infoNot a real database server, but making use of DLLsLinux
Data schemeSchema and schema-less with LDAP viewsschema-freeyesyesyes
Typing infopredefined data types such as float or dateoptionalnoyesyesyes, ANSI Standard SQL Types
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.yesnono
Secondary indexesyesnonoyesno
SQL infoSupport of SQLnonoyes infothrough the embedded Spark runtimeyes infobut not compliant to any SQL standardyes
APIs and other access methodsLDAPgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
ADO.NET
DAO
ODBC
OLE DB
.Net
JDBC
ODBC
Supported programming languagesAll languages with LDAP bindingsC#
C++
Go
Java
JavaScript (Node.js)
Python
C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnonoyesyes infosince Access 2010 using the ACE-engineuser defined functions in Python
Triggersyesnonoyes infosince Access 2010 using the ACE-engineno
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionShardingShardingnonehorizontal and vertical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesInternal replication in Colossus, and regional replication between two clusters in different zonesActive-active shard replicationnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonono
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)Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsAtomic single-row operationsnoACID infobut no files for transaction loggingACID
Concurrency infoSupport for concurrent manipulation of datayesyesNo - written data is immutableyesyes
Durability infoSupport for making data persistentyesyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyes 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.yesnoyes
User concepts infoAccess controlLDAP bind authenticationAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardno infoa simple user-level security was built in till version Access 2003

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More resources
Atos Standard Common RepositoryGoogle Cloud BigtableIBM Db2 Event StoreMicrosoft AccessSQream DB
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