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DBMS > Atos Standard Common Repository vs. Databricks vs. JanusGraph vs. Microsoft Access vs. Tkrzw

System Properties Comparison Atos Standard Common Repository vs. Databricks vs. JanusGraph vs. Microsoft Access vs. Tkrzw

Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonDatabricks  Xexclude from comparisonJanusGraph infosuccessor of Titan  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  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 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.A Graph DBMS optimized for distributed clusters infoIt was forked from the latest code base of Titan in January 2017Microsoft 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 concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet
Primary database modelDocument store
Key-value store
Document store
Relational DBMS
Graph DBMSRelational DBMSKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score2.02
Rank#125  Overall
#12  Graph DBMS
Score101.16
Rank#11  Overall
#8  Relational DBMS
Score0.07
Rank#372  Overall
#57  Key-value stores
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.databricks.comjanusgraph.orgwww.microsoft.com/­en-us/­microsoft-365/­accessdbmx.net/­tkrzw
Technical documentationdocs.databricks.comdocs.janusgraph.orgdeveloper.microsoft.com/­en-us/­access
DeveloperAtos Convergence CreatorsDatabricksLinux Foundation; originally developed as Titan by AureliusMicrosoftMikio Hirabayashi
Initial release20162013201719922020
Current release17030.6.3, February 20231902 (16.0.11328.20222), March 20190.9.3, August 2020
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0commercial infoBundled with Microsoft OfficeOpen Source infoApache Version 2.0
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 languageJavaJavaC++C++
Server operating systemsLinuxhostedLinux
OS X
Unix
Windows
Windows infoNot a real database server, but making use of DLLsLinux
macOS
Data schemeSchema and schema-less with LDAP viewsFlexible Schema (defined schema, partial schema, schema free)yesyesschema-free
Typing infopredefined data types such as float or dateoptionalyesyesno
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 indexesyesyesyesyes
SQL infoSupport of SQLnowith Databricks SQLnoyes infobut not compliant to any SQL standardno
APIs and other access methodsLDAPJDBC
ODBC
RESTful HTTP API
Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
ADO.NET
DAO
ODBC
OLE DB
Supported programming languagesAll languages with LDAP bindingsPython
R
Scala
Clojure
Java
Python
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresnouser defined functions and aggregatesyesyes infosince Access 2010 using the ACE-engineno
Triggersyesyesyes infosince Access 2010 using the ACE-engineno
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionyes infodepending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)nonenone
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesyesnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infovia Faunus, a graph analytics enginenono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyes infoRelationships in graphsyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsACIDACIDACID infobut no files for transaction logging
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcastyes 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 infousing specific database classes
User concepts infoAccess controlLDAP bind authenticationUser authentification and security via Rexster Graph Serverno infoa simple user-level security was built in till version Access 2003no
More information provided by the system vendor
Atos Standard Common RepositoryDatabricksJanusGraph infosuccessor of TitanMicrosoft AccessTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
Atos Standard Common RepositoryDatabricksJanusGraph infosuccessor of TitanMicrosoft AccessTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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