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DBMS > Atos Standard Common Repository vs. Databricks vs. LevelDB vs. RavenDB vs. RDF4J

System Properties Comparison Atos Standard Common Repository vs. Databricks vs. LevelDB vs. RavenDB vs. RDF4J

Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonDatabricks  Xexclude from comparisonLevelDB  Xexclude from comparisonRavenDB  Xexclude from comparisonRDF4J infoformerly known as Sesame  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.Embeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesOpen Source Operational and Transactional Enterprise NoSQL Document DatabaseRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.
Primary database modelDocument store
Key-value store
Document store
Relational DBMS
Key-value storeDocument storeRDF store
Secondary database modelsGraph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score2.35
Rank#111  Overall
#19  Key-value stores
Score2.92
Rank#101  Overall
#18  Document stores
Score0.69
Rank#230  Overall
#9  RDF stores
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.databricks.comgithub.com/­google/­leveldbravendb.netrdf4j.org
Technical documentationdocs.databricks.comgithub.com/­google/­leveldb/­blob/­main/­doc/­index.mdravendb.net/­docsrdf4j.org/­documentation
DeveloperAtos Convergence CreatorsDatabricksGoogleHibernating RhinosSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release20162013201120102004
Current release17031.23, February 20215.4, July 2022
License infoCommercial or Open SourcecommercialcommercialOpen Source infoBSDOpen Source infoAGPL version 3, commercial license availableOpen Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++C#Java
Server operating systemsLinuxhostedIllumos
Linux
OS X
Windows
Linux
macOS
Raspberry Pi
Windows
Linux
OS X
Unix
Windows
Data schemeSchema and schema-less with LDAP viewsFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-freeyes infoRDF Schemas
Typing infopredefined data types such as float or dateoptionalnonoyes
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.yesyesno
Secondary indexesyesyesnoyesyes
SQL infoSupport of SQLnowith Databricks SQLnoSQL-like query language (RQL)no
APIs and other access methodsLDAPJDBC
ODBC
RESTful HTTP API
.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Supported programming languagesAll languages with LDAP bindingsPython
R
Scala
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
PHP
Python
Server-side scripts infoStored proceduresnouser defined functions and aggregatesnoyesyes
Triggersyesnoyesyes
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionnoneShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesnoneMulti-source replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate ConsistencyDefault ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsACIDnoACID, Cluster-wide transaction availableACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes infowith automatic compression on writesyesyes infoin-memory storage is supported as well
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlLDAP bind authenticationnoAuthorization levels configured per client per databaseno
More information provided by the system vendor
Atos Standard Common RepositoryDatabricksLevelDBRavenDBRDF4J infoformerly known as Sesame
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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Atos Standard Common RepositoryDatabricksLevelDBRavenDBRDF4J infoformerly known as Sesame
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