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DBMS > Atos Standard Common Repository vs. Databricks vs. OushuDB vs. QuestDB vs. RDF4J

System Properties Comparison Atos Standard Common Repository vs. Databricks vs. OushuDB vs. QuestDB vs. RDF4J

Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonDatabricks  Xexclude from comparisonOushuDB  Xexclude from comparisonQuestDB  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.A data warehouse powered by Apache HAWQ supporting descriptive analysis and advanced machine learningA high performance open source SQL database for time series dataRDF4J 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
Relational DBMSTime Series DBMSRDF store
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score76.33
Rank#17  Overall
#3  Document stores
#11  Relational DBMS
Score0.09
Rank#357  Overall
#154  Relational DBMS
Score2.48
Rank#115  Overall
#9  Time Series DBMS
Score0.71
Rank#231  Overall
#9  RDF stores
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.databricks.comwww.oushu.com/­product/­oushuDBquestdb.iordf4j.org
Technical documentationdocs.databricks.comwww.oushu.com/­documentationquestdb.io/­docsrdf4j.org/­documentation
DeveloperAtos Convergence CreatorsDatabricksOushuQuestDB Technology IncSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release2016201320142004
Current release17034.0.1, August 2020
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoApache 2.0Open 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 languageJavaJava (Zero-GC), C++, RustJava
Server operating systemsLinuxhostedLinuxLinux
macOS
Windows
Linux
OS X
Unix
Windows
Data schemeSchema and schema-less with LDAP viewsFlexible Schema (defined schema, partial schema, schema free)yesyes infoschema-free via InfluxDB Line Protocolyes infoRDF Schemas
Typing infopredefined data types such as float or dateoptionalyesyesyes
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 indexesyesyesyesnoyes
SQL infoSupport of SQLnowith Databricks SQLFull-featured ANSI SQL supportSQL with time-series extensionsno
APIs and other access methodsLDAPJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
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
C++
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
Java
PHP
Python
Server-side scripts infoStored proceduresnouser defined functions and aggregatesyesnoyes
Triggersyesyesnoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionyeshorizontal partitioning (by timestamps)none
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesSource-replica replication with eventual consistencynone
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsACIDACIDACID for single-table writesACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes 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.yesnoyes infothrough memory mapped files
User concepts infoAccess controlLDAP bind authenticationKerberos, SSL and role based accessno
More information provided by the system vendor
Atos Standard Common RepositoryDatabricksOushuDBQuestDBRDF4J infoformerly known as Sesame
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
» more
Relational model with native time series support Column-based storage and time partitioned...
» more
Competitive advantagesHigh ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more
Typical application scenariosFinancial tick data Industrial IoT Application Metrics Monitoring
» more
Key customersBanks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more
Licensing and pricing modelsOpen source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more
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