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

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

Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonDatabricks  Xexclude from comparisonQuestDB  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonSphinx  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 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.Open source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument store
Key-value store
Document store
Relational DBMS
Time Series DBMSRDF storeSearch engine
Secondary database modelsRelational 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
Score2.52
Rank#109  Overall
#9  Time Series DBMS
Score0.69
Rank#230  Overall
#9  RDF stores
Score5.98
Rank#56  Overall
#5  Search engines
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.databricks.comquestdb.iordf4j.orgsphinxsearch.com
Technical documentationdocs.databricks.comquestdb.io/­docsrdf4j.org/­documentationsphinxsearch.com/­docs
DeveloperAtos Convergence CreatorsDatabricksQuestDB Technology IncSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.Sphinx Technologies Inc.
Initial release20162013201420042001
Current release17033.5.1, February 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0Open Source infoEclipse Distribution License (EDL), v1.0.Open Source infoGPL version 2, commercial licence available
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 languageJavaJava (Zero-GC), C++, RustJavaC++
Server operating systemsLinuxhostedLinux
macOS
Windows
Linux
OS X
Unix
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeSchema and schema-less with LDAP viewsFlexible Schema (defined schema, partial schema, schema free)yes infoschema-free via InfluxDB Line Protocolyes infoRDF Schemasyes
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.yesyesno
Secondary indexesyesyesnoyesyes infofull-text index on all search fields
SQL infoSupport of SQLnowith Databricks SQLSQL with time-series extensionsnoSQL-like query language (SphinxQL)
APIs and other access methodsLDAPJDBC
ODBC
RESTful HTTP API
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
Proprietary protocol
Supported programming languagesAll languages with LDAP bindingsPython
R
Scala
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
Java
PHP
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnouser defined functions and aggregatesnoyesno
Triggersyesnoyesno
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionhorizontal partitioning (by timestamps)noneSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesSource-replica replication with eventual consistencynonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsACIDACID for single-table writesACID infoIsolation support depends on the API usedno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoin-memory storage is supported as wellyes infoThe original contents of fields are not stored in the Sphinx index.
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 authenticationnono
More information provided by the system vendor
Atos Standard Common RepositoryDatabricksQuestDBRDF4J infoformerly known as SesameSphinx
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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