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

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

Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonCoveo  Xexclude from comparisonDatabricks  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 networksAI-powered hosted search, recommendation and personalization platform providing tools for both low-code and full-code developmentThe 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.
Primary database modelDocument store
Key-value store
Search engineDocument store
Relational DBMS
Time Series DBMSRDF store
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.28
Rank#114  Overall
#11  Search engines
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
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.coveo.comwww.databricks.comquestdb.iordf4j.org
Technical documentationdocs.coveo.comdocs.databricks.comquestdb.io/­docsrdf4j.org/­documentation
DeveloperAtos Convergence CreatorsCoveoDatabricksQuestDB Technology IncSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release20162012201320142004
Current release1703
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoApache 2.0Open Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud servicenoyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJava (Zero-GC), C++, RustJava
Server operating systemsLinuxhostedhostedLinux
macOS
Windows
Linux
OS X
Unix
Windows
Data schemeSchema and schema-less with LDAP viewshybrid - fields need to be configured prior to indexing, but relationships can be exploited at query time without pre-configurationFlexible Schema (defined schema, partial schema, schema free)yes 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.yesnoyesno
Secondary indexesyesyesyesnoyes
SQL infoSupport of SQLnonowith Databricks SQLSQL with time-series extensionsno
APIs and other access methodsLDAPRESTful HTTP APIJDBC
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
Supported programming languagesAll languages with LDAP bindingsC#
Java
JavaScript
Python
Python
R
Scala
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
Java
PHP
Python
Server-side scripts infoStored proceduresnonouser defined functions and aggregatesnoyes
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 nodesyesyesyesSource-replica replication with eventual consistencynone
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 ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsyesACIDACID 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 authenticationgranular access controls, API key management, content filtersno
More information provided by the system vendor
Atos Standard Common RepositoryCoveoDatabricksQuestDBRDF4J 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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