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DBMS > Atos Standard Common Repository vs. Microsoft Azure Synapse Analytics vs. QuestDB vs. RDF4J vs. Spark SQL

System Properties Comparison Atos Standard Common Repository vs. Microsoft Azure Synapse Analytics vs. QuestDB vs. RDF4J vs. Spark SQL

Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonQuestDB  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonSpark SQL  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 networksElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerA 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.Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Key-value store
Relational DBMSTime Series DBMSRDF storeRelational DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score20.56
Rank#31  Overall
#19  Relational DBMS
Score2.52
Rank#109  Overall
#9  Time Series DBMS
Score0.69
Rank#230  Overall
#9  RDF stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositoryazure.microsoft.com/­services/­synapse-analyticsquestdb.iordf4j.orgspark.apache.org/­sql
Technical documentationdocs.microsoft.com/­azure/­synapse-analyticsquestdb.io/­docsrdf4j.org/­documentationspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAtos Convergence CreatorsMicrosoftQuestDB Technology IncSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.Apache Software Foundation
Initial release20162016201420042014
Current release17033.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0Open Source infoEclipse Distribution License (EDL), v1.0.Open Source infoApache 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 languageJavaC++Java (Zero-GC), C++, RustJavaScala
Server operating systemsLinuxhostedLinux
macOS
Windows
Linux
OS X
Unix
Windows
Linux
OS X
Windows
Data schemeSchema and schema-less with LDAP viewsyesyes infoschema-free via InfluxDB Line Protocolyes infoRDF Schemasyes
Typing infopredefined data types such as float or dateoptionalyesyesyesyes
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.yesnonono
Secondary indexesyesyesnoyesno
SQL infoSupport of SQLnoyesSQL with time-series extensionsnoSQL-like DML and DDL statements
APIs and other access methodsLDAPADO.NET
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
JDBC
ODBC
Supported programming languagesAll languages with LDAP bindingsC#
Java
PHP
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
Java
PHP
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoTransact SQLnoyesno
Triggersyesnonoyesno
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionSharding, horizontal partitioninghorizontal partitioning (by timestamps)noneyes, utilizing Spark Core
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 integritynono infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsnono
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
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infothrough memory mapped filesno
User concepts infoAccess controlLDAP bind authenticationyesnono
More information provided by the system vendor
Atos Standard Common RepositoryMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseQuestDBRDF4J infoformerly known as SesameSpark SQL
Specific characteristicsRelational 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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More resources
Atos Standard Common RepositoryMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseQuestDBRDF4J infoformerly known as SesameSpark SQL
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