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DBMS > Atos Standard Common Repository vs. QuestDB vs. Spark SQL vs. Stardog

System Properties Comparison Atos Standard Common Repository vs. QuestDB vs. Spark SQL vs. Stardog

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Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonQuestDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonStardog  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 networksA high performance open source SQL database for time series dataSpark SQL is a component on top of 'Spark Core' for structured data processingEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization
Primary database modelDocument store
Key-value store
Time Series DBMSRelational DBMSGraph DBMS
RDF store
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.52
Rank#109  Overall
#9  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score2.02
Rank#123  Overall
#11  Graph DBMS
#6  RDF stores
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositoryquestdb.iospark.apache.org/­sqlwww.stardog.com
Technical documentationquestdb.io/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.stardog.com
DeveloperAtos Convergence CreatorsQuestDB Technology IncApache Software FoundationStardog-Union
Initial release2016201420142010
Current release17033.5.0 ( 2.13), September 20237.3.0, May 2020
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoApache 2.0commercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJava (Zero-GC), C++, RustScalaJava
Server operating systemsLinuxLinux
macOS
Windows
Linux
OS X
Windows
Linux
macOS
Windows
Data schemeSchema and schema-less with LDAP viewsyes infoschema-free via InfluxDB Line Protocolyesschema-free and OWL/RDFS-schema support
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.yesnonono infoImport/export of XML data possible
Secondary indexesyesnonoyes infosupports real-time indexing in full-text and geospatial
SQL infoSupport of SQLnoSQL with time-series extensionsSQL-like DML and DDL statementsYes, compatible with all major SQL variants through dedicated BI/SQL Server
APIs and other access methodsLDAPHTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
JDBC
ODBC
GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3
Supported programming languagesAll languages with LDAP bindingsC infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
Java
Python
R
Scala
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
Server-side scripts infoStored proceduresnononouser defined functions and aggregates, HTTP Server extensions in Java
Triggersyesnonoyes infovia event handlers
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionhorizontal partitioning (by timestamps)yes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replication with eventual consistencynoneMulti-source replication in HA-Cluster
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency in HA-Cluster
Foreign keys infoReferential integritynononoyes inforelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsACID for single-table writesnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infothrough memory mapped filesnoyes
User concepts infoAccess controlLDAP bind authenticationnoAccess rights for users and roles
More information provided by the system vendor
Atos Standard Common RepositoryQuestDBSpark SQLStardog
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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Atos Standard Common RepositoryQuestDBSpark SQLStardog
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