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DBMS > Atos Standard Common Repository vs. Databricks vs. Prometheus vs. SwayDB

System Properties Comparison Atos Standard Common Repository vs. Databricks vs. Prometheus vs. SwayDB

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Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonDatabricks  Xexclude from comparisonPrometheus  Xexclude from comparisonSwayDB  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.Open-source Time Series DBMS and monitoring systemAn embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage
Primary database modelDocument store
Key-value store
Document store
Relational DBMS
Time Series DBMSKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score7.69
Rank#50  Overall
#3  Time Series DBMS
Score0.04
Rank#387  Overall
#61  Key-value stores
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.databricks.comprometheus.ioswaydb.simer.au
Technical documentationdocs.databricks.comprometheus.io/­docs
DeveloperAtos Convergence CreatorsDatabricksSimer Plaha
Initial release2016201320152018
Current release1703
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0Open Source infoGNU Affero GPL V3.0
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaGoScala
Server operating systemsLinuxhostedLinux
Windows
Data schemeSchema and schema-less with LDAP viewsFlexible Schema (defined schema, partial schema, schema free)yesschema-free
Typing infopredefined data types such as float or dateoptionalNumeric data onlyno
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 infoImport of XML data possibleno
Secondary indexesyesyesnono
SQL infoSupport of SQLnowith Databricks SQLnono
APIs and other access methodsLDAPJDBC
ODBC
RESTful HTTP API
RESTful HTTP/JSON API
Supported programming languagesAll languages with LDAP bindingsPython
R
Scala
.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
Java
Kotlin
Scala
Server-side scripts infoStored proceduresnouser defined functions and aggregatesnono
Triggersyesnono
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesyes infoby Federationnone
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 ConsistencynoneImmediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsACIDnoAtomic execution of operations
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.yesnonoyes
User concepts infoAccess controlLDAP bind authenticationnono
More information provided by the system vendor
Atos Standard Common RepositoryDatabricksPrometheusSwayDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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