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DBMS > Atos Standard Common Repository vs. CrateDB vs. Linter vs. SWC-DB

System Properties Comparison Atos Standard Common Repository vs. CrateDB vs. Linter vs. SWC-DB

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Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonCrateDB  Xexclude from comparisonLinter  Xexclude from comparisonSWC-DB infoSuper Wide Column Database  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 networksDistributed Database based on LuceneRDBMS for high security requirementsA high performance, scalable Wide Column DBMS
Primary database modelDocument store
Key-value store
Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Relational DBMSWide column store
Secondary database modelsRelational DBMSSpatial DBMSTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.73
Rank#224  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Score0.09
Rank#346  Overall
#152  Relational DBMS
Score0.01
Rank#376  Overall
#13  Wide column stores
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorycratedb.comlinter.rugithub.com/­kashirin-alex/­swc-db
www.swcdb.org
Technical documentationcratedb.com/­docs
DeveloperAtos Convergence CreatorsCraterelex.ruAlex Kashirin
Initial release2016201319902020
Current release17030.5, April 2021
License infoCommercial or Open SourcecommercialOpen SourcecommercialOpen Source infoGPL V3
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.
CrateDB Cloud: a distributed SQL database that spreads data and processing across an elastic cluster of shared nothing nodes. CrateDB Cloud enables data insights at scale on Microsoft Azure, AWS and Google Cloud Platform.
Implementation languageJavaJavaC and C++C++
Server operating systemsLinuxAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportAIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
Linux
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 dateoptionalyesyes
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 indexesyesyesyes
SQL infoSupport of SQLnoyes, but no triggers and constraints, and PostgreSQL compatibilityyesSQL-like query language
APIs and other access methodsLDAPADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
Proprietary protocol
Thrift
Supported programming languagesAll languages with LDAP bindings.NET
Erlang
Go infocommunity maintained client
Java
JavaScript (Node.js) infocommunity maintained client
Perl infocommunity maintained client
PHP
Python
R
Ruby infocommunity maintained client
Scala infocommunity maintained client
C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl
C++
Server-side scripts infoStored proceduresnouser defined functions (Javascript)yes infoproprietary syntax with the possibility to convert from PL/SQLno
Triggersyesnoyesno
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionShardingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesConfigurable replication on table/partition-levelSource-replica replication
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 configurationEventual Consistency
Read-after-write consistency on record level
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsno infounique row identifiers can be used for implementing an optimistic concurrency control strategyACID
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.yesnono
User concepts infoAccess controlLDAP bind authenticationrights management via user accountsfine grained access rights according to SQL-standard
More information provided by the system vendor
Atos Standard Common RepositoryCrateDBLinterSWC-DB infoSuper Wide Column Database
Specific characteristicsThe enterprise database for time series, documents, and vectors. Distributed - Native...
» more
Competitive advantagesResponse time in milliseconds: e ven for complex ad-hoc queries. Massive scaling...
» more
Typical application scenarios​ IoT: accelerate your IIoT projects with CrateDB, delivering real-time analytics...
» more
Key customersAcross all continents, CrateDB is used by companies of all sizes to meet the most...
» more
Market metricsThe CrateDB open source project was started in 2013 Honorable Mention in 2021 Gartner®...
» more
Licensing and pricing modelsSee CrateDB pricing >
» more

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Atos Standard Common RepositoryCrateDBLinterSWC-DB infoSuper Wide Column Database
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