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DBMS > Atos Standard Common Repository vs. Citus vs. Hawkular Metrics vs. TimescaleDB

System Properties Comparison Atos Standard Common Repository vs. Citus vs. Hawkular Metrics vs. TimescaleDB

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Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonCitus  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonTimescaleDB  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 networksScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelDocument store
Key-value store
Relational DBMSTime Series DBMSTime Series DBMS
Secondary database modelsDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.21
Rank#129  Overall
#61  Relational DBMS
Score0.07
Rank#366  Overall
#38  Time Series DBMS
Score5.33
Rank#72  Overall
#4  Time Series DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.citusdata.comwww.hawkular.orgwww.timescale.com
Technical documentationdocs.citusdata.comwww.hawkular.org/­hawkular-metrics/­docs/­user-guidedocs.timescale.com
DeveloperAtos Convergence CreatorsCommunity supported by Red HatTimescale
Initial release2016201020142017
Current release17038.1, December 20182.13.0, November 2023
License infoCommercial or Open SourcecommercialOpen Source infoAGPL, commercial license also availableOpen Source infoApache 2.0Open Source infoApache 2.0
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 languageJavaCJavaC
Server operating systemsLinuxLinuxLinux
OS X
Windows
Linux
OS X
Windows
Data schemeSchema and schema-less with LDAP viewsyesschema-freeyes
Typing infopredefined data types such as float or dateoptionalyesyesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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.yesyes infospecific XML type available, but no XML query functionalitynoyes
Secondary indexesyesyesnoyes
SQL infoSupport of SQLnoyes infostandard, with numerous extensionsnoyes infofull PostgreSQL SQL syntax
APIs and other access methodsLDAPADO.NET
JDBC
native C library
ODBC
streaming API for large objects
HTTP RESTADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesAll languages with LDAP bindings.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Go
Java
Python
Ruby
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnouser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.nouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersyesyesyes infovia Hawkular Alertingyes
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionShardingSharding infobased on Cassandrayes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replication infoother methods possible by using 3rd party extensionsselectable replication factor infobased on CassandraSource-replica replication with hot standby and reads on replicas info
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 ConsistencyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate Consistency
Foreign keys infoReferential integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsACIDnoACID
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.yesnonono
User concepts infoAccess controlLDAP bind authenticationfine grained access rights according to SQL-standardnofine grained access rights according to SQL-standard

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More resources
Atos Standard Common RepositoryCitusHawkular MetricsTimescaleDB
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