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DBMS > Atos Standard Common Repository vs. GreptimeDB vs. Vertica

System Properties Comparison Atos Standard Common Repository vs. GreptimeDB vs. Vertica

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Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonGreptimeDB  Xexclude from comparisonVertica infoOpenText™ Vertica™  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 networksAn open source Time Series DBMS built for increased scalability, high performance and efficiencyCloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.
Primary database modelDocument store
Key-value store
Time Series DBMSRelational DBMS infoColumn oriented
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.06
Rank#352  Overall
#33  Time Series DBMS
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorygreptime.comwww.vertica.com
Technical documentationdocs.greptime.comvertica.com/­documentation
DeveloperAtos Convergence CreatorsGreptime Inc.OpenText infopreviously Micro Focus and Hewlett Packard
Initial release201620222005
Current release170312.0.3, January 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenonono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaRustC++
Server operating systemsLinuxAndroid
Docker
FreeBSD
Linux
macOS
Windows
Linux
Data schemeSchema and schema-less with LDAP viewsschema-free, schema definition possibleYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.
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.yesnono
Secondary indexesyesyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLnoyesFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsLDAPgRPC
HTTP API
JDBC
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesAll languages with LDAP bindingsC++
Erlang
Go
Java
JavaScript
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresnoPythonyes, PostgreSQL PL/pgSQL, with minor differences
Triggersyesyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionShardinghorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlLDAP bind authenticationSimple rights management via user accountsfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
Atos Standard Common RepositoryGreptimeDBVertica infoOpenText™ Vertica™
Specific characteristicsGreptimeDB is a SQL & Python-enabled timeseries database system built from scratch...
» more
Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more
Competitive advantages- Inherits advantages of Rust, such as excellent performance, memory safe, resource...
» more
Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
» more
Typical application scenariosFor IoT industries, GreptimeDB can seamless integrate with message queues and other...
» more
Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more
Key customersGreptime's clients span multiple sectors including IoT, connected vehicles, and energy...
» more
Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
Market metricsGreptimeDB has garnered global recognition by topping GitHub trends following its...
» more
Licensing and pricing modelsGreptimeDB: open source, distributed, cloud-native TSDB; supports Hybrid Time-series...
» more
Cost-based models and subscription-based models are both available. One license is...
» more

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More resources
Atos Standard Common RepositoryGreptimeDBVertica infoOpenText™ Vertica™
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