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DBMS > Atos Standard Common Repository vs. Databricks vs. GreptimeDB vs. GridGain vs. SQream DB

System Properties Comparison Atos Standard Common Repository vs. Databricks vs. GreptimeDB vs. GridGain vs. SQream DB

Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonDatabricks  Xexclude from comparisonGreptimeDB  Xexclude from comparisonGridGain  Xexclude from comparisonSQream DB  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.An open source Time Series DBMS built for increased scalability, high performance and efficiencyGridGain is an in-memory computing platform, built on Apache Ignitea GPU-based, columnar RDBMS for big data analytics workloads
Primary database modelDocument store
Key-value store
Document store
Relational DBMS
Time Series DBMSKey-value store
Relational DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.12
Rank#351  Overall
#34  Time Series DBMS
Score1.55
Rank#150  Overall
#26  Key-value stores
#70  Relational DBMS
Score0.74
Rank#224  Overall
#103  Relational DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.databricks.comgreptime.comwww.gridgain.comsqream.com
Technical documentationdocs.databricks.comdocs.greptime.comwww.gridgain.com/­docs/­index.htmldocs.sqream.com
DeveloperAtos Convergence CreatorsDatabricksGreptime Inc.GridGain Systems, Inc.SQream Technologies
Initial release20162013202220072017
Current release1703GridGain 8.5.12022.1.6, December 2022
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2.0commercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaRustJava, C++, .NetC++, CUDA, Haskell, Java, Scala
Server operating systemsLinuxhostedAndroid
Docker
FreeBSD
Linux
macOS
Windows
Linux
OS X
Solaris
Windows
Linux
Data schemeSchema and schema-less with LDAP viewsFlexible Schema (defined schema, partial schema, schema free)schema-free, schema definition possibleyesyes
Typing infopredefined data types such as float or dateoptionalyesyesyes, ANSI Standard SQL 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.yesyesnoyes
Secondary indexesyesyesyesyesno
SQL infoSupport of SQLnowith Databricks SQLyesANSI-99 for query and DML statements, subset of DDLyes
APIs and other access methodsLDAPJDBC
ODBC
RESTful HTTP API
gRPC
HTTP API
JDBC
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
.Net
JDBC
ODBC
Supported programming languagesAll languages with LDAP bindingsPython
R
Scala
C++
Erlang
Go
Java
JavaScript
C#
C++
Java
PHP
Python
Ruby
Scala
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnouser defined functions and aggregatesPythonyes (compute grid and cache interceptors can be used instead)user defined functions in Python
Triggersyesyes (cache interceptors and events)no
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionShardingShardinghorizontal and vertical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesyes (replicated cache)none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes (compute grid and hadoop accelerator)no
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes
User concepts infoAccess controlLDAP bind authenticationSimple rights management via user accountsSecurity Hooks for custom implementations
More information provided by the system vendor
Atos Standard Common RepositoryDatabricksGreptimeDBGridGainSQream DB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
» more
GreptimeDB is a SQL & Python-enabled timeseries database system built from scratch...
» more
Competitive advantages- Inherits advantages of Rust, such as excellent performance, memory safe, resource...
» more
Typical application scenariosFor IoT industries, GreptimeDB can seamless integrate with message queues and other...
» more
Key customersGreptime's clients span multiple sectors including IoT, connected vehicles, and energy...
» 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

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Atos Standard Common RepositoryDatabricksGreptimeDBGridGainSQream DB
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