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

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

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonAtos Standard Common Repository  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.
DescriptionAnalytic DBMS for HadoopHighly 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 efficiencyGridGain is an in-memory computing platform, built on Apache Ignitea GPU-based, columnar RDBMS for big data analytics workloads
Primary database modelRelational DBMSDocument store
Key-value store
Time Series DBMSKey-value store
Relational DBMS
Relational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  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
Websiteimpala.apache.orgatos.net/en/convergence-creators/portfolio/standard-common-repositorygreptime.comwww.gridgain.comsqream.com
Technical documentationimpala.apache.org/­impala-docs.htmldocs.greptime.comwww.gridgain.com/­docs/­index.htmldocs.sqream.com
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaAtos Convergence CreatorsGreptime Inc.GridGain Systems, Inc.SQream Technologies
Initial release20132016202220072017
Current release4.1.0, June 20221703GridGain 8.5.12022.1.6, December 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoApache Version 2.0commercialcommercial
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++JavaRustJava, C++, .NetC++, CUDA, Haskell, Java, Scala
Server operating systemsLinuxLinuxAndroid
Docker
FreeBSD
Linux
macOS
Windows
Linux
OS X
Solaris
Windows
Linux
Data schemeyesSchema and schema-less with LDAP viewsschema-free, schema definition possibleyesyes
Typing infopredefined data types such as float or dateyesoptionalyesyesyes, 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.noyesnoyes
Secondary indexesyesyesyesyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsnoyesANSI-99 for query and DML statements, subset of DDLyes
APIs and other access methodsJDBC
ODBC
LDAPgRPC
HTTP API
JDBC
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
.Net
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCAll languages with LDAP bindingsC++
Erlang
Go
Java
JavaScript
C#
C++
Java
PHP
Python
Ruby
Scala
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoPythonyes (compute grid and cache interceptors can be used instead)user defined functions in Python
Triggersnoyesyes (cache interceptors and events)no
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infocell divisionShardingShardinghorizontal and vertical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesyes (replicated cache)none
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoyes (compute grid and hadoop accelerator)no
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic execution of specific operationsACIDACID
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.noyesyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosLDAP bind authenticationSimple rights management via user accountsSecurity Hooks for custom implementations
More information provided by the system vendor
Apache ImpalaAtos Standard Common RepositoryGreptimeDBGridGainSQream DB
Specific characteristicsGreptimeDB 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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More resources
Apache ImpalaAtos Standard Common RepositoryGreptimeDBGridGainSQream DB
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