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DBMS > Altibase vs. Atos Standard Common Repository vs. Databricks vs. Greenplum vs. GridDB

System Properties Comparison Altibase vs. Atos Standard Common Repository vs. Databricks vs. Greenplum vs. GridDB

Editorial information provided by DB-Engines
NameAltibase  Xexclude from comparisonAtos Standard Common Repository  Xexclude from comparisonDatabricks  Xexclude from comparisonGreenplum  Xexclude from comparisonGridDB  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.
DescriptionAn enterprise grade, high-performance RDBMSHighly 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.Analytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database infoA logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.Scalable in-memory time series database optimized for IoT and Big Data
Primary database modelRelational DBMSDocument store
Key-value store
Document store
Relational DBMS
Relational DBMSTime Series DBMS
Secondary database modelsDocument store
Spatial DBMS
Key-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.02
Rank#189  Overall
#88  Relational DBMS
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score8.08
Rank#48  Overall
#31  Relational DBMS
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Websitealtibase.comatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.databricks.comgreenplum.orggriddb.net
Technical documentationgithub.com/­ALTIBASE/­Documents/­tree/­master/­Manualsdocs.databricks.comdocs.greenplum.orgdocs.griddb.net
DeveloperAltibaseAtos Convergence CreatorsDatabricksPivotal Software Inc.Toshiba Corporation
Initial release19992016201320052013
Current releasev7.3, 2023, August 202317037.0.0, September 20235.1, August 2022
License infoCommercial or Open Sourcecommercial infoOpen source edition discontinued with March 2023commercialcommercialOpen Source infoApache 2.0Open Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++JavaC++
Server operating systemsAIX
HP-UX
Linux
LinuxhostedLinuxLinux
Data schemeyesSchema and schema-less with LDAP viewsFlexible Schema (defined schema, partial schema, schema free)yesyes
Typing infopredefined data types such as float or dateyesoptionalyesyes infonumerical, string, blob, geometry, boolean, timestamp
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.noyesyesyes infosince Version 4.2no
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLANSI SQL-92nowith Databricks SQLyesSQL92, SQL-like TQL (Toshiba Query Language)
APIs and other access methodsJDBC
ODBC
Proprietary protocol
LDAPJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Supported programming languagesC
C++
Java
All languages with LDAP bindingsPython
R
Scala
C
Java
Perl
Python
R
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Server-side scripts infoStored proceduresstored procedures and stored functionsnouser defined functions and aggregatesyesno
Triggersyesyesyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infocell divisionShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesyesSource-replica replicationSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobs
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate ConsistencyImmediate consistency within container, eventual consistency across containers
Foreign keys infoReferential integrityyesnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic execution of specific operationsACIDACIDACID at container level
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.yesyesnonoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardLDAP bind authenticationfine grained access rights according to SQL-standardAccess rights for users can be defined per database
More information provided by the system vendor
AltibaseAtos Standard Common RepositoryDatabricksGreenplumGridDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
» more
GridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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More resources
AltibaseAtos Standard Common RepositoryDatabricksGreenplumGridDB
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