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DBMS > Adabas vs. Apache Impala vs. GridDB vs. Yaacomo

System Properties Comparison Adabas vs. Apache Impala vs. GridDB vs. Yaacomo

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Editorial information provided by DB-Engines
NameAdabas infodenotes "adaptable data base"  Xexclude from comparisonApache Impala  Xexclude from comparisonGridDB  Xexclude from comparisonYaacomo  Xexclude from comparison
Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionOLTP - DBMS for mainframes and Linux/Unix/Windows environments infoused typically together with the Natural programming platformAnalytic DBMS for HadoopScalable in-memory time series database optimized for IoT and Big DataOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelMultivalue DBMSRelational DBMSTime Series DBMSRelational DBMS
Secondary database modelsDocument storeKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.17
Rank#94  Overall
#1  Multivalue DBMS
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Websitewww.softwareag.com/­en_corporate/­platform/­adabas-natural.htmlimpala.apache.orggriddb.netyaacomo.com
Technical documentationimpala.apache.org/­impala-docs.htmldocs.griddb.net
DeveloperSoftware AGApache Software Foundation infoApache top-level project, originally developed by ClouderaToshiba CorporationQ2WEB GmbH
Initial release1971201320132009
Current release4.1.0, June 20225.1, August 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2Open Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++
Server operating systemsBS2000
Linux
Unix
Windows
z/OS
z/VSE
LinuxLinuxAndroid
Linux
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyes infonumerical, string, blob, geometry, boolean, timestampyes
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.nononono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLyes infowith add-on product Adabas SQL GatewaySQL-like DML and DDL statementsSQL92, SQL-like TQL (Toshiba Query Language)yes
APIs and other access methodsHTTP API infowith add-on software Adabas SOA Gateway
SOAP-based API infowith add-on software Adabas SOA Gateway
JDBC
ODBC
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
JDBC
ODBC
Supported programming languagesNaturalAll languages supporting JDBC/ODBCC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Server-side scripts infoStored proceduresin Naturalyes infouser defined functions and integration of map-reduceno
Triggersnonoyesyes
Partitioning methods infoMethods for storing different data on different nodesyes, with additonal products like Adabas Cluster Services, Adabas Parallel Services, Adabas VistaShardingShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes, with add-on product Event Replicatorselectable replication factorSource-replica replicationSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReduceConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate consistency within container, eventual consistency across containersImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID at container levelACID
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.nonoyesyes
User concepts infoAccess controlonly with OS-specific tools (e.g. IBM RACF, CA Top Secret)Access rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights for users can be defined per databasefine grained access rights according to SQL-standard
More information provided by the system vendor
Adabas infodenotes "adaptable data base"Apache ImpalaGridDBYaacomo
Specific characteristicsGridDB 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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Adabas infodenotes "adaptable data base"Apache ImpalaGridDBYaacomo
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