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

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

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Editorial information provided by DB-Engines
NameAdabas infodenotes "adaptable data base"  Xexclude from comparisonApache Druid  Xexclude from comparisonApache Impala  Xexclude from comparisonGridDB  Xexclude from comparison
DescriptionOLTP - DBMS for mainframes and Linux/Unix/Windows environments infoused typically together with the Natural programming platformOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataAnalytic DBMS for HadoopScalable in-memory time series database optimized for IoT and Big Data
Primary database modelMultivalue DBMSRelational DBMS
Time Series DBMS
Relational DBMSTime Series 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
Score3.34
Rank#88  Overall
#48  Relational DBMS
#7  Time Series 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.htmldruid.apache.orgimpala.apache.orggriddb.net
Technical documentationdruid.apache.org/­docs/­latest/­designimpala.apache.org/­impala-docs.htmldocs.griddb.net
DeveloperSoftware AGApache Software Foundation and contributorsApache Software Foundation infoApache top-level project, originally developed by ClouderaToshiba Corporation
Initial release1971201220132013
Current release29.0.1, April 20244.1.0, June 20225.1, August 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache license v2Open Source infoApache Version 2Open 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 servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++C++
Server operating systemsBS2000
Linux
Unix
Windows
z/OS
z/VSE
Linux
OS X
Unix
LinuxLinux
Data schemeyesyes infoschema-less columns are supportedyesyes
Typing infopredefined data types such as float or dateyesyesyesyes 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.nononono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLyes infowith add-on product Adabas SQL GatewaySQL for queryingSQL-like DML and DDL statementsSQL92, SQL-like TQL (Toshiba Query Language)
APIs and other access methodsHTTP API infowith add-on software Adabas SOA Gateway
SOAP-based API infowith add-on software Adabas SOA Gateway
JDBC
RESTful HTTP/JSON API
JDBC
ODBC
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Supported programming languagesNaturalClojure
JavaScript
PHP
Python
R
Ruby
Scala
All languages supporting JDBC/ODBCC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Server-side scripts infoStored proceduresin Naturalnoyes infouser defined functions and integration of map-reduceno
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesyes, with additonal products like Adabas Cluster Services, Adabas Parallel Services, Adabas VistaSharding infomanual/auto, time-basedShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes, with add-on product Event Replicatoryes, via HDFS, S3 or other storage enginesselectable replication factorSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infoquery execution via MapReduceConnector 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 ConsistencyEventual ConsistencyImmediate consistency within container, eventual consistency across containers
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACID at container level
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.nononoyes
User concepts infoAccess controlonly with OS-specific tools (e.g. IBM RACF, CA Top Secret)RBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights for users can be defined per database
More information provided by the system vendor
Adabas infodenotes "adaptable data base"Apache DruidApache ImpalaGridDB
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 DruidApache ImpalaGridDB
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