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DBMS > Adabas vs. Atos Standard Common Repository vs. Databricks vs. Microsoft Azure AI Search vs. Splice Machine

System Properties Comparison Adabas vs. Atos Standard Common Repository vs. Databricks vs. Microsoft Azure AI Search vs. Splice Machine

Editorial information provided by DB-Engines
NameAdabas infodenotes "adaptable data base"  Xexclude from comparisonAtos Standard Common Repository  Xexclude from comparisonDatabricks  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonSplice Machine  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.
DescriptionOLTP - DBMS for mainframes and Linux/Unix/Windows environments infoused typically together with the Natural programming platformHighly 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.Search-as-a-service for web and mobile app developmentOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelMultivalue DBMSDocument store
Key-value store
Document store
Relational DBMS
Search engineRelational DBMS
Secondary database modelsVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.17
Rank#94  Overall
#1  Multivalue DBMS
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score5.59
Rank#63  Overall
#7  Search engines
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitewww.softwareag.com/­en_corporate/­platform/­adabas-natural.htmlatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.databricks.comazure.microsoft.com/­en-us/­services/­searchsplicemachine.com
Technical documentationdocs.databricks.comlearn.microsoft.com/­en-us/­azure/­searchsplicemachine.com/­how-it-works
DeveloperSoftware AGAtos Convergence CreatorsDatabricksMicrosoftSplice Machine
Initial release19712016201320152014
Current release1703V13.1, March 2021
License infoCommercial or Open SourcecommercialcommercialcommercialcommercialOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenonoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJava
Server operating systemsBS2000
Linux
Unix
Windows
z/OS
z/VSE
LinuxhostedhostedLinux
OS X
Solaris
Windows
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
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.noyesyesno
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLyes infowith add-on product Adabas SQL Gatewaynowith Databricks SQLnoyes
APIs and other access methodsHTTP API infowith add-on software Adabas SOA Gateway
SOAP-based API infowith add-on software Adabas SOA Gateway
LDAPJDBC
ODBC
RESTful HTTP API
RESTful HTTP APIJDBC
Native Spark Datasource
ODBC
Supported programming languagesNaturalAll languages with LDAP bindingsPython
R
Scala
C#
Java
JavaScript
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresin Naturalnouser defined functions and aggregatesnoyes infoJava
Triggersnoyesnoyes
Partitioning methods infoMethods for storing different data on different nodesyes, with additonal products like Adabas Cluster Services, Adabas Parallel Services, Adabas VistaSharding infocell divisionSharding infoImplicit feature of the cloud serviceShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes, with add-on product Event Replicatoryesyesyes infoImplicit feature of the cloud serviceMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic execution of specific operationsACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
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.noyesnonoyes
User concepts infoAccess controlonly with OS-specific tools (e.g. IBM RACF, CA Top Secret)LDAP bind authenticationyes infousing Azure authenticationAccess rights for users, groups and roles according to SQL-standard
More information provided by the system vendor
Adabas infodenotes "adaptable data base"Atos Standard Common RepositoryDatabricksMicrosoft Azure AI SearchSplice Machine
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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Adabas infodenotes "adaptable data base"Atos Standard Common RepositoryDatabricksMicrosoft Azure AI SearchSplice Machine
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