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

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

Editorial information provided by DB-Engines
NameAdabas infodenotes "adaptable data base"  Xexclude from comparisonAtos Standard Common Repository  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonSnowflake  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 networksSearch-as-a-service for web and mobile app developmentCloud-based data warehousing service for structured and semi-structured dataOpen-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
Search engineRelational DBMSRelational 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
Score5.59
Rank#63  Overall
#7  Search engines
Score121.33
Rank#9  Overall
#6  Relational DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitewww.softwareag.com/­en_corporate/­platform/­adabas-natural.htmlatos.net/en/convergence-creators/portfolio/standard-common-repositoryazure.microsoft.com/­en-us/­services/­searchwww.snowflake.comsplicemachine.com
Technical documentationlearn.microsoft.com/­en-us/­azure/­searchdocs.snowflake.net/­manuals/­index.htmlsplicemachine.com/­how-it-works
DeveloperSoftware AGAtos Convergence CreatorsMicrosoftSnowflake Computing Inc.Splice Machine
Initial release19712016201520142014
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

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Implementation languageJavaJava
Server operating systemsBS2000
Linux
Unix
Windows
z/OS
z/VSE
LinuxhostedhostedLinux
OS X
Solaris
Windows
Data schemeyesSchema and schema-less with LDAP viewsyesyes infosupport of semi-structured data formats (JSON, XML, Avro)yes
Typing infopredefined data types such as float or dateyesoptionalyesyesyes
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 indexesyesyesyesyes
SQL infoSupport of SQLyes infowith add-on product Adabas SQL Gatewaynonoyesyes
APIs and other access methodsHTTP API infowith add-on software Adabas SOA Gateway
SOAP-based API infowith add-on software Adabas SOA Gateway
LDAPRESTful HTTP APICLI Client
JDBC
ODBC
JDBC
Native Spark Datasource
ODBC
Supported programming languagesNaturalAll languages with LDAP bindingsC#
Java
JavaScript
Python
JavaScript (Node.js)
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresin Naturalnonouser defined functionsyes infoJava
Triggersnoyesnono infosimilar concept for controling cloud resourcesyes
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 serviceyesShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes, with add-on product Event Replicatoryesyes infoImplicit feature of the cloud serviceyesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoYes, 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 integritynononoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic execution of specific operationsnoACIDACID
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 authenticationUsers with fine-grained authorization concept, user roles and pluggable authenticationAccess rights for users, groups and roles according to SQL-standard

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Adabas infodenotes "adaptable data base"Atos Standard Common RepositoryMicrosoft Azure AI SearchSnowflakeSplice Machine
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