DBMS > Adabas vs. Microsoft SQL Server vs. Spark SQL
System Properties Comparison Adabas vs. Microsoft SQL Server vs. Spark SQL
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|Editorial information provided by DB-Engines|
|Name||Adabas denotes "adaptable data base" Xexclude from comparison||Microsoft SQL Server Xexclude from comparison||Spark SQL Xexclude from comparison|
|Description||OLTP - DBMS for mainframes and Linux/Unix/Windows environments used typically together with the Natural programming platform||Microsofts relational DBMS||Spark SQL is a component on top of 'Spark Core' for structured data processing|
|Primary database model||Multivalue DBMS||Relational DBMS||Relational DBMS|
|Secondary database models||Document store|
|Developer||Software AG||Microsoft||Apache Software Foundation|
|Current release||SQL Server 2017, October 2017||v2.4.4, September 2019|
|License Commercial or Open Source||commercial||commercial restricted free version is available||Open Source Apache 2.0|
|Cloud-based only Only available as a cloud service||no||no||no|
|DBaaS offerings (sponsored links) Database as a Service|
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|Server operating systems||BS2000|
|Typing predefined data types such as float or date||yes||yes||yes|
|XML support Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.||no||yes||no|
|SQL Support of SQL||yes with add-on product Adabas SQL Gateway||yes||SQL-like DML and DDL statements|
|APIs and other access methods||HTTP API with add-on software Adabas SOA Gateway|
SOAP-based API with add-on software Adabas SOA Gateway
Tabular Data Stream (TDS)
|Supported programming languages||Natural||C#|
|Server-side scripts Stored procedures||in Natural||Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java||no|
|Partitioning methods Methods for storing different data on different nodes||yes, with additonal products like Adabas Cluster Services, Adabas Parallel Services, Adabas Vista||tables can be distributed across several files (horizontal partitioning); sharding through federation||yes, utilizing Spark Core|
|Replication methods Methods for redundantly storing data on multiple nodes||yes, with add-on product Event Replicator||yes, but depending on the SQL-Server Edition||none|
|MapReduce Offers an API for user-defined Map/Reduce methods||no||no|
|Consistency concepts Methods to ensure consistency in a distributed system||Immediate Consistency||Immediate Consistency|
|Foreign keys Referential integrity||no||yes||no|
|Transaction concepts Support to ensure data integrity after non-atomic manipulations of data||ACID||ACID||no|
|Concurrency Support for concurrent manipulation of data||yes||yes||yes|
|Durability Support for making data persistent||yes||yes||yes|
|In-memory capabilities Is there an option to define some or all structures to be held in-memory only.||no||yes||no|
|User concepts Access control||only with OS-specific tools (e.g. IBM RACF, CA Top Secret)||fine grained access rights according to SQL-standard||no|
More information provided by the system vendor
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|Adabas denotes "adaptable data base"||Microsoft SQL Server||Spark SQL|
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|Conferences and events|
PASS Summit 2019
Spark Summit Europe 2019
|Recent citations in the news|
Software AG: Q3 Due On October 22 - Wait For A Further Pullback
Software AG Announces New “Adabas & Natural 2050” Agenda
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Software (ETR:SOW) Given a €26.00 Price Target at JPMorgan Chase & Co.
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