DBMS > Adabas vs. Oracle NoSQL vs. RocksDB vs. Spark SQL

System Properties Comparison Adabas vs. Oracle NoSQL vs. RocksDB vs. Spark SQL

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Editorial information provided by DB-Engines

Name

Description

OLTP - DBMS for mainframes and Linux/Unix/Windows environments

used typically together with the Natural programming platform

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Spark SQL is a component on top of 'Spark Core' for structured data processing

Primary database model

Multivalue DBMS

Document store
Key-value store
Relational DBMS

Key-value store

Relational DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	2.79
Rank	#102	Overall
	#2	Multivalue DBMS

Score	3.05
Rank	#97	Overall
	#17	Document stores
	#16	Key-value stores
	#50	Relational DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Website

www.softwareag.com/en_corporate/platform/adabas-natural.html

www.oracle.com/database/nosql/technologies/nosql

rocksdb.org

spark.apache.org/sql

Technical documentation

docs.oracle.com/en/database/other-databases/nosql-database/index.html

github.com/facebook/rocksdb/wiki

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

Software AG

Oracle

Facebook, Inc.

Apache Software Foundation

Initial release

1971

2011

2013

2014

Current release

24.1, May 2024

9.2.1, May 2024

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

commercial

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

Open Source

BSD

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C++

Scala

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

Linux
Solaris SPARC/x86

Linux

Linux
OS X
Windows

Data scheme

yes

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

schema-free

yes

Typing

predefined data types such as float or date

yes

optional

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.

Secondary indexes

yes

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

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

RESTful HTTP API

C++ API
Java API

JDBC
ODBC

Supported programming languages

Natural

C
C#
Go
Java
JavaScript (Node.js)
Python

C
C++
Go
Java
Perl
Python
Ruby

Java
Python
R
Scala

Server-side scripts

Stored procedures

in Natural

Triggers

Partitioning methods

Methods for storing different data on different nodes

yes, with additonal products like Adabas Cluster Services, Adabas Parallel Services, Adabas Vista

Sharding

horizontal partitioning

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

Foreign keys

Referential integrity

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

configurable

ACID within a storage node (=shard)

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

off heap cache

yes

User concepts

Access control

only with OS-specific tools (e.g. IBM RACF, CA Top Secret)

Access rights for users and roles

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