DBMS > Adabas vs. Kinetica vs. ReductStore vs. RisingWave

System Properties Comparison Adabas vs. Kinetica vs. ReductStore vs. RisingWave

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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

Fully vectorized database across both GPUs and CPUs

Designed to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.

A distributed RDBMS for stream processing, wire-compatible with PostgreSQL

Primary database model

Secondary database models

Spatial DBMS
Time Series DBMS

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

Score	2.64
Rank	#104	Overall
	#1	Multivalue DBMS

Score	0.42
Rank	#261	Overall
	#120	Relational DBMS

Score	0.00
Rank	#385	Overall
	#40	Time Series DBMS

Score	0.61
Rank	#237	Overall
	#111	Relational DBMS

Website

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

www.kinetica.com

github.com/reductstore
www.reduct.store

www.risingwave.com/database

Technical documentation

docs.kinetica.com

www.reduct.store/docs

docs.risingwave.com/docs/current/intro

Developer

Software AG

Kinetica

ReductStore LLC

RisingWave Labs

Initial release

1971

2012

2023

2022

Current release

7.1, August 2021

1.9, March 2024

1.2, September 2023

License

Commercial or Open Source

commercial

Open Source

Business Source License 1.1

Open Source

Apache Version 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

C, C++

C++, Rust

Rust

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

Linux

Docker
Linux
macOS
Windows

Docker
Linux
macOS

Data scheme

yes

Typing

predefined data types such as float or date

yes

Standard SQL-types and JSON

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

yes

APIs and other access methods

HTTP API

with add-on software Adabas SOA Gateway
SOAP-based API

with add-on software Adabas SOA Gateway

JDBC
ODBC
RESTful HTTP API

HTTP API

JDBC
PostgreSQL wire protocol

Supported programming languages

Natural

C++
Java
JavaScript (Node.js)
Python

C++
JavaScript (Node.js)
Python
Rust

Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

in Natural

user defined functions

UDFs in Python or Java

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

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

GPU vRAM or System RAM

yes

User concepts

Access control

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

Access rights for users and roles on table level

Users and Roles

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