DBMS > Adabas vs. EventStoreDB vs. Hive vs. ReductStore vs. Yaacomo

System Properties Comparison Adabas vs. EventStoreDB vs. Hive vs. ReductStore vs. Yaacomo

Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

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

used typically together with the Natural programming platform

Industrial-strength, open-source database solution built from the ground up for event sourcing.

data warehouse software for querying and managing large distributed datasets, built on Hadoop

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.

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

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

Score	2.79
Rank	#102	Overall
	#2	Multivalue DBMS

Score	1.19
Rank	#173	Overall
	#1	Event Stores

Score	59.76
Rank	#18	Overall
	#12	Relational DBMS

Score	0.05
Rank	#384	Overall
	#44	Time Series DBMS

Website

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

www.eventstore.com

hive.apache.org

github.com/reductstore
www.reduct.store

yaacomo.com

Technical documentation

developers.eventstore.com

cwiki.apache.org/confluence/display/Hive/Home

www.reduct.store/docs

Developer

Software AG

Event Store Limited

Apache Software Foundation

initially developed by Facebook

ReductStore LLC

Q2WEB GmbH

Initial release

1971

2012

2023

2009

Current release

21.2, February 2021

3.1.3, April 2022

1.9, March 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

Open Source

Business Source License 1.1

commercial

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++, Rust

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

Linux
Windows

All OS with a Java VM

Docker
Linux
macOS
Windows

Android
Linux
Windows

Data scheme

yes

Typing

predefined data types such as float or date

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

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
Thrift

HTTP API

JDBC
ODBC

Supported programming languages

Natural

C++
Java
PHP
Python

C++
JavaScript (Node.js)
Python
Rust

Server-side scripts

Stored procedures

in Natural

yes

user defined functions and integration of map-reduce

Triggers

yes

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

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

selectable replication factor

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

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

User concepts

Access control

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

Access rights for users, groups and roles

fine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

Why is Hadoop not listed in the DB-Engines Ranking?
13 May 2013, Paul Andlinger

show all

Recent citations in the news

Re-evaluating legacy: Should you leave Adabas (and Natural) behind?
30 May 2024, ITWeb

State agency proves DevOps and mainframes can coexist
12 April 2024, SiliconANGLE News

Is it the end of the road for Software AG after selling its integration business to IBM?
12 January 2024, diginomica

IBM buys 50-year-old Software AG's enterprise tech units for €2.13B in cash
18 December 2023, The Register

Michael E. Jakes Obituary (1941 - 2023)
26 October 2023, Legacy.com

provided by Google News

Design a data mesh pattern for Amazon EMR-based data lakes using AWS Lake Formation with Hive metastore ...
10 June 2024, AWS Blog

Apache Software Foundation Announces Apache Hive 4.0
30 April 2024, Datanami

18 Top Big Data Tools and Technologies to Know About in 2024
24 January 2024, TechTarget

ASF Unveils the Next Evolution of Big Data Processing With the Launch of Hive 4.0
2 May 2024, Datanami

Run Apache Hive workloads using Spark SQL with Amazon EMR on EKS | Amazon Web Services
18 October 2023, AWS Blog

provided by Google News

Share this page