DBMS > Adabas vs. BigObject vs. ClickHouse vs. EsgynDB

System Properties Comparison Adabas vs. BigObject vs. ClickHouse vs. EsgynDB

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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

Analytic DBMS for real-time computations and queries

A high-performance, column-oriented SQL DBMS for online analytical processing (OLAP) that uses all available system resources to their full potential to process each analytical query as fast as possible. It is available as both an open-source software and a cloud offering.

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Primary database model

Multivalue DBMS

Relational DBMS

a hierachical model (tree) can be imposed

Relational DBMS

Secondary database models

Time Series DBMS

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

Score	3.17
Rank	#94	Overall
	#1	Multivalue DBMS

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	16.34
Rank	#38	Overall
	#23	Relational DBMS

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Website

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

bigobject.io

clickhouse.com

www.esgyn.cn

Technical documentation

docs.bigobject.io

clickhouse.com/docs

Developer

Software AG

BigObject, Inc.

Clickhouse Inc.

Esgyn

Initial release

1971

2015

2016

2015

Current release

v24.4.1.2088-stable, May 2024

License

Commercial or Open Source

commercial

free community edition available

Open Source

Apache 2.0

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.

Aiven for Clickhouse: Managed cloud data warehousing with high-speed analytics.
DoubleCloud: Fully managed ClickHouse alongside best-in-class managed open-source services to build analytics at scale.
ClickHouse Cloud: Get the performance you love from open source ClickHouse in a serverless offering that takes care of the details so you can spend more time getting insight out of the fastest database on earth.

Implementation language

C++

C++, Java

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

FreeBSD
Linux
macOS

Linux

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

Close to ANSI SQL (SQL/JSON + extensions)

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

fluentd
ODBC
RESTful HTTP API

gRPC
HTTP REST
JDBC
MySQL wire protocol
ODBC
PostgreSQL wire protocol
Proprietary protocol

ADO.NET
JDBC
ODBC

Supported programming languages

Natural

3rd party library
C++
Elixir

3rd party library
Go

3rd party library
Java

3rd party library
JavaScript (Node.js)

3rd party library
Kotlin

3rd party library
Nim

3rd party library
Perl

3rd party library
PHP

3rd party library
Python

3rd party library
R

3rd party library
Ruby

3rd party library
Rust
Scala

3rd party library

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

in Natural

Lua

yes

Java Stored Procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

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

none

key based and custom

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

none

Asynchronous and synchronous physical replication; geographically distributed replicas; support for object storages.

Multi-source replication between multi datacenters

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

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 and roles. Column and row based policies. Quotas and resource limits. Pluggable authentication with LDAP and Kerberos. Password based, X.509 certificate, and SSH key authentication.

fine grained access rights according to SQL-standard

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