DBMS > Adabas vs. Amazon Redshift vs. ClickHouse vs. EventStoreDB vs. Google Cloud Bigtable

System Properties Comparison Adabas vs. Amazon Redshift vs. ClickHouse vs. EventStoreDB vs. Google Cloud Bigtable

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

Large scale data warehouse service for use with business intelligence tools

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.

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

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

Primary database model

Multivalue DBMS

Relational DBMS

Event Store

Key-value store
Wide column store

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	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	16.34
Rank	#38	Overall
	#23	Relational DBMS

Score	1.10
Rank	#179	Overall
	#1	Event Stores

Score	3.26
Rank	#92	Overall
	#13	Key-value stores
	#8	Wide column stores

Website

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

aws.amazon.com/redshift

clickhouse.com

www.eventstore.com

cloud.google.com/bigtable

Technical documentation

docs.aws.amazon.com/redshift

clickhouse.com/docs

developers.eventstore.com

cloud.google.com/bigtable/docs

Developer

Software AG

Amazon (based on PostgreSQL)

Clickhouse Inc.

Event Store Limited

Google

Initial release

1971

2012

2016

2012

2015

Current release

v24.4.1.2088-stable, May 2024

21.2, February 2021

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

DoubleCloud: Fully managed ClickHouse alongside best-in-class managed open-source services to build analytics at scale.
Aiven for Clickhouse: Managed cloud data warehousing with high-speed analytics.
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++

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

hosted

FreeBSD
Linux
macOS

Linux
Windows

hosted

Data scheme

yes

schema-free

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

restricted

yes

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

yes

does not fully support an SQL-standard

Close to ANSI SQL (SQL/JSON + extensions)

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

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

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

Supported programming languages

Natural

All languages supporting JDBC/ODBC

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

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

Server-side scripts

Stored procedures

in Natural

user defined functions

in Python

yes

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

key based and custom

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

yes

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

Internal replication in Colossus, and regional replication between two clusters in different zones

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

Transaction concepts

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

ACID

Atomic single-row operations

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)

fine grained access rights according to SQL-standard

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.

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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