DBMS > Adabas vs. Couchbase vs. Google BigQuery vs. KairosDB

System Properties Comparison Adabas vs. Couchbase vs. Google BigQuery vs. KairosDB

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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 distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database

Large scale data warehouse service with append-only tables

Distributed Time Series DBMS based on Cassandra or H2

Primary database model

Secondary database models

Key-value store

originating from the former Membase product and supporting the Memcached protocol
Spatial DBMS

using the Geocouch extension
Search engine
Time Series DBMS
Vector DBMS

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

Score	2.64
Rank	#104	Overall
	#1	Multivalue DBMS

Score	16.74
Rank	#33	Overall
	#5	Document stores

Score	52.67
Rank	#19	Overall
	#13	Relational DBMS

Score	0.60
Rank	#238	Overall
	#20	Time Series DBMS

Website

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

www.couchbase.com

cloud.google.com/bigquery

github.com/kairosdb/kairosdb

Technical documentation

docs.couchbase.com

cloud.google.com/bigquery/docs

kairosdb.github.io

Developer

Software AG

Couchbase, Inc.

Google

Initial release

1971

2011

2010

2013

Current release

Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023

1.2.2, November 2018

License

Commercial or Open Source

commercial

Open Source

Business Source License (BSL 1.1); Commercial licenses also available

commercial

Open Source

Apache 2.0

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.

Implementation language

C, C++, Go and Erlang

Java

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

Linux
OS X
Windows

hosted

Linux
OS X
Windows

Data scheme

yes

schema-free

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

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

SQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases

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

CLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data

RESTful HTTP/JSON API

Graphite protocol
HTTP REST
Telnet API

Supported programming languages

Natural

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

in Natural

Functions and timers in JavaScript and UDFs in Java, Python, SQL++

user defined functions

in JavaScript

Triggers

yes

via the TAP protocol

Partitioning methods

Methods for storing different data on different nodes

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

Automatic Sharding

none

Sharding

based on Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

Multi-source replication

including cross data center replication
Source-replica replication

selectable replication factor

based on Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Since BigQuery is designed for querying data

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

Ephemeral buckets

User concepts

Access control

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

User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control.

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

simple password-based access control

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