DBMS > Adabas vs. Atos Standard Common Repository vs. Couchbase vs. HarperDB vs. SpaceTime

System Properties Comparison Adabas vs. Atos Standard Common Repository vs. Couchbase vs. HarperDB vs. SpaceTime

Editorial information provided by DB-Engines

Name

This system has been discontinued and will be removed from the DB-Engines ranking.

Description

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

used typically together with the Natural programming platform

Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks

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

Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.

SpaceTime is a spatio-temporal DBMS with a focus on performance.

Primary database model

Multivalue DBMS

Document store
Key-value store

Document store

Spatial DBMS

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

Relational DBMS

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

Score	2.79
Rank	#102	Overall
	#2	Multivalue DBMS

Score	16.59
Rank	#36	Overall
	#5	Document stores

Score	0.60
Rank	#244	Overall
	#38	Document stores

Score	0.03
Rank	#392	Overall
	#8	Spatial DBMS

Website

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

atos.net/en/convergence-creators/portfolio/standard-common-repository

www.couchbase.com

www.harperdb.io

www.mireo.com/spacetime

Technical documentation

docs.couchbase.com

docs.harperdb.io/docs

Developer

Software AG

Atos Convergence Creators

Couchbase, Inc.

HarperDB

Mireo

Initial release

1971

2016

2011

2017

2020

Current release

1703

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

3.1, August 2021

License

Commercial or Open Source

commercial

Open Source

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

commercial

free community edition available

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, C++, Go and Erlang

Node.js

C++

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

Linux

Linux
OS X
Windows

Linux
OS X

Linux

Data scheme

yes

Schema and schema-less with LDAP views

schema-free

dynamic schema

yes

Typing

predefined data types such as float or date

yes

optional

yes

JSON data types

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.

yes

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

SQL-like data manipulation statements

A subset of ANSI SQL is implemented

APIs and other access methods

HTTP API

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

with add-on software Adabas SOA Gateway

LDAP

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

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

RESTful HTTP API

Supported programming languages

Natural

All languages with LDAP bindings

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

C#
C++
Python

Server-side scripts

Stored procedures

in Natural

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

Custom Functions

since release 3.1

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

Sharding

cell division

Automatic Sharding

A table resides as a whole on one (or more) nodes in a cluster

Fixed-grid hypercubes

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

yes

Multi-source replication

including cross data center replication
Source-replica replication

yes

the nodes on which a table resides can be defined

Real-time block device replication (DRBD)

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 or Eventual Consistency depending on configuration

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Atomic execution of specific operations

ACID

Atomic execution of specific operations

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, using LMDB

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Ephemeral buckets

yes

User concepts

Access control

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

LDAP bind authentication

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

Access rights for users and roles

yes

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