DBMS > Atos Standard Common Repository vs. CouchDB vs. GreptimeDB vs. Riak TS

System Properties Comparison Atos Standard Common Repository vs. CouchDB vs. GreptimeDB vs. Riak TS

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Editorial information provided by DB-Engines

Name

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

Description

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

A native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.

An open source Time Series DBMS built for increased scalability, high performance and efficiency

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

Primary database model

Document store
Key-value store

Document store

Time Series DBMS

Secondary database models

Spatial DBMS

using the Geocouch extension

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

Score	7.46
Rank	#51	Overall
	#7	Document stores

Score	0.09
Rank	#343	Overall
	#31	Time Series DBMS

Score	0.17
Rank	#318	Overall
	#27	Time Series DBMS

Website

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

couchdb.apache.org

greptime.com

Technical documentation

docs.couchdb.org/en/stable

docs.greptime.com

www.tiot.jp/riak-docs/riak/ts/latest

Developer

Atos Convergence Creators

Apache Software Foundation

Apache top-level project, originally developed by Damien Katz, a former Lotus Notes developer

Greptime Inc.

Open Source, formerly Basho Technologies

Initial release

2016

2005

2022

2015

Current release

1703

3.3.3, December 2023

3.0.0, September 2022

License

Commercial or Open Source

commercial

Open Source

Apache version 2

Open Source

Apache Version 2.0

Open Source

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Erlang

Rust

Erlang

Server operating systems

Linux

Android
BSD
Linux
OS X
Solaris
Windows

Android
Docker
FreeBSD
Linux
macOS
Windows

Linux
OS X

Data scheme

Schema and schema-less with LDAP views

schema-free

schema-free, schema definition possible

schema-free

Typing

predefined data types such as float or date

optional

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

via views

yes

restricted

SQL

Support of SQL

yes

yes, limited

APIs and other access methods

LDAP

RESTful HTTP/JSON API

gRPC
HTTP API
JDBC

HTTP API
Native Erlang Interface

Supported programming languages

All languages with LDAP bindings

C
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk

C++
Erlang
Go
Java
JavaScript

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

View functions in JavaScript

Python

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding

improved architecture with release 2.0

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

links between datasets can be stored

Transaction concepts

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

Atomic execution of specific operations

atomic operations within a single document possible

Concurrency

Support for concurrent manipulation of data

yes

strategy: optimistic locking

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

LDAP bind authentication

Access rights for users can be defined per database

Simple rights management via user accounts

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Market metrics

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Licensing and pricing models

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