DBMS > Atos Standard Common Repository vs. Cloudflare Workers KV vs. RethinkDB vs. Riak TS

System Properties Comparison Atos Standard Common Repository vs. Cloudflare Workers KV vs. RethinkDB 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 global, low-latency, key-value store for applications on Cloudflare with exceptionally high read volumes and low-latency.

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

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

Key-value store

Document store

Time Series DBMS

Secondary database models

Spatial DBMS

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

Score	0.29
Rank	#283	Overall
	#40	Key-value stores

Score	2.58
Rank	#105	Overall
	#20	Document stores

Score	0.17
Rank	#318	Overall
	#27	Time Series DBMS

Website

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

www.cloudflare.com/developer-platform/workers-kv

rethinkdb.com

Technical documentation

developers.cloudflare.com/kv/api

rethinkdb.com/docs

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

Developer

Atos Convergence Creators

Cloudflare

The Linux Foundation

since July 2017

Open Source, formerly Basho Technologies

Initial release

2016

2018

2009

2015

Current release

1703

2.4.1, August 2020

3.0.0, September 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

Open Source

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

Java

C++

Erlang

Server operating systems

Linux

hosted

Linux
OS X
Windows

Linux
OS X

Data scheme

Schema and schema-less with LDAP views

schema-free

Typing

predefined data types such as float or date

optional

yes

string, binary, float, bool, date, geometry

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

restricted

SQL

Support of SQL

yes, limited

APIs and other access methods

LDAP

HTTP REST
Proprietary protocol

HTTP API
Native Erlang Interface

Supported programming languages

All languages with LDAP bindings

C
C++
Dart
JavaScript
Kotlin
Python
Rust
Scala

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

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

Erlang

Triggers

yes

Client-side triggers through changefeeds

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding

range based

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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 single-document operations

Concurrency

Support for concurrent manipulation of data

yes

MVCC based

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

yes

users and table-level permissions

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More resources

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