DBMS > Atos Standard Common Repository vs. Cloudflare Workers KV vs. Databend vs. Trafodion

System Properties Comparison Atos Standard Common Repository vs. Cloudflare Workers KV vs. Databend vs. Trafodion

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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.

Apache Trafodion has been retired in 2021. Therefore it is excluded 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.

An open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexity

Transactional SQL-on-Hadoop DBMS

Primary database model

Document store
Key-value store

Key-value store

Relational DBMS

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

Score	0.39
Rank	#274	Overall
	#39	Key-value stores

Score	0.34
Rank	#283	Overall
	#130	Relational DBMS

Website

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

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

github.com/datafuselabs/databend
www.databend.com

trafodion.apache.org

Technical documentation

developers.cloudflare.com/kv/api

docs.databend.com

trafodion.apache.org/documentation.html

Developer

Atos Convergence Creators

Cloudflare

Databend Labs

Apache Software Foundation, originally developed by HP

Initial release

2016

2018

2021

2014

Current release

1703

1.0.59, April 2023

2.3.0, February 2019

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

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

Java

Rust

C++, Java

Server operating systems

Linux

hosted

hosted
Linux
macOS

Linux

Data scheme

Schema and schema-less with LDAP views

schema-free

yes

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

SQL

Support of SQL

yes

APIs and other access methods

LDAP

HTTP REST
Proprietary protocol

CLI Client
JDBC
RESTful HTTP API

ADO.NET
JDBC
ODBC

Supported programming languages

All languages with LDAP bindings

C
C++
Dart
JavaScript
Kotlin
Python
Rust
Scala

Go
Java
JavaScript (Node.js)
Python
Rust

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

Java Stored Procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic execution of specific operations

yes

ACID

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

LDAP bind authentication

Users with fine-grained authorization concept, user roles

fine grained access rights according to SQL-standard

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