DBMS > Atos Standard Common Repository vs. Databend vs. FatDB vs. JaguarDB

System Properties Comparison Atos Standard Common Repository vs. Databend vs. FatDB vs. JaguarDB

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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.

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Description

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

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

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

Performant, highly scalable DBMS for AI and IoT applications

Primary database model

Document store
Key-value store

Relational DBMS

Document store
Key-value store

Key-value store
Vector DBMS

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

Score	0.28
Rank	#287	Overall
	#131	Relational DBMS

Score	0.00
Rank	#385	Overall
	#61	Key-value stores
	#16	Vector DBMS

Website

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

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

www.jaguardb.com

Technical documentation

docs.databend.com

www.jaguardb.com/support.html

Developer

Atos Convergence Creators

Databend Labs

FatCloud

DataJaguar, Inc.

Initial release

2016

2021

2012

2015

Current release

1703

1.0.59, April 2023

3.3 July 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

Open Source

GPL V3.0

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

Rust

C++

the server part. Clients available in other languages

Server operating systems

Linux

hosted
Linux
macOS

Windows

Linux

Data scheme

Schema and schema-less with LDAP views

yes

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

Via inetgration in SQL Server

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

APIs and other access methods

LDAP

CLI Client
JDBC
RESTful HTTP API

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

JDBC
ODBC

Supported programming languages

All languages with LDAP bindings

Go
Java
JavaScript (Node.js)
Python
Rust

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

yes

via applications

Triggers

yes

via applications

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

selectable replication factor

Multi-source replication

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

Immediate Consistency

Eventual Consistency
Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Atomic execution of specific operations

yes

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

Can implement custom security layer via applications

rights management via user accounts

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