DBMS > CockroachDB vs. FatDB vs. OushuDB vs. Realm

System Properties Comparison CockroachDB vs. FatDB vs. OushuDB vs. Realm

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Editorial information provided by DB-Engines

Name

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

Description

CockroachDB is a distributed database architected for modern cloud applications. It is wire compatible with PostgreSQL and backed by a Key-Value Store, which is either RocksDB or a purpose-built derivative, called Pebble.

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

A data warehouse powered by Apache HAWQ supporting descriptive analysis and advanced machine learning

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

Primary database model

Relational DBMS

Document store
Key-value store

Relational DBMS

Document store

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

Score	6.15
Rank	#55	Overall
	#33	Relational DBMS

Score	0.04
Rank	#363	Overall
	#154	Relational DBMS

Score	7.60
Rank	#52	Overall
	#9	Document stores

Website

www.cockroachlabs.com

www.oushu.com/product/oushuDB

realm.io

Technical documentation

www.cockroachlabs.com/docs

www.oushu.com/documentation

realm.io/docs

Developer

Cockroach Labs

FatCloud

Oushu

Realm, acquired by MongoDB in May 2019

Initial release

2015

2012

2014

Current release

23.1.1, May 2023

4.0.1, August 2020

License

Commercial or Open Source

Open Source

Apache 2.0, commercial license available

commercial

Open Source

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

Server operating systems

Linux
macOS
Windows

Windows

Linux

Android
Backend: server-less
iOS
Windows

Data scheme

dynamic schema

schema-free

yes

Typing

predefined data types such as float or date

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.

Secondary indexes

yes

SQL

Support of SQL

yes, wire compatible with PostgreSQL

Via inetgration in SQL Server

Full-featured ANSI SQL support

APIs and other access methods

JDBC

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

JDBC
ODBC

Supported programming languages

C#
C++
Clojure
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust

C
C++

.Net
Java

with Android only
Objective-C
React Native
Swift

Server-side scripts

Stored procedures

yes

via applications

yes

runs within the applications so server-side scripts are unnecessary

Triggers

yes

via applications

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by key range)

all tables are translated to an ordered KV store and then broken down into 64MB ranges, which are then used as replicas in RAFT

Sharding

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using RAFT

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

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

In-Memory realm

User concepts

Access control

Role-based access control

Can implement custom security layer via applications

Kerberos, SSL and role based access

yes

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More resources

DB-Engines blog posts

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