DBMS > Badger vs. FatDB vs. JaguarDB

System Properties Comparison Badger vs. FatDB vs. JaguarDB

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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

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

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

Performant, highly scalable DBMS for AI and IoT applications

Primary database model

Key-value store

Document store
Key-value store

Key-value store
Vector DBMS

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

Score	0.14
Rank	#331	Overall
	#49	Key-value stores

Score	0.00
Rank	#383	Overall
	#60	Key-value stores
	#13	Vector DBMS

Website

github.com/dgraph-io/badger

www.jaguardb.com

Technical documentation

godoc.org/github.com/dgraph-io/badger

www.jaguardb.com/support.html

Developer

DGraph Labs

FatCloud

DataJaguar, Inc.

Initial release

2017

2012

2015

Current release

3.3 July 2023

License

Commercial or Open Source

Open Source

Apache 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

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Implementation language

C++

the server part. Clients available in other languages

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Windows

Linux

Data scheme

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

Via inetgration in SQL Server

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

APIs and other access methods

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

JDBC
ODBC

Supported programming languages

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

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

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

none

Eventual Consistency
Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

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.

User concepts

Access control

Can implement custom security layer via applications

rights management via user accounts

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