DBMS > Badger vs. EJDB vs. FatDB vs. HugeGraph

System Properties Comparison Badger vs. EJDB vs. FatDB vs. HugeGraph

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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.

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

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

A fast-speed and highly-scalable Graph DBMS

Primary database model

Key-value store

Document store

Document store
Key-value store

Graph DBMS

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

Score	0.20
Rank	#325	Overall
	#49	Key-value stores

Score	0.30
Rank	#294	Overall
	#44	Document stores

Score	0.15
Rank	#339	Overall
	#33	Graph DBMS

Website

github.com/dgraph-io/badger

github.com/Softmotions/ejdb

github.com/hugegraph
hugegraph.apache.org

Technical documentation

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

github.com/Softmotions/ejdb/blob/master/README.md

hugegraph.apache.org/docs

Developer

DGraph Labs

Softmotions

FatCloud

Baidu

Initial release

2017

2012

2018

Current release

0.9

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

GPLv2

commercial

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Server operating systems

BSD
Linux
OS X
Solaris
Windows

server-less

Windows

Linux
macOS
Unix

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

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

also supports composite index and range index

SQL

Support of SQL

Via inetgration in SQL Server

APIs and other access methods

in-process shared library

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

Java API
RESTful HTTP API
TinkerPop Gremlin

Supported programming languages

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

Groovy
Java
Python

Server-side scripts

Stored procedures

yes

via applications

asynchronous Gremlin script jobs

Triggers

yes

via applications

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

yes

depending on used storage backend, e.g. Cassandra and HBase

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

yes

depending on used storage backend, e.g. Cassandra and HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency
Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

yes

edges in graph

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

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

Can implement custom security layer via applications

Users, roles and permissions

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