DBMS > Badger vs. BigchainDB vs. RDF4J vs. Vitess

System Properties Comparison Badger vs. BigchainDB vs. RDF4J vs. Vitess

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Editorial information provided by DB-Engines

Name

Description

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

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Scalable, distributed, cloud-native DBMS, extending MySQL

Primary database model

Secondary database models

Document store
Spatial DBMS

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

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

Score	0.79
Rank	#212	Overall
	#36	Document stores

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Score	0.82
Rank	#209	Overall
	#97	Relational DBMS

Website

github.com/dgraph-io/badger

www.bigchaindb.com

rdf4j.org

vitess.io

Technical documentation

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

bigchaindb.readthedocs.io/en/latest

rdf4j.org/documentation

vitess.io/docs

Developer

DGraph Labs

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

The Linux Foundation, PlanetScale

Initial release

2017

2016

2004

2013

Current release

15.0.2, December 2022

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

AGPL v3

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

Apache Version 2.0, commercial licenses available

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

Python

Java

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux

Linux
OS X
Unix
Windows

Docker
Linux
macOS

Data scheme

schema-free

yes

RDF Schemas

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

with proprietary extensions

APIs and other access methods

CLI Client
RESTful HTTP API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

Go
Haskell
Java
JavaScript
Python
Ruby

Java
PHP
Python

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

Isolation support depends on the API used

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

Durability

Support for making data persistent

yes

yes,with MongoDB ord RethinkDB

yes

in-memory storage is supported as well

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

yes

Users with fine-grained authorization concept

no user groups or roles

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More resources

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