DBMS > Amazon Neptune vs. Badger vs. Bangdb vs. BigchainDB

System Properties Comparison Amazon Neptune vs. Badger vs. Bangdb vs. BigchainDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Fast, reliable graph database built for the cloud

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

Converged and high performance database for device data, events, time series, document and graph

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

Primary database model

Graph DBMS
RDF store

Key-value store

Document store
Graph DBMS
Time Series DBMS

Document store

Secondary database models

Spatial DBMS

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

Score	2.20
Rank	#113	Overall
	#9	Graph DBMS
	#5	RDF stores

Score	0.14
Rank	#328	Overall
	#48	Key-value stores

Score	0.07
Rank	#346	Overall
	#47	Document stores
	#35	Graph DBMS
	#32	Time Series DBMS

Score	0.76
Rank	#216	Overall
	#36	Document stores

Website

aws.amazon.com/neptune

github.com/dgraph-io/badger

bangdb.com

www.bigchaindb.com

Technical documentation

aws.amazon.com/neptune/developer-resources

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

docs.bangdb.com

bigchaindb.readthedocs.io/en/latest

Developer

Amazon

DGraph Labs

Sachin Sinha, BangDB

Initial release

2017

2012

2016

Current release

BangDB 2.0, October 2021

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

BSD 3

Open Source

AGPL v3

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C, C++

Python

Server operating systems

hosted

BSD
Linux
OS X
Solaris
Windows

Linux

Data scheme

schema-free

Typing

predefined data types such as float or date

yes

yes: string, long, double, int, geospatial, stream, events

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

secondary, composite, nested, reverse, geospatial

SQL

Support of SQL

SQL like support with command line tool

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

Proprietary protocol
RESTful HTTP API

CLI Client
RESTful HTTP API

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

C
C#
C++
Java
Python

Go
Haskell
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

Triggers

yes, Notifications (with Streaming only)

Partitioning methods

Methods for storing different data on different nodes

none

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances.

none

selectable replication factor, Knob for CAP (enterprise version only)

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Tunable consistency, set CAP knob accordingly

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes

with encyption-at-rest

yes

yes, implements WAL (Write ahead log) as well

yes,with MongoDB ord RethinkDB

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes, run db with in-memory only mode

User concepts

Access control

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

yes (enterprise version only)

yes

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

How Amazon stores deliver trustworthy shopping and seller experiences using Amazon Neptune
18 September 2024, AWS Blog

Hydrating the Natural History Museum’s Planetary Knowledge Base with Amazon Neptune and Open Data on AWS
13 September 2024, AWS Blog

How Prisma Cloud built Infinity Graph using Amazon Neptune and Amazon OpenSearch Service
27 August 2024, AWS Blog

Amazon Neptune Analytics now supports openCypher queries over RDF Graphs
13 August 2024, AWS Blog

Using knowledge graphs to build GraphRAG applications with Amazon Bedrock and Amazon Neptune
1 August 2024, AWS Blog

provided by Google News

Dgraph raises $11.5 million for scalable graph database solutions
31 July 2019, VentureBeat

provided by Google News

Using BigchainDB: A Database with Blockchain Characteristics
20 January 2022, Open Source For You

7 blockchain firms join Bosch led GAIA-X consortium for vehicle identity
13 September 2022, Ledger Insights

What is BigchainDB Technology & How it works and the Characteristics?
26 August 2017, Blockchain Council

How to use blockchain to build a database solution
2 March 2017, ZDNet

BigchainDB: A Popular and Powerful Database for Blockchain
9 September 2019, Open Source For You

provided by Google News

Share this page