DBMS > Bangdb vs. Couchbase vs. Dgraph vs. Neo4j

System Properties Comparison Bangdb vs. Couchbase vs. Dgraph vs. Neo4j

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Editorial information provided by DB-Engines

Name

Description

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

A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database

Distributed and scalable native Graph DBMS

Scalable, ACID-compliant graph database designed with a high-performance distributed cluster architecture, available in self-hosted and cloud offerings

Primary database model

Document store
Graph DBMS
Time Series DBMS

Document store

Graph DBMS

Secondary database models

Spatial DBMS

Key-value store

originating from the former Membase product and supporting the Memcached protocol
Spatial DBMS

using the Geocouch extension
Search engine
Time Series DBMS
Vector DBMS

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

Score	0.08
Rank	#347	Overall
	#47	Document stores
	#34	Graph DBMS
	#31	Time Series DBMS

Score	17.30
Rank	#36	Overall
	#5	Document stores

Score	1.45
Rank	#156	Overall
	#15	Graph DBMS

Score	44.46
Rank	#23	Overall
	#1	Graph DBMS

Website

Technical documentation

Developer

Sachin Sinha, BangDB

Couchbase, Inc.

Dgraph Labs, Inc.

Neo4j, Inc.

Initial release

2012

2011

2016

2007

Current release

BangDB 2.0, October 2021

Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023

5.19, April 2024

License

Commercial or Open Source

Open Source

BSD 3

Open Source

Business Source License (BSL 1.1); Commercial licenses also available

Open Source

Apache 2.0

Open Source

GPL version3, 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.

Neo4j Aura: Neo4j’s fully managed cloud service: The zero-admin, always-on graph database for cloud developers.

Implementation language

C, C++

C, C++, Go and Erlang

Java, Scala

Server operating systems

Linux

Linux
OS X
Windows

Linux

Can also be used server-less as embedded Java database.
OS X
Solaris
Windows

Data scheme

schema-free

schema-free and schema-optional

Typing

predefined data types such as float or date

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

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

secondary, composite, nested, reverse, geospatial

yes

pluggable indexing subsystem, by default Apache Lucene

SQL

Support of SQL

SQL like support with command line tool

SQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases

APIs and other access methods

Proprietary protocol
RESTful HTTP API

CLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

Bolt protocol
Cypher query language
Java API
Neo4j-OGM

Object Graph Mapper
RESTful HTTP API
Spring Data Neo4j
TinkerPop 3

Supported programming languages

C
C#
C++
Java
Python

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

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

.Net
Clojure
Elixir
Go
Groovy
Haskell
Java
JavaScript
Perl
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

Functions and timers in JavaScript and UDFs in Java, Python, SQL++

yes

User defined Procedures and Functions

Triggers

yes, Notifications (with Streaming only)

yes

via the TAP protocol

yes

via event handler

Partitioning methods

Methods for storing different data on different nodes

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

Automatic Sharding

yes

yes using Neo4j Fabric

Replication methods

Methods for redundantly storing data on multiple nodes

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

Multi-source replication

including cross data center replication
Source-replica replication

Synchronous replication via Raft

Causal Clustering using Raft protocol

available in in Enterprise Version only

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Immediate Consistency

Causal and Eventual Consistency configurable in Causal Cluster setup
Immediate Consistency in stand-alone mode

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, optimistic concurrency control

yes

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

yes

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

yes

Ephemeral buckets

User concepts

Access control

yes (enterprise version only)

User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control.

Planned for future releases

Users, roles and permissions. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos)

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Market metrics

Neo4j boasts the world's largest graph database ecosystem with more than 140 million...
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Licensing and pricing models

GPL v3 license that can be used all the places where you might use MySQL. Neo4j Commercial...
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News

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