DBMS > BigchainDB vs. Cloudflare Workers KV vs. MongoDB vs. Neo4j vs. Vertica

System Properties Comparison BigchainDB vs. Cloudflare Workers KV vs. MongoDB vs. Neo4j vs. Vertica

Editorial information provided by DB-Engines

Name

Description

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

A global, low-latency, key-value store for applications on Cloudflare with exceptionally high read volumes and low-latency.

One of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructure

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

Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.

Primary database model

Column oriented

Secondary database models

Spatial DBMS
Search engine

integrated Lucene index, currently in MongoDB Atlas only.
Time Series DBMS

Time Series Collections introduced in Release 5.0
Vector DBMS

currently available in the MongoDB Atlas cloud service only

Spatial DBMS
Time Series DBMS

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

Score	0.85
Rank	#208	Overall
	#35	Document stores

Score	0.39
Rank	#274	Overall
	#39	Key-value stores

Score	421.08
Rank	#5	Overall
	#1	Document stores

Score	44.89
Rank	#21	Overall
	#1	Graph DBMS

Score	10.06
Rank	#42	Overall
	#26	Relational DBMS

Website

www.bigchaindb.com

www.cloudflare.com/developer-platform/workers-kv

www.mongodb.com

neo4j.com

www.vertica.com

Technical documentation

bigchaindb.readthedocs.io/en/latest

developers.cloudflare.com/kv/api

www.mongodb.com/docs/manual

neo4j.com/docs

vertica.com/documentation

Developer

Cloudflare

MongoDB, Inc

Neo4j, Inc.

OpenText

previously Micro Focus and Hewlett Packard

Initial release

2016

2018

2009

2007

2005

Current release

6.0.7, June 2023

5.20, May 2024

12.0.3, January 2023

License

Commercial or Open Source

Open Source

AGPL v3

commercial

Open Source

MongoDB Inc.'s Server Side Public License v1. Prior versions were published under GNU AGPL v3.0. Commercial licenses are also available.

Open Source

GPL version3, commercial licenses available

commercial

Limited community edition free

Cloud-based only

Only available as a cloud service

yes

MongoDB available as DBaaS (MongoDB Atlas)

on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers

DBaaS offerings (sponsored links)

Database as a Service

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

MongoDB Flex @ STACKIT offers managed MongoDB Instances with adjustable CPU, RAM, storage amount and speed, in enterprise grade to perfectly match all application requirements. All services are 100% GDPR-compliant.
MongoDB Atlas: Global multi-cloud database with unmatched data distribution and mobility across AWS, Azure, and Google Cloud, built-in automation for resource and workload optimization, and so much more.

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

Implementation language

Python

C++

Java, Scala

C++

Server operating systems

Linux

hosted

Linux
OS X
Solaris
Windows

Linux

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

Linux

Data scheme

schema-free

Although schema-free, documents of the same collection often follow the same structure. Optionally impose all or part of a schema by defining a JSON schema.

schema-free and schema-optional

Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.

Typing

predefined data types such as float or date

yes

string, integer, double, decimal, boolean, date, object_id, geospatial

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

pluggable indexing subsystem, by default Apache Lucene

No Indexes Required. Different internal optimization strategy, but same functionality included.

SQL

Support of SQL

Read-only SQL queries via the MongoDB Atlas SQL Interface

Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.

APIs and other access methods

CLI Client
RESTful HTTP API

HTTP REST
Proprietary protocol

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

Bolt protocol
Cypher query language
Java API
Neo4j-OGM

Object Graph Mapper
RESTful HTTP API
Spring Data Neo4j
TinkerPop 3

ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL

character-based, interactive, front-end utility

Supported programming languages

Go
Haskell
Java
JavaScript
Python
Ruby

C
C++
Dart
JavaScript
Kotlin
Python
Rust
Scala

Actionscript

unofficial driver
C
C#
C++
Clojure

unofficial driver
ColdFusion

unofficial driver
D

unofficial driver
Dart

unofficial driver
Delphi

unofficial driver
Erlang
Go
Groovy

unofficial driver
Haskell
Java
JavaScript
Kotlin
Lisp

unofficial driver
Lua

unofficial driver
MatLab

unofficial driver
Perl
PHP
PowerShell

unofficial driver
Prolog

unofficial driver
Python
R

unofficial driver
Ruby
Rust
Scala
Smalltalk

unofficial driver
Swift

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

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

Server-side scripts

Stored procedures

JavaScript

yes

User defined Procedures and Functions

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes

in MongoDB Atlas only

yes

via event handler

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

Sharding

Partitioned by hashed, ranged, or zoned sharding keys. Live resharding allows users to change their shard keys as an online operation with zero downtime.

yes using Neo4j Fabric

horizontal partitioning, hierarchical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

Multi-Source deployments with MongoDB Atlas Global Clusters
Source-replica replication

Causal Clustering using Raft protocol

available in in Enterprise Version only

Multi-source replication

One, or more copies of data replicated across nodes, or object-store used for repository.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Bi-directional Spark integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

can be individually decided for each read operation
Immediate Consistency

default behaviour

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

Immediate Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

yes

Relationships in graphs

yes

Transaction concepts

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

Multi-document ACID Transactions with snapshot isolation

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes,with MongoDB ord RethinkDB

yes

optional, enabled by default

yes

In-memory capabilities

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

yes

In-memory storage engine introduced with MongoDB version 3.2

User concepts

Access control

yes

Access rights for users and roles

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

fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

More information provided by the system vendor

Specific characteristics

MongoDB provides an integrated suite of cloud database and data services to accelerate...
» more

Neo4j delivers graph technology that has been battle tested for performance and scale...
» more

Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more

Competitive advantages

Built around the flexible document data model and unified API, MongoDB is a developer...
» more

Neo4j is the market leader, graph database category creator, and the most widely...
» more

Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
» more

Typical application scenarios

AI-enriched intelligent apps (Continental, Telefonica, Iron Mountain) Internet of...
» more

Real-Time Recommendations Master Data Management Identity and Access Management Network...
» more

Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more

Key customers

ADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
» more

Over 800 commercial customers and over 4300 startups use Neo4j. Flagship customers...
» more

Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more

Market metrics

Hundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month...
» more

Neo4j boasts the world's largest graph database ecosystem with more than 140 million...
» more

Licensing and pricing models

MongoDB database server: Server-Side Public License (SSPL) . Commercial licenses...
» more

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

Cost-based models and subscription-based models are both available. One license is...
» more

News

This Week in Neo4j: Importing Data, NODES, GenAI, Going Meta and more
1 June 2024

openCypher Will Pave the Road to GQL for Cypher Implementers
22 May 2024

7 Tips for Submitting Your NODES 2024 Talk
22 May 2024

How to Configure Neo4j Aura With AWS PrivateLink
21 May 2024

This Week in Neo4j: Podcast, GraphRAG, GraphQL, Chatbot and more
18 May 2024

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.