DBMS > Google Cloud Firestore vs. MongoDB vs. Neo4j vs. Redis

System Properties Comparison Google Cloud Firestore vs. MongoDB vs. Neo4j vs. Redis

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Editorial information provided by DB-Engines

Name

Description

Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.

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

Popular in-memory data platform used as a cache, message broker, and database that can be deployed on-premises, across clouds, and hybrid environments

Redis focuses on performance so most of its design decisions prioritize high performance and very low latencies.

Primary database model

Document store

Graph DBMS

Key-value store

Multiple data types and a rich set of operations, as well as configurable data expiration, eviction and persistence

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

Document store

with RedisJSON
Graph DBMS

with RedisGraph
Spatial DBMS
Search engine

with RediSearch
Time Series DBMS

with RedisTimeSeries
Vector DBMS

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

Score	7.85
Rank	#51	Overall
	#8	Document stores

Score	421.65
Rank	#5	Overall
	#1	Document stores

Score	44.46
Rank	#23	Overall
	#1	Graph DBMS

Score	157.80
Rank	#6	Overall
	#1	Key-value stores

Website

firebase.google.com/products/firestore

www.mongodb.com

neo4j.com

redis.com
redis.io

Technical documentation

firebase.google.com/docs/firestore

www.mongodb.com/docs/manual

neo4j.com/docs

docs.redis.com/latest/index.html
redis.io/docs

Developer

Google

MongoDB, Inc

Neo4j, Inc.

Redis project core team, inspired by Salvatore Sanfilippo

Development sponsored by Redis Inc.

Initial release

2017

2009

2007

2009

Current release

6.0.7, June 2023

5.19, April 2024

7.2.4, January 2024

License

Commercial or Open Source

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

Open Source

source-available extensions (modules), commercial licenses for Redis Enterprise

Cloud-based only

Only available as a cloud service

yes

MongoDB available as DBaaS (MongoDB Atlas)

DBaaS offerings (sponsored links)

Database as a Service

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

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.

Aiven for Redis: Fully managed in-memory key-value store for all your caching and speedy lookup needs.

Implementation language

C++

Java, Scala

Server operating systems

hosted

Linux
OS X
Solaris
Windows

Linux

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

BSD
Linux
OS X
Windows

ported and maintained by Microsoft Open Technologies, Inc.

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

schema-free

Typing

predefined data types such as float or date

yes

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

yes

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

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

yes

with RediSearch module

SQL

Support of SQL

Read-only SQL queries via the MongoDB Atlas SQL Interface

with RediSQL module

APIs and other access methods

Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API

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

proprietary protocol

RESP - REdis Serialization Protocol

Supported programming languages

Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python

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#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

JavaScript

yes

User defined Procedures and Functions

Lua; Redis Functions coming in Redis 7 (slides and Github)

Triggers

yes, with Cloud Functions

yes

in MongoDB Atlas only

yes

via event handler

publish/subscribe channels provide some trigger functionality; RedisGears

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

Sharding

Automatic hash-based sharding with support for hash-tags for manual sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

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

with Redis Enterprise Pack
Source-replica replication

Chained replication is supported

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

yes

through RedisGears

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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

Eventual Consistency
Causal consistency can be enabled in Active-Active databases
Strong consistency with Redis Raft
Strong eventual consistency with Active-Active

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

yes

Relationships in graphs

Transaction concepts

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

yes

Multi-document ACID Transactions with snapshot isolation

ACID

Atomic execution of command blocks and scripts and optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

optional, enabled by default

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

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

yes

User concepts

Access control

Access rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.

Access rights for users and roles

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

Access Control Lists (ACLs): redis.io/docs/management/security/acl
LDAP and Role-Based Access Control (RBAC) for Redis Enterprise
Mutual TLS authentication: redis.io/docs/management/security/encryption
Password-based authentication

More information provided by the system vendor

Specific characteristics

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Neo4j delivers graph technology that has been battle tested for performance and scale...
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Competitive advantages

Built around the flexible document data model and unified API, MongoDB is a developer...
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Neo4j is the market leader, graph database category creator, and the most widely...
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Typical application scenarios

AI-enriched intelligent apps (Continental, Telefonica, Iron Mountain) Internet of...
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Real-Time Recommendations Master Data Management Identity and Access Management Network...
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Key customers

ADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
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Over 800 commercial customers and over 4300 startups use Neo4j. Flagship customers...
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Market metrics

Hundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month...
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Neo4j boasts the world's largest graph database ecosystem with more than 140 million...
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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

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