DBMS > AllegroGraph vs. Couchbase vs. Neo4j vs. OpenQM vs. Redis

System Properties Comparison AllegroGraph vs. Couchbase vs. Neo4j vs. OpenQM vs. Redis

Editorial information provided by DB-Engines

Name

Description

High performance, persistent RDF store with additional support for Graph DBMS

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

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

QpenQM is a high-performance, self-tuning, multi-value DBMS

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

with version 6.5
Graph DBMS
RDF store
Vector DBMS

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

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

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	0.84
Rank	#204	Overall
	#35	Document stores
	#18	Graph DBMS
	#7	RDF stores
	#10	Vector DBMS

Score	16.74
Rank	#33	Overall
	#5	Document stores

Score	42.68
Rank	#21	Overall
	#1	Graph DBMS

Score	0.28
Rank	#291	Overall
	#10	Multivalue DBMS

Score	149.43
Rank	#6	Overall
	#1	Key-value stores

Website

allegrograph.com

www.couchbase.com

neo4j.com

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

redis.com
redis.io

Technical documentation

franz.com/agraph/support/documentation/current/agraph-introduction.html

docs.couchbase.com

neo4j.com/docs

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

Developer

Franz Inc.

Couchbase, Inc.

Neo4j, Inc.

Rocket Software, originally Martin Phillips

Redis project core team, inspired by Salvatore Sanfilippo

Development sponsored by Redis Inc.

Initial release

2004

2011

2007

1993

2009

Current release

8.0, December 2023

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

5.23, August 2024

3.4-12

7.2.5, May 2024

License

Commercial or Open Source

commercial

Limited community edition free

Open Source

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

Open Source

GPL version3, commercial licenses available

Open Source

GPLv2, extended commercial license available

Open Source

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

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++, Go and Erlang

Java, Scala

Server operating systems

Linux
OS X
Windows

Linux

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

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

BSD
Linux
OS X
Windows

ported and maintained by Microsoft Open Technologies, Inc.

Data scheme

yes

RDF schemas

schema-free

schema-free and schema-optional

yes

with some exceptions

schema-free

Typing

predefined data types such as float or date

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.

bulk load of XML files possible

yes

Secondary indexes

yes

pluggable indexing subsystem, by default Apache Lucene

yes

with RediSearch module

SQL

Support of SQL

SPARQL is used as query language

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

with RediSQL module

APIs and other access methods

RESTful HTTP API
SPARQL

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

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

C#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

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

.Net
Basic
C
Java
Objective C
PHP
Python

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

JavaScript or Common Lisp

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

yes

User defined Procedures and Functions

yes

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

Triggers

yes

via the TAP protocol

yes

via event handler

yes

publish/subscribe channels provide some trigger functionality; RedisGears

Partitioning methods

Methods for storing different data on different nodes

with Federation

Automatic Sharding

yes using Neo4j Fabric

yes

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
Source-replica replication

Multi-source replication

including cross data center replication
Source-replica replication

Causal Clustering using Raft protocol

available in in Enterprise Version only

yes

Multi-source replication

with Redis Enterprise Pack
Source-replica replication

Chained replication is supported

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

through RedisGears

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

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

Immediate Consistency

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

yes

Relationships in graphs

Transaction concepts

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

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

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

Ephemeral buckets

yes

User concepts

Access control

Users with fine-grained authorization concept, user roles and pluggable authentication

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

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

Access rights can be defined down to the item level

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

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

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Typical application scenarios

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Key customers

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