DBMS > InterSystems Caché vs. Neo4j vs. Oracle Coherence

System Properties Comparison InterSystems Caché vs. Neo4j vs. Oracle Coherence

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Editorial information provided by DB-Engines

Name

Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.

Description

A multi-model DBMS and application server

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

Oracles in-memory data grid solution

Primary database model

Key-value store
Object oriented DBMS
Relational DBMS

Graph DBMS

Key-value store

Secondary database models

Document store

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

Score	46.15
Rank	#20	Overall
	#1	Graph DBMS

Score	1.66
Rank	#132	Overall
	#22	Key-value stores

Website

www.intersystems.com/products/cache

neo4j.com

www.oracle.com/java/coherence

Technical documentation

docs.intersystems.com

neo4j.com/docs

docs.oracle.com/en/middleware/standalone/coherence

Developer

InterSystems

Neo4j, Inc.

Oracle

Initial release

1997

2007

Current release

2018.1.4, May 2020

5.23, August 2024

14.1, August 2023

License

Commercial or Open Source

commercial

Open Source

GPL version3, commercial licenses available

commercial

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.

Implementation language

Java, Scala

Java

Server operating systems

AIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows

Linux

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

All OS with a Java VM

Data scheme

depending on used data model

schema-free and schema-optional

schema-free

Typing

predefined data types such as float or date

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.

yes

Secondary indexes

yes

pluggable indexing subsystem, by default Apache Lucene

SQL

Support of SQL

yes

APIs and other access methods

.NET Client API
JDBC
ODBC
RESTful HTTP API

Bolt protocol
Cypher query language
Java API
Neo4j-OGM

Object Graph Mapper
RESTful HTTP API
Spring Data Neo4j
TinkerPop 3

JCache
JPA
RESTful HTTP API

Supported programming languages

C#
C++
Java

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

.Net
C++
Java

Server-side scripts

Stored procedures

yes

User defined Procedures and Functions

Triggers

yes

via event handler

yes

Live Events

Partitioning methods

Methods for storing different data on different nodes

none

yes using Neo4j Fabric

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Causal Clustering using Raft protocol

available in in Enterprise Version only

yes, with selectable consistency level

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

ACID

configurable

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optionally

In-memory capabilities

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

yes

User concepts

Access control

Access rights for users, groups and roles

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

authentification to access the cache via certificates or http basic authentication

More information provided by the system vendor

News

This Week in Neo4j: Knowledge Graph, Deepseek, Bloodhound, RAG and more
15 March 2025

Graph Database vs. Relational Database: What’s The Difference?
13 March 2025

How to Build a Knowledge Graph in 7 Steps
12 March 2025

Function Calling in Agentic Workflows
12 March 2025

Automate Start and Stop of Neo4j AuraDB Instances Using GitHub Actions
11 March 2025

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More resources

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2 March 2016, Paul Andlinger

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22 December 2015, Emil Eifrem (guest author)

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