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# System prepended metadata

title: Neo4j Enterprise

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# Neo4j Enterprise
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## Overview

In this section we have examined Causal Clustering at a high level from an operational and an application development point of view. We now understand that the Core Servers are responsible for the long-term safekeeping of data while the more numerous Read Replicas are responsible for scaling out graph query workloads. Reasoning about this powerful architecture is greatly simplified by the Neo4j drivers which abstract the cluster topology to easily provide read levels like causal consistency.

## Pay to features

Neo4j’s Causal Clustering provides three main features:

**Safety**: Core Servers provide a fault tolerant platform for transaction processing which will remain available while a simple majority of those Core Servers are functioning.

**Scale**: Read Replicas provide a massively scalable platform for graph queries that enables very large graph workloads to be executed in a widely distributed topology.

**Causal consistency**: when invoked, a client application is guaranteed to read at least its own writes.

|![](https://i.imgur.com/s5HEIlK.png)|
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|Figure 1. Causal Cluster Architecture|

## Pricing

https://neo4j.com/pricing/

## Refer

- https://neo4j.com/licensing/
- https://neo4j.com/docs/operations-manual/current/clustering/introduction/#causal-clustering-introduction