Neo4j AuraDB Reviews

Neo4j AuraDB is a cloud-based graph database. It’s mainly used for projects that must start small and scale up as required. The cloud interface is easy to use and requires no maintenance, making it ideal for development and client handover.

From my experience, I particularly like the professional version. Initially, developers often start with the free variant. Once the project grows, we switch to the professional version, which offers multiple databases, expanded memory, and better scalability. This allows us to handle more data and use cloud scaling features.

Think of Neo4j AuraDB as a special type of database - it's a graph database. Graph databases can be used for situations where you want to do relationship-centric modeling. If you want to identify how data points are related to each other, that's where AuraDB does really well.

Specifically, in terms of RAG and generative AI use cases, where you want to find out how close data points are to each other, AuraDB does really well. It's fast because the data is essentially a graph database with points linked to each other.

It feels like a perfect solution if your use cases involve identifying or working with relationships within the data.

Think of AuraDB as a database. For example, imagine you have textual data in the form of documents, and you want to feed that data into an existing LLM model to gain extra context. That's where you would use AuraDB.

In this use case, you would convert your textual corpus into a graph database and store it in AuraDB. This can then be fed into an existing or newly created LLM model, which will provide better insights. You can then perform analysis on your data, and your LLMs can answer questions and provide better context based on the additional data you've provided.

This is essentially RAG workflow, but it's really useful for storing extra data or storing your data efficiently.

AuraDB effectively manages complex data relationships. If there is an inherent need within your data or your use case to identify how the data is related to each other and how the individual points are related to each other, then the graph structure of the database itself is the biggest feature AuraDB provides.

It also has a query language called Cypher, which is used to query within the database, create the database, and get your use cases out.

So the key features or the key pointers are the Cypher query language, its speed, and the inherent graph structure of the database.

I was getting data from Hacker News to store it on Neo4j. I was running a cron job using Neo4j to scrape topics and comments from Hacker News every two hours. I ran that for at least a year and a half, but stopped recently. I wanted to see how stable and useful it was.

First, I liked that it was free. I also liked that you can run multiple languages with it. I can connect it to a Spring Boot app, a Python app, or a Go app. If I'm doing network correlation, graph or node analysis, I can easily connect my Google Colab to my Neo4j AuraDB account. Those are the things I like about it.

I like the idea of graphs and nodes and the possibilities Neo4j AuraDB offers.

I worked on a project focused on the quality of public menus, using Neo4j AuraDB to connect and create relationships between food items. This allowed us to visualize data in interesting ways and identify communities. A key feature was using the Green Dot to link unstructured data, such as investment information, with structured data from tables and PDFs. The AuraDB documentation was also helpful in making these connections and providing valuable insights.

The most valuable features of Neo4j AuraDB include its flexible data model and broad language support. It’s great that it offers a dedicated query language, which delivers excellent performance and high availability. Additionally, it’s hosted on AWS Cloud, which ensures reliability. The platform also allows for the integration of videos and other media.

I'm a research scholar, and I've learned cipher language for my research work. I've been using Neo4j AuraDB for that cipher language.

I'm also working on Python as a front-end language. Integrating the front-end language with Neo4j AuraDB is a very easy process. We can directly import packages and see the visualization in the Python interface. Neo4j AuraDB provides interfaces for languages other than Python, such as Java.

It is a very difficult job to show the graph schema and understand a problem using the graph technique.Neo4j AuraDB is a very convenient tool for our team because it allows access to anyone invited to a project. Others can easily access the graph data if I invite people and train the schema.

The solution's most valuable features stem from its easy connection to other modules and integrations. Understanding graphs can be a very complex concept, as there are many other combination modules in it, like LangChain, the LLM module, and the data processing module. I think there are more than four modules that heavily rely on GraphRAG's implementation, but AuraDB's role is very good because everything is very convenient for our team in the cloud and graph database systems.