What do you like best about the product?

RDBMS are now the de-facto industry standard and they shine in calculations through BIG arrays of data packed into rectangular tables (consider mega- hyper-Excel on steroids). But neither real world nor business logic is rectangular by their nature. The World consists of flexible structures like lists, like trees (be it a plant, or organisational structure, or tree of possible decisions), like networks and lace, or - what a horror! - like fractals. RDBMS, with its tabular rectangular nature, is able to emulate these with its tables - but it requires deep and complex programmatical magic, which also involve complexity, computational and human resources, and... software errors.

Being a native graph database, Neo4j allows you to reflect complex real-world graph structures of entities and their relationships in an easy and natural way, close to 1:1 mapping - and thus, avoid bulky emulation of ethereal spiderweb structures with heavy rectangular bricks made of SQL. This allows you to make your systems faster, more responsive and smarter - because they reflect the reality better. Also, graph data model is much agiler than relational and tolerates many real-world conditions which RDBMS can not.

Using Neo4j since 2013 I confirm all the above myself. It is perfectly suitable for being a kernel for enterprise Master Data Management, integrating different business systems around it. Neo4j is perfectly suitable for modern microservice architectures of enterprise solutions, this technology is also native to it.

And the price-performance ratio is impressive. Neo4j is very, very fast, and (with Enterprise license) it smoothly scales horizontally (you also get HA as a bonus). Databases scaling a billion of nodes and several billions of relationships are perfectly realizable (I personally have used a database of about 200 million nodes and Neo4j scale extremely well - it's performance does not depend on the size of the database, only diameter of the graph really matters).

What captivated me the most is how easy and natural graph technology allows you model complex realities and discover non-obvious interconnections and relationships between the entities, together with hidden patterns of facts. OLAP cubes too are graph structures. after all.

Technology is new - but the learning curve is not too steep, as soon as you catch up with this new, different graph attitude. Also online support from the community and directly from Neo4j team members makes learning Neo4j a fascinating and pleasant experience.

What do you dislike about the product?

Neo4j is industrial grade, commercial quality product. But it is at the stage of rapid development just now, upcoming version 3.0.0 promises new features and performance boosts. Also the graph query language - Cypher - is under extensive development, new "sugar" is being added to it together with performance enhancements. So it may be hard to choose which version to take for you project - more mature with fewer features, or the newest and powerful, but not proven bullet-proof yet?

Anyway, I can not call it a disadvantage, you just need to think two steps ahead, not one.

What problems is the product solving and how is that benefiting you?

In my projects, Neo4j was used as a master storage for business data migrated from legacy inherited systems, including CRM data, product catalog, provisioning, and billing. Observed benefits were:
- Neo4j allows easy data model reengineering, which brings new business value to inherited datasets, and gives abilities to interrelate previously isolated chunks of data,
- makes software development faster and easier - it eliminates the so-called Object-Relation Impedance which is typical to systems where RDBMS acts as a persistent storage of complex business data objects. Bulky and unwieldy and cumbersome Object-Relational-Mapping (ORM) persistence software layer (which in fact does not create business value) is replaced with lightweight and natural Object-Graph-Mapping (OGM) and this and it saves a lot of man-hours of development with better business results,
- Neo4j and graph data model tolerates "dirty data" and non-critical software errors much better than RDBMS; it is perfectly suited for Agile development process when requirement changes are popping out almost daily - but with graph, these changes do not demand re-engineering of the whole data model, only isolated parts of graph are affected and you can easily avoid crashing your previous development efforts.

Recommendations to others considering the product:

You need 1-2 men who are not afraid to learn and give them some time for experiments, things will start rolling forward easily then.

What do you like best about the product?

The browser based query and admin interface, which is very intuitive to use

What do you dislike about the product?

Very little, as all the features are well documented.

What problems is the product solving and how is that benefiting you?

Building recommendation engines. The nature of graphs which is at the heart of Neo4j makes building these systems a breeze

Recommendations to others considering the product:

If you don't use it, you might not know other use cases Neo4j might help you implement

What do you like best about the product?

Neo4j provides an intuitive way to model real-world entities in a completely logical way.

What do you dislike about the product?

Given that it's still a fairly new database, community support is a little sparse.

What problems is the product solving and how is that benefiting you?

Modeling relationships between real world entities.

Recommendations to others considering the product:

Make sure you've got a way to control access to neo4j before deployment.

What do you like best about the product?

The speed and flexibility of Neo4j are great, we used it to implement a flexible permission system, and it works great. They share a free book on their site too.

What do you dislike about the product?

No concept of a database like in relational or document databases, Neo4j handles only a single graph instance, which makes local development harder.

What problems is the product solving and how is that benefiting you?

We've implemented a flexible permission system based on roles and individual needs for users. Doing great for now, in production for 3 months, we had no issues with it.

Recommendations to others considering the product:

It's fast and stable, it's easy entry, didn't really need to use their support so I can't tell about their quality of service.

What do you like best about the product?

The inbuilt tutorials that got me started in less than 15 minutes. The Cypher language is not that hard to learn and understand as such, but a little recipe book with some real-world problem-solutions on the same could help a lot.

What do you dislike about the product?

Not many ways inbuilt, to import data from various types of formats and sources especially JSON. You have to write your own program talking to their rest api, in order to upload a dataset that you already have in more useable format i.e JSON

What problems is the product solving and how is that benefiting you?

I can't state exact business problem, but the abstract of that problem is to find suggestions based on various geographical & demographical factors for a given person, primarily about Travel. The benefits that are there with usage of this product is that, the time taken to bring up a working solution got shortened by a huge factor. We were able to test our algorithms and the output based on business requirements fairly well.

Recommendations to others considering the product:

Only use this, if you have to find interconnected relationship in your data. Though this alone might not be as useful as it can be with combination of a regular RDBMS software or a modern ODBMS. In short, it entirely depends on your requirement. This is a quick solution for an urgent need of analysing connected data

What do you like best about the product?

The easy to relate anything to anything combined with the fact that it allows modelling data as it appears in the real world. This proves to be very powerful when building websites which contain lots of interconnected and related data.

You will find that the data model and the navigation model overlap and interconnect. Creating views which are connected to other views and show related content become natural building blocks to unlock the data.

What do you dislike about the product?

There is no easy way (other than running another instance) to create a database per customer/project. It would be nice to separate graphs per account which is common in other database systems. This would allow for many websites running on the same Neo4J instance without mixing their data.

Currently the only way to do it is to run an instance per project, which can be on the same machine using different port settings but maintaining that is more a nuisance than simply maintain one instance used by multiple (logically separated) users.

What problems is the product solving and how is that benefiting you?

Creating web sites with lots of content which is all related. Building navigation and explorative interfaces becomes very easy once your data is in a graph.

Recommendations to others considering the product:

See if Cypher fits in your head, once you get the grasp of it try to model some stuff you always wanted to do but never could. Now writes some queries for that model. Be amazed and never look back if possible.

What do you like best about the product?

Great query interface. Nice graph query capabilities

What do you dislike about the product?

Some of the queries are not so trivial to perform. In some other situations I'd see performance bottlenecks.

What problems is the product solving and how is that benefiting you?

I'm building a cooperation graph for github users.

What do you like best about the product?

Neo4j is such a robust and easy NOSQL paradigm to utilize and deploy. I have been using it for bioinformatics research as a repository for protein interactions for the past 3 years. Recently, we have been creating computer generated models and storing that information into Neo4J. Also, I have been working on a system to create mini semantic models too and storing that graph information into Neo4J.

What do you dislike about the product?

Nothing really, sometimes if the environment you are deploying needs to be updated with the newest version of JAVA to run, but nothing to complicated. Our current worry is disk size and spatial distribution of the graph network, nothing to difficult to solve.

What problems is the product solving and how is that benefiting you?

Bioinformatics domain and Semantic Web domain is our current use cases. We are realizing we can create quick models and store them readily into Neo4j.

Recommendations to others considering the product:

This product can be used in a variety of domains. I have seen it being used in social media to health care. I even bet there can be a use case for the insurance industry.

What do you like best about the product?

It is a high efficiency graph database, the query language called 'cypher' is powerful. The visualization of the database (a web page) is beautiful.

What do you dislike about the product?

It is not distributed, so it will be slow when many queries come together. It has bugs, when I was an Intern at LInkedIn China, neo4j caused our service down.

What problems is the product solving and how is that benefiting you?

a social app backend service, we use neo4j to store users' information and relationships. due to the great query language 'cypher', we can query relationships between users on neo4j. If we use other no-graph database, those queries will be hard to resolve.

Recommendations to others considering the product:

great database to solve graph queries

What do you like best about the product?

Whenever we begin a project we usually think about the relationships between all the various actors. We draw them on the white board. With Neo4j it's really easy to translate that mental model directly into a database schema.

What do you dislike about the product?

The tooling itself was an issue. We used the neo4j ruby bindings to create an embedded neo4j database in rails. This required us to use jruby instead of regular ruby. Using jruby created a lot of other issues with compatibility with the various gems out there that we needed to use. Also there was a lot of uncertainty about licensing which was a business concern. Just by using it were we in the clear or did we have to pay out if we were commercial? It was a headache the legal department did not want to deal with.

What problems is the product solving and how is that benefiting you?

We were creating a new kind of generalizable recommendation engine. We were able to prototype new search algorithms quickly.