Neo4j

(32)
4.5 out of 5 stars

Neo4 is a graph database, that brings data relationships to the fore. From companies offering personalized product and service recommendations; to websites adding social capabilities; to telcos diagnosing network issues; to enterprises reimagining master data, identity, and access models; organizations adopt graph databases as the best way to model, store and query both data and its relationships.

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Neo4j review by <span>Matthew H.</span>
Matthew H.
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Best database for managing relationships

What do you like best?

The Neo4j database is very easy to learn. There isn't even a need to understand relational databases. Neo4j is easy to teach people and easy to manage.

What do you dislike?

Neo4j is getting better in terms of storing more objects and more properties, but right now I find it a little difficult to manage object properties.

Recommendations to others considering the product

If you are looking for a graph database to manage relationships this is the graph database to go with.

What business problems are you solving with the product? What benefits have you realized?

We use Neo4j for all of our relationships in our applications. We need to understand different paths and connections and the capabilities give us a very easy way to query the data. We have realized how easy it is to manage the relationships and how the data is related. We also have implemented our own algorithms for a recommendation engine.

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Neo4j review by <span>Shaik R.</span>
Shaik R.
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The best Option for Data analysis

What do you like best?

The ease of implementing it. It can hold a large amount(millions) of relational data with ease and can retrieval is fast too. Coming to the cypher query language(CQL) it is very convenient to retrieve complex data from the database even if it's highly connected data. Now with the recent releases the APOC procedures make it more simpler to control the basic DMLs and DDLs. This database is a must try for relational data.

What do you dislike?

OLTP is not that flexible if used with neo4j. As the relational data grows we started facing problems with the implementation of OLTP part with Neo4j. And it still can face problems with Super Nodes(most highly connected single node). The schema should be properly designed to hold off millions of data without ambiguity.

Recommendations to others considering the product

If you have relational data and are looking for statistical analytics the neo4j is the best solution in the market out there right now.

What business problems are you solving with the product? What benefits have you realized?

We used Neo4j for Analytics purpose. The retrieval from the cypher is fast and convenient. The best part is that it has many language drivers so implementation is very flexible. We didn't face any problem while we moved our code from one language to other to check the compatibility with the database.

What Graph Databases solution do you use?

Thanks for letting us know!
Neo4j review by <span>Shivendra S.</span>
Shivendra S.
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Great data store. Very use case specific. Not recommended for users not operating at scale.

What do you like best?

I started using Neo4J to represent various facilities ( of a startup that I work at) across the city as nodes and represent their relationships in terms of mode of commute available and the associated costs.

The brilliant thing about Neo4J, or graph DB for that matter of fact, is that it represents a graph like database as a graph and not a format manipulated to be used like a graph. This is turn makes it extremely practical for various graph based use cases like route optimization, connectivity networks etc

One more added advantage with using neo4j is the ability to use years of research done on graphs & its algorithms.

Now, what sets neo4J apart :

1) The cypher query language is very natural to write and easy to understand.

2) Allows many RDBMS like constraints to be applied to a graph.

3) The in-built query browser eliminates the use of 3rd party tools for simple graph visualizations

What do you dislike?

1) Not optimized for long traversal queries. Queries that require multiple routes inherently.

2) Very few DB drivers available, mostly are SDKs wrapped over the cypher query language (and communicates with the DB over HTTP & hence slightly slower).

3) cypher queries though simple to get started with, quickly turns into a complicated one due to very few methods.

Recommendations to others considering the product

Just one : It doesn't scale with multiple cores if you are using the community edition.

So before using it in a production environment make sure that the community edition would meet your scale, as the enterprise edition is pretty steeply priced.

What business problems are you solving with the product? What benefits have you realized?

We were trying to create a graph of various facilities and depots with weighted routes. What we essentially wanted to do was find the cheapest route from one facility to another ( via multiple hops)

Benefits of using neo4j are pretty obvious for us, we have created a graph and neo4j is a graph db, so there can not be a more natural fit for our usecase.

Neo4j review by <span>Petr B.</span>
Petr B.
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Forward thinking product alas not always practical.

What do you like best?

Property graph model is great as it is isomorphic to datastructures (knowledge graphs) that we model which lets us avoid writing much glue code and awful joins. I very much like the query language for its flexibility and of course the web interface is super useful for exploration.

What do you dislike?

I wish there was some room for hybrid representation - like in document-based dbs. In some cases, the fact that it's a connected graph rather than a collection of ad-hoc rows, triples or whatever puts additional responsibility in certain fairly basic use cases.

Recommendations to others considering the product

I've seen an earlier version few years back and witnessed witnessed how it matured, especially the UI. But be wary that it might not work in plain old object serialization use-cases (although I know there is a great object persistence framework for Neo - NeoModel). It should be great for exploratory applications like social network analysis but at the same time it would accommodate something more profound like SPARQL-style content.

What business problems are you solving with the product? What benefits have you realized?

Knowledge representation and cognitive memory modeling for natural language understanding / artificial intelligence.

Neo4j review by <span>Michael S.</span>
Michael S.
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Great for prototyping.

What do you like best?

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?

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 business problems are you solving with the product? What benefits have you realized?

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

Neo4j review by <span>Nikhil K.</span>
Nikhil K.
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Verified Current User
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Very interesting library with good support

What do you like best?

The dashboard interface is really nice. Really user friendly to write Cypher queries to retrieve graph subsets. The graph is also made interactive and this helps easy presentation.

What do you dislike?

There could be more flexible implementations of algorithms in the library. This is possible, but usually with the loss of readability.

Recommendations to others considering the product

Just play around with the interface, the bouncing nodes and relationships. This is the easiest way to get familiar with Cypher.

Understand graph algorithms before attempting to use the built in methods in neo4j. This will save a lot of time as it is difficult to map the interfaces with the familiar algorithms.

What business problems are you solving with the product? What benefits have you realized?

I was trying to compare two huge xml files. Initially I tried a DOM parser. But comparing files of the size >1GB eats up my memory and would never work. I did not want to introduce the overhead of a relational database. Using neo4j, I was able to create a library which transforms an xml to a graph in neo4j. This helps traversal and retrieval

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