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126 reviews
from G2

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    Petr B.

Forward thinking product alas not always practical.

  • June 06, 2016
  • Review verified by G2

What do you like best about the product?
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 about the product?
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.
What problems is the product solving and how is that benefiting you?
Knowledge representation and cognitive memory modeling for natural language understanding / artificial intelligence.
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.


    Internet

The future of databases is already here and it's a Graph database!

  • May 08, 2016
  • Review verified by G2

What do you like best about the product?
There are a lot of things that make a graph database awesome for every day usage. On of them is the fact that previous queries that would had to join a lot of tables are very easily to make now at huge speeds. Getting friends of friends that like something that you haven't is extremely easy to do and this makes it a perfect tool for Recommendations. And not any kind of recommendations but Real-Time Recommendations. It's the perfect tool for storing huge amounts of data that are very interconnected and getting data easily out using Cypher which is a perfect tool for anyone to understand, even non-technical people.
What do you dislike about the product?
I dislike only a couple of things. The fact that there's no possibility to store object data to nodes or relationships without flattening them before and the fact that there's no native data storage integrated.
What problems is the product solving and how is that benefiting you?
Recommendations. Neo4j enables us to do Real-Time Recommendations, from basic things like, if you liked this you might also like x,y,z to getting detailed social information like what friends of friends like and do to even more complex things like computing similarity between users, bulking them into buckets and recommending things that people in your bucket liked and you haven't seen yet.

One of the other cool things is that it's Whiteboard friendly, it's extremely easy to explain the structure and how things are connected in the database to non-technical users. Also, the query language (Cyphers) makes writing queries a breeze, and not only writing queries but also reading and understanding them by just taking a look at a query.
Recommendations to others considering the product:
Definitely give it a try, especially if you have very interconnected data or a lot of social aspects (joining tables is not fun) also, if you know your app will change a lot, having the flexibility of starting with something simple and going to more complex data-sets is awesome. Finally, it's easy to understand (the concept of nodes and relationships is easy of anyone to grasp) so new programmers will be up and running in no time.


    Internet

Graphs are everywhere - implement using Neo4j

  • April 18, 2016
  • Review verified by G2

What do you like best about the product?
Easy data modeling and installation and really awesome easy data import (Load CSV).
Good data visualization.
What do you dislike about the product?
Documentation - extensive example using Java in REST mode is big time missing - at-least I did not understand how to implement.
What problems is the product solving and how is that benefiting you?
Recommendation and Discovery, Tags and Categories.
Many to many relationship is resolved with ease.


    Macy C.

NEO4J graphs database FTW

  • April 15, 2016
  • Review verified by G2

What do you like best about the product?
Great community, awesome in city meetups. The language is really simple compared to other data languages. Once you get into graphs, you need a framework that can express your thoughts easily. The neo4j graph language is fairly easy to understand and there are a LOT of toolkits available to map it to your environment. (graphs)-[:ARE]->(everywhere)
What do you dislike about the product?
I wish there was a vis tool to help learn the language. Although I said it's easy, I should have said it is the easiest. Without an instructor like at the city meetups, it is probably tough to learn it over a weekend. But WAY easier than other systems. At least you don't need to install java or some other crazy dependency. :)
What problems is the product solving and how is that benefiting you?
Graphs help define distances between relationships of entities. I was working on analysing cyber attacks to determine "strike" distance for a given attack against a given environment.
Recommendations to others considering the product:
Use neo4j, go to a city meetup.
LEARN graph concepts first. Do not try and stick RDBMS ideas and concepts or use cases into a graph.
graph is a special tool to apply node edge math. not a data store best suited for record keeping (USUALLY)
obviously your milage will very depending on your use case. But my advice to managers is to know if you have the right use case for this kind of database, e.g. distance - So if you can transform your data into a topology and your question can be phrased in a closeness / distance way, then you will be very successful.


    Mario C.

Graph analysis with Neo4J

  • April 14, 2016
  • Review provided by G2

What do you like best about the product?
Neo4j is the leader in the graph databases solutions. Its initial release was in 2007 and today it must be the first solution if you want to do serious things with graphs and machine learning using very optimized algorithms. It's very polished in many features, including their web UI which is awesome. Cypher is also an awesome query language that gives "out-of-the-box" many algorithms that you'll usually have to do manually in Gremlin.
What do you dislike about the product?
Its licensing is GPL3 and their "Enterprise" edition is quite expensive. Community Edition (free) has lot less pro features than enterprise but usually you won't need them in "small" projects. Its scalability is also not specially friendly forcing you a master-slave with a load balancer. Cypher, althought very powerful, is a new query language to learn and that takes some time to master.
What problems is the product solving and how is that benefiting you?
Neo4J is specially good for rapid queries, graph analysis, sentiment analysis, prediction and to "make triangles" in general. We use it for a dependency graph and work flawlessly but we finally give a try to OrientDB to gain some know-how and make a comparison. Today we stay with Neo4j.
Recommendations to others considering the product:
The three players today are Neo4j, OrientDB and TitanDB. I would start with Neo4j as it's the one that has more tutorials and videos on internet. Then I would give a try to OrientDB after a while with Neo4j, just to know your options. Finally, if you really have a huge amount of data, try TitanDB from the beginning (deployment is complex).


    Nikhil K.

Very interesting library with good support

  • March 30, 2016
  • Review verified by G2

What do you like best about the product?
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 about the product?
There could be more flexible implementations of algorithms in the library. This is possible, but usually with the loss of readability.
What problems is the product solving and how is that benefiting you?
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
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.


    Per K.

Using Neo4j for development of a new database system

  • March 29, 2016
  • Review verified by G2

What do you like best about the product?
The well-designed concepts and implementation of Neo4j makes it easy to model the domain data I had. It also turned to be easier to develop the data model using a graph database than an SQL database,. Oftentimes, SQL database schema become brittle and hard to modify after a certain level of complexity. I did not experience this problem with Neo4j. The Cypher query language took a little time to figure out, but in the end turned out to be powerful and easy to use.
What do you dislike about the product?
With the current implementation, one Neo4j server has one and only one data space. For use cases where one has two or more distinct data domains, one would sometimes be able to use one single server for more than one data space. It is of course possible to work around this in different ways, but that is messy.
What problems is the product solving and how is that benefiting you?
I have mostly tried out Neo4j in a hobby project involving authors, books, articles, an the critique and influence relations between them. The modelling of this domain was easy, almost trivial in neo4j. This data creates very dense relationship graphs, and having to use I have sketched several other more work-related projects, but have not yet been able to spend substantial effort on them.
Recommendations to others considering the product:
If you have densely connected data, use Neo4j. If you are experimenting with different conceptual models of your data, Neo4j is easier to work with than SQL databases.


    Andrii S.

Neo4j allows native elegant graph solutions for tasks which require heavyweight & costly SQL magic

  • March 25, 2016
  • Review verified by G2

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.


    Ijem O.

Awesome graphDB engine!

  • March 23, 2016
  • Review verified by G2

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


    Computer Software

A solid graph database

  • March 16, 2016
  • Review provided by G2

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.