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High performance, great support
What do you like best about the product?
Neo4j really excels at answering complex queries, which would never work in traditional SQL. Our team has also received great support from Neo, which has helped us get the most out of the technology. Whenever we want to extend functionality, it always seems possible, which has really helped our business.
What do you dislike about the product?
Our team is really happy with the Neo4j solution, no complaints.
What problems is the product solving and how is that benefiting you?
Neo4j supports our cloud solution to help businesses digitize and map supply chains. With Neo4j we can deal with very complex networks without sacrificing performance, which immediately benefits us and our customers.
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Awesome for specific needs, overkill for others
What do you like best about the product?
You could link concept between them without any constraints, it's really useful for mixing all kind of data in a hypergraph way.
Sometimes it's more natural for brain to navigate in a graph wired data network, than in a classic table-row model.
Sometimes it's more natural for brain to navigate in a graph wired data network, than in a classic table-row model.
What do you dislike about the product?
The cypher language is a double side knife tool, it could be powerful but also a pain.
What problems is the product solving and how is that benefiting you?
Threat intelligence.
Recommendations to others considering the product:
If you need to merge data from different sources but with common "bridges" between data communities you could use Neo4j. We have coupled it with ElasticSearch for historical and indexing features.
Great data store. Very use case specific. Not recommended for users not operating at scale.
What do you like best about the product?
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
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 about the product?
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.
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.
What problems is the product solving and how is that benefiting you?
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.
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.
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.
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.
Forward thinking product alas not always practical.
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.
The future of databases is already here and it's a Graph database!
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.
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.
Graphs are everywhere - implement using Neo4j
What do you like best about the product?
Easy data modeling and installation and really awesome easy data import (Load CSV).
Good data visualization.
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.
Many to many relationship is resolved with ease.
NEO4J graphs database FTW
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.
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.
Graph analysis with Neo4J
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).
Very interesting library with good support
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.
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.
Using Neo4j for development of a new database system
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.
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