What do you like best about the product?

In Neo4J, the various interactions between nodes are very effective in large databases. Processes are special keys that can be introduced into Neo4J to allow specific software requests or integration with Java operations. Also, UI client credentials restricted access enables for nicely controlled access. Neo4J is really helpful when it comes to solving the Cypher scripting language's limitations.

What do you dislike about the product?

Even the graphical display of the less advanced data set is nice, but it is not nice for a complex information set with over ten probable relationship charts. Also, you must use Neo4J native API, as it does not cooperate with any other open source APIs. I would specially like it to be integrate with BluePrint.

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

Neo4J is a good choice for us to examine and create a relationship modules. It allows us to build large multi-property objects, consume them at competitive prices, scan for the map and display results quickly enough for you to actually operate the site from them. As the software is entirely materialized, both joints are assembled in frequent time, which significantly improves database quality without requiring additional software development.

Recommendations to others considering the product:

Neo4J is suitable for companies where matching information patterns is important and when data scanning constantly required. The use of Neo4J facilitates effective information processing and the capacity to search using Cypher. However, Neo4J is probably not really the most effective solution if you have deep requirements to search for individual nodes and their related data.

What do you like best about the product?

Neo4J is a very fast software. It offers support for REST API, which allows for a simpler and quicker communication with Neo4J. Also, it offers a fantastic free version for the community that works with small projects. In general, Neo4J offers a wonderful user experience for every kind of data study you perform.

What do you dislike about the product?

The aggregation request needs a better support, as right now it is deficient. To be honest, I think most of the Neo4J issues comes with the support, so the solution would be to improve it. Also, I think Sandboxing should be easier too, as the process is unnecessarily complicated. If you work with a JSON data framework, it can not be changed into a graph.

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

Neo4J introduces the foundation for our web host to collate supply chains of businesses. It is used by the development team of our IT department, but it benefits the entire company, as it allows us to speed up our business growth. Neo4J also involves more than a dozen node-to-node connections, which makes it perfect to be our primary software server.

Recommendations to others considering the product:

Neo4J is very good for POC and research purposes, even for very active querying language for database information in certain large databases. It is a good alternative option, as it's a challenging and expensive process to design this sort of information with a conventional SQL database. However, this is less ideal for any data structure different to graphs.

What do you like best about the product?

Neo4j has a very straightforward and simple to use Cypher language. This Cypher is quite good if pattern matches on the introduction of interesting ideas. It makes us replicate our thoughts even better, because the way we think of information is a very simple, with just nodes and connections and Neo4j helps us to show it exactly how it is. Also, Spark controls are used to do ML or more computer work, and you can boost file backups.

What do you dislike about the product?

The language framework support currently is only available on Java libraries. I would like to see more variety on this field.

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

We use Neo4j to build our information map as a database system with no schema. We wanted a solution that could manage highly complicated queries without sacrificing quality, and Neo4j actually tackles these challenges. I evaluated it and compared it with similar usage cases and found that Neo4j performance was what we needed. The system was built to assign a node or an edge for each bit of information, so we did not have to use some kind of link server or any database without SQL.

Recommendations to others considering the product:

Neo4j is very useful for every enterprise concerned with complex and intertwined information. Also, it is suitable if you have your information represented as a graph, in nodes or edges, and if your network attributes are of concern to you. Nonetheless, it's not a good option if you need to work with a large, complex data collection.

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).

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.

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.

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?

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