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Neo4j has proven to be a valuable tool for a wide range of applications and industries. Users appreciate its efficiency in storing and …
Starting at $65 per month
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What is Neo4j?
Neo4j is an open source embeddable graph database developed by Neo Technologies based in San Mateo, California with an office in Sweden.
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What is Neo4j?
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What Is Neo4j?
Neo4j Technical Details
| Deployment Types | On-premise, Software as a Service (SaaS), Cloud, or Web-Based |
|---|---|
| Operating Systems | Windows, Linux, Mac |
| Mobile Application | No |
Frequently Asked Questions
Neo4j is an open source embeddable graph database developed by Neo Technologies based in San Mateo, California with an office in Sweden.
Neo4j starts at $65.
The most common users of Neo4j are from Mid-sized Companies (51-1,000 employees).
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Neo4j has proven to be a valuable tool for a wide range of applications and industries. Users appreciate its efficiency in storing and retrieving data with tree relationships, making it an ideal choice as the primary database for applications. In comparison to traditional SQL databases, Neo4j outperforms in efficiently looking up nodes and their relationships. This is particularly beneficial for applications that deal with data containing multiple relationships.
One area where Neo4j excels is in persisting knowledge graphs, providing a schemaless data store that enables the discovery of relationships between entities. Its ability to improve query performance through constant-time joins and fast search and retrieval of results makes it suitable for websites that require efficient data management. Additionally, Neo4j serves as a central storage solution for managing relationships within complex datasets, offering easy data management, analysis, and reporting capabilities.
In the commercial sector, Neo4j is highly utilized to create network maps and visualize relationships between customers or end-users. This not only aids in understanding the connections between individuals but also facilitates strategic planning and decision-making. Furthermore, Neo4j's capacity to handle large databases with multiple relationships without sacrificing performance makes it an excellent choice for both research and development purposes as well as at the application level for supporting queries on extensive datasets. Overall, Neo4j's versatility and efficiency make it a powerful tool for various use cases across industries.
Fast and Efficient Performance: Many users have praised Neo4j for its extremely fast performance, allowing for quick processing of queries and efficient handling of large datasets. The software's ability to handle complex tasks without any performance issues has been highlighted by multiple reviewers.
Intuitive Query Language: Reviewers have appreciated the intuitive and easy-to-use query language, Cypher, which makes it simple to write and execute queries in Neo4j. This mature query language offers rich features and is capable of effectively handling a wide range of problems, making it a preferred choice for many users.
Flexible Integration Options: Neo4j's support for APIs in various programming languages such as Java, Python, PHP, and NodeJS has been highly valued by users. This flexibility allows for seamless integration with different systems and provides ease of use when working with external applications or services.
Scaling Challenges: Some users have found it challenging to horizontally scale Neo4j and have not been able to find a viable solution for this issue.
Limited Integration with Other APIs: Several users have mentioned that Neo4j does not integrate well with other open source APIs like Blueprint, requiring the use of its own native API instead.
Lack of Built-in Visual Tool: Many users expressed a desire for a built-in visual tool within Neo4j to view data, rather than relying on third-party tools.
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(1-4 of 4)Companies can't remove reviews or game the system. Here's why
As [we are] working in the US healthcare domain, we have to deal with large databases like UMLS. It also contains more than 12 relationships among the nodes. To analyze and build a relational module, Neo4j is good choice for us. Mostly Neo4j is used in the R&D department for analysis. But it is also in use at application level to support queries on a large dataset.
- It's very efficient on large datasets to support the multiple relations between the nodes.
- Inserting or updating any node or relation is also very easy through the UI or a script
- Provides very good graphical representation to analyse or present a dataset
- Very good interactive UI for analysis of any dataset
- Though the performance is good on a small dataset it requires a well configured server for a large dataset
- Also graphical representation for less complex dataset is good but for complex dataset in which more than 10 relation possible graphs are not good
- Also the interactive UI for a complex dataset is little bit complex
- It adds the ability to quickly load any data set with less time
- Also we are able to do a POC on different graphs very easily through a good query language; Good for less heavy applications
We used Neo4J to store data that have tree relationships. It is being used by our entire organization for various data to be stored. It addresses the problem of storing data that has multiple relationships pretty well. Storing data in Neo4J allows for a very efficient way to look up nodes and their relationships are quicker than storing similar data in traditional SQL database.
- Mature Query language, I found Cypher QL to be mature in handling all sorts of problems we throw at it. Its expressive enough to be intuitive while providing rich features for various scenarios.
- Native support for REST API, that makes interacting with Neo4J intuitive and easy.
- Support for Procedures in Java, procedures are custom code that could be added to the Neo4J to write custom querying of data. The best part about the procedures is it could be invoked using the REST API. This allows us to overcome any shortcomings from their Cypher query language.
- Nice UI and interface for executing the Query and visualizing the response.
- UI access controlled by User credentials allows for neat access controls.
- Awesome free community edition for small-scale projects.
- Support for language based libraries. Currently, Neo4J only supports Java-based libraries. We used node and found issues with documentation and support for this library. It helps if Neo4J supports libraries in popular languages.
- Support for triggers, that's one of the neat features of Postgres and other traditional SQL databases.
- Support for indexes for data lookup. Looking up multiple nodes information using Neo4J is not very efficient, it is more optimized for looking up relationships between nodes. So adding that support would be very useful.
- Very positive ROI, we moved legacy data from Oracle into Neo4J after considering query needs and the performance of the lookups increased 4x. Apart from the performance, the code is a lot concise and clean without needing to write 10 joins to look up 2 relationships.
- Neo4J's licensing model allowed us to experiment with their community edition for free, which is amazing. They provide full support for Community edition and if your data does not warrant Hot backups and Master/Slave configurations, you might as well stick to the Community edition in Prod.
- Overall, it was a very pleasant experience working with Neo4J. Would highly recommend it.
Neo4j was an experiment for us. We needed to model people and relationships for which graph databases were most suited. Google search resulted "Neo4j" on top, so we tried it, and it is awesome! The project, unfortunately, has been shut down, but at the time, we used it as the primary database for the application. The database model was designed such that every piece of information could be mapped to either a node or an edge, so we didn't need to use any sort of relational or other no-SQL database.
- Neo4j is extremely fast.
- Neo4j has its own query language CYPHER which is very intuitive and easy to use.
- Neo4j supports API in almost every language like Java, Python, PHP, NodeJS, etc.
- One of the hardest challenges that Neo4j had to solve was the horizontal scaling problem. I am not updated on recent developments, but at the time of my use, I couldn't find a viable solution.
- Neo4j does not play with other open source APIs like Blueprint. You have to use the native Neo4j API.
- There wasn't a visual tool to see your data. Of course, third party tools are always available, but I would have loved something which came with the Neo4j bundle. I love that Docker comes bundled with Kitematic, so it's not wrong to hope that Neo4j could also ship with some default visualization software.
- For experimentation purposes, it had a positive impact on my company. It was very natural to work with Neo4j and so intuitive to visualize the data.
- Neo4j community edition is free, which is what we experimented on. So there was no investment up front apart from employee's time. But this quickly gave results and it was time well spent.
- Neo4j is a cool but very new technology. It was hard to have people onboard, especially some of the leadership and relational folks.
- Titan-Distributed Graph Database
Neo4j is ahead of any of the leading competitors I know. The only one which comes close, in my opinion, is the "Titan-Distributed Graph Database" which is completely open source and free to use. Titan works on top of Apache Cassandra so it has some huge learning curves to do, whereas Neo4j is just downloaded and used. Because of this reason, I can easily see why someone would prefer Neo4j over Titan or any other graph database.
September 12, 2016
Neo4j: Connecting the dots for graph data
We use Neo4j as storage for data that can naturally be modeled as a graph (think nodes and edges). It allows us to create rich objects with multiple properties, ingest them at reasonable rates, and the search against the graph and return results fast enough that you can run a website directly off it.
It's not a general data storage solution, but for applications where you can about the graph or network nature of the data it excels.
It's not a general data storage solution, but for applications where you can about the graph or network nature of the data it excels.
- It's very easy to install.
- The built in web interface is incredibly useful. It enables you to quickly test out queries and visualize the results.
- Third-party libraries/APIs are well represented. CYPHER isn't actually that hard to write directly, either.
- It would be nice to have some concept of namespaces, or some way of roughly making a single instance multi-tenant. It'd be nice to make sandboxing easier.
- Automatic backups could be improved.
- It enables backend functionality that would essentially be impossible without it. It's also pretty easy to get up and running and demos very well.