Neo4j Graph Database Reviews

We have used Neo4j in microservices. In one of the microservices, we used Neo4j since we have some requirements similar to MongoDB plus Elasticsearch. It performs both functions. Instead of doing those two things, we use Neo4j's in-built Solr for queries, and it has MongoDB-like features. We have used these features as well and found them beneficial. 

For Neo4j, we have used it for smaller applications. I have not tested it with larger applications or big data. Our clients use it for applications with 200 to 300 customers. We have a limited database yet did not find any performance issues. 

It is good for search-based tasks, providing solid search results and aggregate results compared to MongoDB. Aggregating with MongoDB is somewhat difficult, whereas with Neo4j, it's easier. Aggregating, backing up data, and creating a new cluster are very easy from the back end. In our DevOps web deployment, we did not find any issues. We created Docker instances and set up Avaya and data configurations, handling databases up to 50 gigabytes without identifying any problems.

Neo4j helps with advanced search needs, providing good search results and aggregates compared to MongoDB. Aggregating with MongoDB can be difficult; however, with Neo4j, it's easier. Aggregating data, backing up, and creating new clusters are user-friendly from the back end. In DevOps web deployment, we noticed no database issues. We created Docker instances and set them up efficiently, managing databases up to 50 gigabytes.

The only problem is that the community is quite small. 

We started using the solution in the year 2014.

I did not find any issues with stability. For two log-related predictions, we created solutions, and they have been addressed in the latest version.

The community edition is very good for scalability. It is highly scalable.

We follow the documentation. If the community is available, we ask questions on Google for solutions. For future needs, we refer to more block messages.

Positive

In contrast, we used Cassandra for a very large database, up to five to ten terabytes, and encountered a few batch insert issues. But we did not work extensively with that amount of data on Neo4j. We have used Neo4j up to fifty gigabytes of data. In our AI project, it's working well and is helpful.

The setup and replication process is good. Both deployment and installation are smooth. We have used the community edition, which offered some great features. We did not find difficulties in setup, except for backing up, which is slightly challenging.

We have used both editions without any difficulty. In the fourth year, they provided the software, and we installed three additional community editions with no issues. Backing up required some effort. 

We rate it nine out of ten. 

We use Neo4j for AI models without production data sets, replicating data in the required format. Neo4j is excellent if you have MongoDB and Elasticsearch compatibility for caching applications.

We're building a social media platform, which is a great use case for the product. It helps connect people. For example, if we're friends on Facebook, I can get suggestions for people near me or related to you. I can see suggestions for people I might know based on our connection. This is possible because of the tool, which can use location parameters and other factors. Twitter is another good example. I follow certain hashtags and want suggestions based on them. I can group hashtags and get suggestions from them.

The solution's best feature is how it differs from traditional SQL databases. It's hard to map people and find those near me in SQL, which requires long, complex queries. Neo4j Graph Database makes this easier with simpler queries. It also supports more data types, like JSON, which SQL doesn't.

The tool could improve by having more resources, especially for Golang, which we use. It lacks good basic libraries and doesn't have an ORM (Object-Relational Mapping) tool, which many NoSQL databases have. We thought about building an ORM for the Neo4j Graph Database but are too busy.

I have been using the product for eight months. 

The solution is stable, the team is great, and they have good funding. Many big tech companies are using Neo4j Graph Database now, and I think we'll see a big market for it in the future. The main problem is the lack of people who can use it. I've had to train ten freshers because there aren't many experts.

In my previous company, about 20 people were using the Neo4j Graph Database. We were building a social media platform with multiple microservices, and all teams depended on Neo4j.

I've talked to the support team before. I seek help from the Neo4j community in Bangalore, India. We have discussions and meetups there.

The company chose Neo4j Graph Database because our platform is a social media app. We also use other databases like MongoDB for different use cases, such as authentication.

Installation, setup, and deployment of Neo4j are easy. It has good support on Google Cloud and AWS. Neo4j also offers a free cloud service called AuraDB, which is great for small startups. We've deployed the Neo4j Graph Database on both AWS and Google Cloud Platforms. However, I am not sure about its use on Azure. 

The solution is open source so that you can use it for free. They also offer an enterprise version with its billing. If your company is earning well, I suggest using the enterprise version. Otherwise, you can deploy it on your own cloud and pay based on usage.

If someone asks me whether to use Neo4j Graph Database, I'd want to know what they're building. I'd recommend it based on their use case. If it meets their needs, I'd suggest it. I recommend starting with the tool even for those exploring graph databases. It's been around since about 2010 and is better than other graph databases in many ways.

Learning the tool depends on the programming language you're using. We had some challenges with Golang due to limited library support. However, Neo4j is easier to use with Node.js, JavaScript, or Python.

Overall, I'd rate the tool eight to nine out of ten. It offers great features, scalability, and flexibility and has good documentation. It's easy to learn. However, every database has pros and cons, so the rating might change when comparing it to other graph databases.

For now, my company is building a knowledge graph for a client. I don't know if you have heard about GraphRAG by Microsoft, for which I am using Neo4j Graph Database. We are building a big knowledge graph for the LLM, and that is it. We are using Neo4j Graph Database to store the knowledge graph.

The tool is easy to use for me, and it is fast for what I need. I searched for many other applications or databases with some other products, but I still prefer Neo4j Graph Database because it is a strong tool.

For now, the tool is okay. I don't know if, after some evolution in the needs of a client. I don't know yet if we have to develop something else or if Neo4j Graph Database needs to be more efficient. For now, the tool is perfectly matched to the needs of the applications.

For some people who don't know about the tool, I don't know if it will be easy for them to use it, making it an area where the tool can be improved.

I have been using Neo4j Graph Database for a year. I am just a user of the solution.

For now, the tool doesn't break down or stop, so it is quite stable.

I am working with one person to build a knowledge graph. Our company has two data scientists.

I searched for some help on a forum, and I always found a solution on Stack Overflow. Cipher is like Python, which is quite easy to write.

For me, when the tool was deployed on an on-premises model, it was a little bit difficult the first time. On the cloud, the tool's deployment was easy, and maybe it was because of the experience, too, so it was not very difficult for me.

The solution is currently deployed on the cloud. In my first project, it was deployed on an on-premises model.

The tool is not expensive.

I searched for about a month to find the best solution, but that was quite difficult for my company to dive into. Neo4j Graph Database meets the needs and is easy to handle. Our client needs to begin the project quickly, and that is why we chose Neo4j Graph Database, which was easy for us to select.

For first-time users, if you don't know much about the tool, I think you should go with a document-based DBMS tool. I had to use the tool because I learned about it in college. My advice to others is that they need to learn about the tool, nodes, and vertices and then purchase Neo4j Graph Database. It will be a little bit difficult for new users to know what is the meaning of a node, what vertices are, how to use it, or how an application can use it.

The tool is easy for new users as it is an intuitive tool.

I rate the tool a nine out of ten.

About one year ago, some of my customers were interested in a graph database. I found Neo4j and other local Korean graph database solutions. Neo4j is better than the local vendors as it is a global first-ranking solution. 

Last year the FDS project was completed successfullyeith neo4j, and I am proud to be satisfied with the customer.

We have seen that it has helped the way our company functions and sped up results. 

As a graph database, I am surprised at their performance and response time. 

I found that graphed database does not use the join function. In LDBMS, there's usually the time function with some tables. However, in a graph database, they only have nodes, raw data, and it's very powerful. Using GDB, it's very, very competitive with the RDBMS for some functions and business processes. In some cases, there are a lot of times, a lot of days, or a lot of months to get the results using the RDBMS; however, using the GDB, it only needs a few seconds or a few minutes.

I tested and trained using Neo4j, and the Neo4j database also has a user interface solution called Bloom which is a very, very powerful solution for the client. 

The graph database is very different from the relational database. The graph data solution is not popular in Korea. However, it will be very popular and competitive for customers in the future. It's very good. In two to five years, the GDB, graph database, will be really popular.

The product is easy to set up. 

It is stable. 

The solution can scale. 

So far, we have not had any issues and are happy with the product in general.

However, I wish I had cypher tools to inquiry like RDB SQL tools.

I've been using the solution for 1.5 year including FDS Project.

I haven't had any issues with stability. It seems to be reliable. There are no bugs or glitches. It works well. 

My PCN, my company server, is very small. However, I worked with a large volume of data the first time I used the solution. It is very scalable. 

It takes 30 minutes to load the bulk of test data. However, on the server, the CPU is minimal, and there is no difference in performance. My experience is we use below 10% of the server capability. You can extend the usage tenfold basically by current parameters.

About two or three months ago, two people joined and trained up on Neo4j, even though they have their own job. It's very simple to get more people on board. While we've had many years for the RDBMS, this solution is still very new to us.

We did not previously use a different solution. 

The solution is stable. 

I have seen the operation manual. Using the Neo4j website is free. Anyone can see the installation manual, so it is easily accessible. I didn't face any difficulties setting everything up. You can have it up and running within a day. It is very fast.

I had to delete and install it three or four times and only really needed half an hour to set it up in the end. 

You only need one or two people to handle deployment and maintenance tasks. 

I handled the initial setup myself. I didn't need any outside assistance. 

I don't have information about the license fee amount. That said, I know that the Neo4j license fee is more expensive than a local solution.

There aren't really any extra costs. However, if we need a Neo4j engineer or some architect, at that time, we have to pay more money to them.

I did look into local vendors. However, they didn't have the international reputation this solution does. 

We are trying to get a partnership with Neo4j. Right now, we are customers. 

Neo4j is updated many times. Recently I have experienced about four different versions.

I have tested it in the cloud, which is serviced from Neo4j, and on my desktop PC, as well as my company's local server. 

Neo4j has detailed the training courses and web courses. I would recommend that new people who want to learn Neo4j invest some time through those. They should visit the Neo4j academy or view them on youtube.com.

I'd rate the solution an eight out of ten. 

Relationship management: Understanding which clients can buy which products, building eligibility and propensity criteria.

• It enables circumstances which would have been a complex problem to be simplified. 
• It creates a visualization for people to understand and have engagement.

• Ability to visualize outputs.
• Enables people to understand what the business problem is and how the technology helps.

There are concerns about performance and whether the tool can necessarily scale to provide the solution.

The graph modeling paradigm suits our data set well, where there may be orders of magnitude more connections between data points than data points themselves. The Cypher query language is declarative, expressive and easy to learn the basics. Graph database design also allows for interesting optimization patterns that are more difficult to visualize and model in relational or key/value databases.

We are not transitioning from another database system, so our system will be based on graph database design from the start.

There are things I found unintuitive or difficult to understand, however I can't say this is a deficiency in the product and likely more a function of my relatively low experience. I believe the best performance can be gained by building your logic in Java and interacting directly with their Java API, however this may be less of an issue with the stored procedure support coming in version 3.0.

I've used it for four months.

I hear good things about the scalability when using Neo4j Enterprise Edition and its High Availability cluster support.

They reached out to me, set up a phone meeting to help answer any questions, and along with their partner GraphAware offered a variety of training and prototyping assistance services.

It's pretty straightforward. You can either run the server using the minimal graphical UI, or you can run it directly in various configurations from the command line. There are two configuration files you can tweak to achieve the best memory and disk usage for your needs, as well as to configure any extensions.

In-house implementation. We may use paid vendor services down the road to help with optimization and other advanced usage needs.

We haven't yet transitioned to their paid Enterprise Edition, but it looks like you need to contact them to establish pricing.

We considered Postgres, Mongo and Arongo, but decided that the graph modeling approach was far and away the best match for our data sets.

Strongly consider graph solutions if you have a high ratio of relationships to data points, or if you need to run optimized queries against enormous datasets. Because you can build your own indexing trees, you can really hand-optimize if necessary. There are also out-of-the-box solutions like GraphAware's TimeTree extension that can really limit the number of objects that have to be consulted during a query.