Neo4j Graph Database Reviews

It is opensourced graph database.

Semi structred data can easily represented and easily get retrive connected data faster.

Scalable architecture.

It helps to maintain the predictability of relation based queries.

No security for data and No data encryption.

There is limit in the graph size like per graph it supports 10 B of nodes.

We are integrating Neo4j knowledge graphs with LLM. This helps to remove model hallucinations in the output or inferencing. Sometime we combine both the results of neo4j and LLM.

Neo4j is a great platform for the new user to learn the commands it is very interesting, and we can see the command along with its results. we can see the result in multiple ways like in graph format, table, text or code.

I do not have much dislike about this platform but this is little confusing for the new user because it is little complicated for installation and initiate the commands. User may require the instruction for installation.

A user can easily learn the database command by implementing multiple changes in similar commands. moreover it is very interesting for the user user to run the command and the best thing is that a person can see the overview for more details about the its queries.

The active development, the large, international community, integrations, available documentation and training, certification programs, online events, friendly UI, easy-to-use query language and APOC.

I cannot think of anything serious, but the upgrade process could be more straightforward and not require running multiple upgrades to get to the latest version if you're running a much older one in production.

As with graph databases, one of the most generous benefits, especially compared to traditional databases, is the relationships between the data that can be easily traversed and help discover hidden connections.

Neo4j is the most interactive and easy to use or query tool I have ever worked with. The cyphers are so user-friendly that someone with no knowledge of programming or query languages can get started at any moment which gives us an edge to explain the BI analysis and parameters to our customers. Visualizations help you debug and resolve the issues way faster compared to other DBs. And their integration with most cloud services allows a smooth integration in our applications.

There is nothing that comes to my mind right now.

Knowledge graph-based recommendations problems with real-time BI analytics using Looker and inhouse dashboards.

Very Easy to convert a standard dataset to graphical form which provides more detailing and understandability.

Yet not encountered, still exploring NEO4J

Neo4J for Graphical Data Science and its integration with Python

Very Easy to convert a standard dataset to graphical form which provides more detailing and understandability.

Yet not encountered, still exploring NEO4J

Neo4J for Graphical Data Science and its integration with Python

Very intuitive and engaging. Love the different labs that neo4j offers to understand the various use cases. Easy to get on with. One good thing is browser, desktop and aura db all have a unified user experience

CQL is a learning curve. Not easy to understand the syntaxes. Even though neo4j bloom is intuitive, it has many features that require some training to fully make use of it

its helping visualise the data in a graph format, unlocking newer insights and relationships between entities. I have use neo4j to visualise the network connectivity

Never experienced Hyper Agility of an App that handles > 10k rows of data. That's not the basic reason. Neo4J helps you validate your thoughts. By connecting nodes & other tags and all possible information about a particular topic; you get to see the grammatic scope of a matter which is more important than the numeric scope which we can see through Excel etc.

Nothing as such - the technology at Neo4J is ahead of times.

Being a student of one of their academic courses, I can say that Neo4J will benefit law agencies, law enforcement etc deeply. If it's about an unheard politician who recently won the elections - using Neo4j one can instantly connect all the past dots about the person through information pulled and consolidated from diverse sources such as mainstream media reports containing the person's name, blogs, and everything else which the developer can connect to the system to pull info. It's a jiffy experience using Neo4j to get 360-degree information and see them in graphs. Yes I am a graphista!

The ability to tie together vastly diverse datasets within our service offerings, compare them to provisioning (actual) and automate remediation as well as traditional reporting functionalities.

This has allowed us to rapidly create functionality where no native integrations exist and map our client experience with our service catalog (planned services)

The biggest difficulty is creating customized graph native applications, as we don't currently have modern SPA development teams within our company. the neo4j browser is still too technical for most of our end-users. It sounds like the new workspace integrations may help solve some of these issues.

We are validating our services vs service offerings sold are matching up, and using graph queries to automate remediation tickets and reporting when they do not align.

Also solving data accuracy by verifying accounts in different systems are provisioned/named properly (by identifying missing relationships).

We are rapidly identifying over or underprovisioning of services for our clients so we can remediate them before it becomes an issue.

The multi labels. Everyone is so kind and helpful, and the community is amazing. I'm extremely glad that it's maintained Cypher as I find it so much more enjoyable to use than the other languages for graphs on the market. The integrations are easy to todo, and it enables me to use all the data science of python with ease.

AuraDB is extremely pricey, much higher than MongoDB which makes it difficult to convince my superiors to let us switch. I enjoy the visualizers, but I wish NeoDash was truly made into a formal tool as many of my colleagues want a dashboard.

I'm using knowledge graphs to bring in a variety of information about orcas in the Puget sound from research papers, and environmental context, to free from citizen scientist reports. Along with that I volunteer for Freedom Signal and am trying to get them to move their data from MongoDB to Neo4j. The cost is prohibitive for a non-profit, but the gains they will get from speed and insights using clustering for the sex trafficking rings I believe will be invaluable.