prisma-examples VS Neo4j

The usefulness of vector search is already evident by the rate of generative AI adoption. Almost every mainstream documentation site now has an Ask AI button, including Supabase, Netlify, Prisma, and many more.

Prisma

We'll use a simple blogging app as an example through out this article. Our work will be based on the NestJS + Prisma starter project here. You can also create a new project from it with a one liner:

Prisma's docs[0] are one of the best I've read

[0] https://www.prisma.io/docs

Quiero algo de este estilo: https://github.com/prisma/prisma-examples/tree/latest/typescript/graphql-nexus

Prisma is a package that invites new users. It is well-documented and well-suited for your first or 50th Node project. Their documentation contains comprehensive information on the features available. You can also access several guides, including introductory "how-tos," steps for deploying applications that use Prisma, and instructions on migrating from another ORM. The guides are thorough, up-to-date, and easy to follow. In addition, Prisma's team has made sure your experience using their ORM is as painless as possible.

And that's how we can use a Node.js library like Prisma to work with NoSQL and SQL databases. Prisma's documentation page gives further details about this process.

We will follow the documentation to get started with Prisma. You can read and also take a reference to the documentation.

Neo4j

Neo4j: An ACID-compliant graph database with a high-performance distributed architecture. Ideal for complex relationship and pattern analysis in domains like social networks.

After spending millions fighting the committer of ONgDB who removed the commons clause from the AGPL branded license, it looks like the Free Software Foundation got involved and forced them to remove the commons clause or change the license to their own proprietary license.

https://github.com/neo4j/neo4j/commit/b6237ca4e31706b1efbd0f...

The GenAI Stack came about through a collaboration between Docker, Neo4j, LangChain, and Ollama. The goal of the collaboration was to create a pre-built GenAI stack of best-in-class technologies that are well integrated, come with sample applications, and make it easy for developers to get up and running. The goal of the collaboration was to create a pre-built GenAI stack of best-in-class technologies that are well integrated, come with sample applications, and make it easy for developers to get up and running.

Neo4j (GraphQL)

NoSQL is a term that we have become very familiar with in recent times and it is used to describe a set of databases that don't make use of SQL when writing & composing queries. There are loads of different types of NoSQL databases ranging from key-value databases like the Reddis to document-oriented databases like MongoDB and Firestore to graph databases like Neo4J to multi-paradigm databases like FaunaDB and Cassandra.

this thread on this github issue could be useful.

Recently I have taken an interest in big data. https://neo4j.com/ , https://cassandra.apache.org/ , https://clickhouse.com/, https://www.elastic.co/ - are all databases I have experience with. Neo4j and Cassandra only as a hobby, but Clickhouse I have used in production, and Elasticsearch I have used for some 7 years now.

For organizations and their applications that are designed to detect fraud, like International Consortium of Investigative Journalists, or try to improve customer experience via personalization, as in the case of Tourism Media, a NoSQL graph database like Neo4j is a good match. In these kinds of use cases, the quantity of data we're dealing with is enormous, and the pattern we're searching for in the data is often complex.

First, you need to choose a specific graph database platform to work with, such as Neo4j, OrientDB, JanusGraph, Arangodb or Amazon Neptune. Once you have selected a platform, you can then start working with graph data using the platform's query language.