nodejs-storage VS Neo4j

Cloud Storage: blog storage for static assets and media files

Preevy includes built-in support for saving profiles on AWS S3 and Google Cloud Storage. You can also store the profile on the local filesystem and copy it manually before running Preevy - we won't show this method here.

Google Cloud Storage{:target="_blank"} is a globally distributed object storage service offered by Google Cloud Platform. They provide trustworthy and scalable databases for storing large amounts of blob data. They also provide a way to optimize cost and performance with different storage classes and pricing options.

Google Cloud Storage - https://cloud.google.com/storage/

Also, in terms of packing a pre-trained model you will probably want to puts weights, biases etc into S3 or similar object storage (https://cloud.google.com/storage etc) and load it on application start

An object storage system (e.g. Amazon S3, Azure Blob Storage, Google Cloud Platform Cloud Storage, etc.) makes it easy and simple to save large amounts of historical data and retrieve it for future use.

ToolJet allows you to build applications that use relational and non-relational databases, REST APIs, and cloud storage like Google Cloud Storage, AWS S3, and Minio. It is an excellent development tool helping individuals, developers, and businesses create and ship products faster.

Google Cloud Storage is a flexible, scalable, and cost-effective option for hosting a static website. It offers features like custom domains and SSL certificates, and it's easy to use. However, it can be more expensive than some other options for high-traffic websites.

There are a few ways to handle this depending on your client's preferences. If your client still wants to own the data, we support exporting to Object Storage systems like S3, GCS, R2, etc. This will keep the data out of their production systems but allow them to query it on demand.

Of course, the storage layer is the place where the data is stored. Because the amount of data to be stored is huge, we can not use HDD or SSD data storages, we need something cheaper. In this case we will be talking about AWS S3 because we are working with Amazon Web Services. For Azure, you could use Azure Data Lake Storage Gen2. If you are working with Google Cloud, you could use Google Cloud Storage. It does not matter what storage you use as long as it is cheap and can store a huge amount of data.

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.