GlusterFS VS Neo4j

https://github.com/gluster/glusterfs/issues/894

And apparently apart from modern coreutils using that, it is mostly gentoo users hitting the bugs in lseek.

This Product Appendix does not apply to online service offerings managed by Red Hat or generally available open source projects such as www.wildfly.org, www.fedoraproject.org, www.openstack.redhat.com, www.gluster.org, www.centos.org, okd.io, Ansible Project Software or other community projects.

Just because Red Hat will stop selling commercial support for their product, does not mean GlusterFS itself is dying. It's an open source project like any other - https://github.com/gluster/glusterfs

https://www.gluster.org/ Is the way to do this across nodes

This allows us to fetch the desired quality of the video as per the user's request, and once the media file finishes processing, it will be uploaded to a distributed file storage such as HDFS, GlusterFS, or an object storage such as Amazon S3 for later retrieval during streaming.

GlusterFS

But where can we store files at scale? Well, object storage is what we're looking for. Object stores break data files up into pieces called objects. It then stores those objects in a single repository, which can be spread out across multiple networked systems. We can also use distributed file storage such as HDFS or GlusterFS.

GlusterFS - same as above (https://www.gluster.org/)

What you look for is a clustered file system. Like https://www.gluster.org/. As long as all units are closeby with low latency there are a couple solutions that allow you to create distributed storage solutions of various kinds. Key value stores applenty, clustered file systems that pretent to be one file system etc. If you have geographically distributed solutions with high latencies it becomes harder. Most open source systems don't work really well in this scenario. There were a couple attempts like Hydrabase but they didn't go so far. It normally is solved by doing two clusters and then replicate between them.

I'd imagine most managed service providers are going to require a credit card, though most of them have a free tier. If you want to take an unmanaged approach, maybe look into Gluster. I've used it before and never had issue with it, but I also had an infrastructure team that set it up, so I'm not familiar with the challenges that way: https://www.gluster.org/

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.