31–40 of 45 posts
Great tutorial on graph modeling! The author did an excellent job of explaining the basic terminology and practices related to graph databases and graph modeling. The tutorial is well-structured and easy to follow, making it an excellent resource for anyone looking to learn more about graph modeling. The author covers a wide range of use cases for graph databases, including social networks, fraud detection, network a…
ChatGPT or not, if this is an honest comment, thnx! :)
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What a world we live in, where a person can't write a coherent blurb of text without being suspected of using ChatGPT. Anyone remember Idiocracy? That movie is starting to sound more and more like a prophecy.
Your original post is a summary without any new ideas or thoughts about the article. That is why it reads like you asked an AI to generate it. I don’t think the question was meant as an accusation, but it is amusing to think about whether some commenters are using an AI to generate their comments. Would we even notice?
You're right. I often look for a quick summary of the articles here in these comments to avoid falling for clickbaits, so contributing a summary about something I found useful.
> I don’t think the question was meant as an accusation, but it is amusing to think about whether some commenters are using an AI to generate their comments. Would we even notice?
Fair enough. The one word question was hard to read into, and it's amusing indeed. We shall never know for sure!
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What a world we live in, where a person can't write a coherent blurb of text without being suspected of using ChatGPT. Anyone remember Idiocracy? That movie is starting to sound more and more like a prophecy.
Repeating "graph modeling" three sentences in a row, with all those sentences being damn near content-free, reads like it came from something even less capable than ChatGPT, to me.
Sorry to disappoint?
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Thanks for this intro to Graphs. Does Memgraph persist to disk or is it in-memory only? If in-memory only, do you have plans to support graphs which become larger than available memory? Thanks!
Yes, memgrpah persists data on-disk, but there is not the support for larger than memory datasets yet (but a lot can fit on a single machine). In general, our primary focus at the moment is the scale out / proper graph sharding support. The progress on that side can be tracked under the following project -> https://github.com/orgs/memgraph/projects/5 How big is your graph and do you have specific queries in mind?
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Yes, memgrpah persists data on-disk, but there is not the support for larger than memory datasets yet (but a lot can fit on a single machine). In general, our primary focus at the moment is the scale out / proper graph sharding support. The progress on that side can be tracked under the following project -> https://github.com/orgs/memgraph/projects/5 How big is your graph and do you have specific queries in mind?
I have around 100GB of data in a relational database. Not sure how that would translate into nodes and edges. Is that amount feasible in Memgraph?
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I have around 100GB of data in a relational database. Not sure how that would translate into nodes and edges. Is that amount feasible in Memgraph?
It depends on a few things. If you want to migrate all the data that's heavier than just, e.g., the graph part and connections. It heavily depends on the final model, required data types and overall distribution of data. This guide -> https://memgraph.com/docs/memgraph/under-the-hood/storage can help you with calculating the amount of required RAM. Also, we plan to include a simple calculator into the next release of…
Earlier quoted context omitted.
It depends on a few things. If you want to migrate all the data that's heavier than just, e.g., the graph part and connections. It heavily depends on the final model, required data types and overall distribution of data. This guide -> https://memgraph.com/docs/memgraph/under-the-hood/storage can help you with calculating the amount of required RAM. Also, we plan to include a simple calculator into the next release of…
Thank you so much! One more question if you'll permit me - and then I'll leave you alone I promise. Social networks are often recommended as a use-case for a graph database. How well would Memgraph perform on generating an activity feed of all of the posts of the people I follow ordered by post date descending, for example (hopefully with pagination)?
Please join our Discord at https://discord.gg/memgraph, more people will be able to help you there :)
The concepts (nodes, edges, etc...) can all be represented in a traditional relational database using tables and foreign keys.
What is the advantage of a graph database?