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Looking forward to giving it another try soon!
Could someone explain what a graph-relational database is? I'm not able to extract a technical definition from the paragraph below: "What is a graph-relational database? EdgeDB is built on an extension of the relational data model that we call the graph-relational model. This model completely eliminates the object-relational impedance mismatch while retaining the solid basis of and performance of the classic relation…
(EdgeDB CTO here) In a classic relational model everything is a tuple containing scalar values. Graph-relational extends the relational data model in three ways: - every relation always has a global immutable key independent of data (explicit autoincrement keys aren't needed) - this enables us to add a "reference type", which is essentially a pointer to some other record (i.e. a foreign key) - attributes can be set-v…
I think this work is absolutely commendable, but at the end of the day it's a database written in Python with Rust extensions sprinkled here and there. Is 1.0 your MVP?
We perform quite favorably in benchmarks, see our old blog post with some: https://www.edgedb.com/blog/edgedb-1-0-alpha-2#results
> Is 1.0 your MVP?
EdgeDB is ready for production and is light years ahead of its first technical preview MVP release published a few years ago.
I tried the beta around August last year. I struggled grokking it mostly because I had had very minimal experience with SQL - which it kind of assumed you already know the drawbacks of. However, I did like the idea very much. Looking forward to giving it another try soon!
To quickly learn EdgeQL I recommend our online interactive in-browser tutorial: [1]
We also have a book, it's called Easy EdgeDB, check it out here: [2]
Congrats! Can I get the ebook as pdf somewhere?
Earlier quoted context omitted.
This is a nice example. How the data is stored physically? Does the model work for large datasets and when it could break down? What are optimal workloads? Do we still need to fiddle with indexing and such?
Data is stored relationally in Postgres in 3NF. References are indexed automatically, but you still need to index type properties if you use them in `filter`.
FWIW, I do think there's a space in the market for a thin wrapper over Postgres (or MySQL) which would automate certain optimisations such as whether to index a particular table. It always struck me as perverse that that optimisation was delegated to the developer, when it's no more subjective or application-specific than a thousand other automated optimisations the engine makes. I'd be really interested if your project covered that.
> the first open source, graph-relational database OrientDB?
As far as I'm aware OrientDB don't call themselves "graph-relational". In fact, they're positioning themselves as a multi-model NoSQL database. Where's EdgeDB positions itself as a relational database and a successor of SQL.
How you guys compare yourself to dgraph database?
Earlier quoted context omitted.
Data is stored relationally in Postgres in 3NF. References are indexed automatically, but you still need to index type properties if you use them in `filter`.
Wait, it stores the data in Postgres? So this is essentially a data model on Postgres? FWIW, I do think there's a space in the market for a thin wrapper over Postgres (or MySQL) which would automate certain optimisations such as whether to index a particular table. It always struck me as perverse that that optimisation was delegated to the developer, when it's no more subjective or application-specific than a thousan…
Could someone explain what a graph-relational database is? I'm not able to extract a technical definition from the paragraph below: "What is a graph-relational database? EdgeDB is built on an extension of the relational data model that we call the graph-relational model. This model completely eliminates the object-relational impedance mismatch while retaining the solid basis of and performance of the classic relation…
(EdgeDB CTO here) In a classic relational model everything is a tuple containing scalar values. Graph-relational extends the relational data model in three ways: - every relation always has a global immutable key independent of data (explicit autoincrement keys aren't needed) - this enables us to add a "reference type", which is essentially a pointer to some other record (i.e. a foreign key) - attributes can be set-v…