20 unstable releases (3 breaking)
new 0.4.0-alpha.10 | Dec 11, 2024 |
---|---|
0.4.0-alpha.3 | Nov 29, 2024 |
0.1.2 | Dec 31, 2020 |
0.1.1 | Nov 24, 2020 |
#260 in Database interfaces
1,086 downloads per month
300KB
8K
SLoC
🚧🚧🚧 Please note that this is work in progress, so while a lot of things have settled by now, we still favour breaking backwards compatiblity for seeminly minor improvements. 🚧🚧🚧
About
The real tragedy would be if people forgot that you can have new ideas about programming models in the first place.
- Bret Victor
The trible.space is our answer to the question "what if we re-invented data storage from first principles". It is a knowledge graph standard for blob storage that provides metadata management capabilities similar to file- and version-control-systems with the queryability and convenience of an embedded database.
We hope to overcome the shortcomings of previous semantic web/triple-store technologies, through simplicity, easy canonicalization and cryptographic identifiers, clean distributed semantics and lightweight libraries empowered by idiomatic host-language capabilities.
By reifying most concepts and operations as first class citizens, we hope to provide a toolkit that can be flexibly combined to serve a variety of knowledge representation, database, and data exchange use cases.
Differentiators
- A novel family of worst case optimal join algorithms combined with a series of tailored datastructures obviates manual query-tuning.
- Optimizer-free query engine design, providing predicatble performance and enabling single digit μs latency.
- Fast in-memory datasets with cheap COW semantics (i.e. persistent immutability).
- Fast set operations over in-memory datasets.
- Separation of names and identities.
- Explicit abstract datatypes and concrete layouts.
- Durable compressed fully queryable zero-copy archives, based on succinct datastructures.
- Self describing and documenting.
- Eventually consistent distributed semantics based on CRDTs and CALM, providing build-in version control.
- 🚧 Delta-Queries between arbitrary datasets.
- Compile-time typed queries and dataset construction.
- Low overall complexity. If you feel that stuff is obvious, maybe a bit boring, and that you could have come up with it yourself, then we achieved our goal.
Community
If you have any questions or want to chat about graph databases hop into our discord.
Example
use tribles::prelude::*;
use tribles::prelude::valueschemas::*;
use tribles::prelude::blobschemas::*;
NS! {
pub namespace literature {
"8F180883F9FD5F787E9E0AF0DF5866B9" as author: GenId;
"0DBB530B37B966D137C50B943700EDB2" as firstname: ShortString;
"6BAA463FD4EAF45F6A103DB9433E4545" as lastname: ShortString;
"A74AA63539354CDA47F387A4C3A8D54C" as title: ShortString;
"76AE5012877E09FF0EE0868FE9AA0343" as height: FR256;
"6A03BAF6CFB822F04DA164ADAAEB53F6" as quote: Handle<Blake3, LongString>;
}
}
fn main() -> std::io::Result<()> {
let mut blobs = BlobSet::new();
let mut set = TribleSet::new();
let author_id = ufoid();
set.union(literature::entity!(&author_id, {
firstname: "Frank",
lastname: "Herbert",
}));
set.union(literature::entity!({
title: "Dune",
author: &author_id,
quote: blobs.insert("Deep in the human unconscious is a \
pervasive need for a logical universe that makes sense. \
But the real universe is always one step beyond logic."),
quote: blobs.insert("I must not fear. Fear is the \
mind-killer. Fear is the little-death that brings total \
obliteration. I will face my fear. I will permit it to \
pass over me and through me. And when it has gone past I \
will turn the inner eye to see its path. Where the fear \
has gone there will be nothing. Only I will remain.")
}));
let title = "Dune";
for (_, f, l, q) in find!(ctx,
(author: (), first: String, last: Value<_>, quote),
literature::pattern!(ctx, &set, [
{ author @
firstname: first,
lastname: last
},
{
title: (title),
author: author,
quote: quote
}])) {
let q: &str = blobs.get(q).unwrap();
println!("'{q}'\n - from {title} by {f} {}.", l.from_value::<&str>())
}
Ok(())
}
Dependencies
~82MB
~1M SLoC