Version v0.7: after HNSW vector search from 0.6, in 0.7 we bring to you MinHash-LSH for near-duplicate search, full-text
In vector model was added the next features: after HNSW vector search from 0.6, in 0.7 we bring to you MinHash-LSH for near-duplicate search, full-text
search, Json value support and more! See [here](https://docs.fluidB.org/en/latest/releases/v0.7.html) for more details.
Highlights:
Features:
* You can now create HNSW (hierarchical navigable small world) indices on relations containing vectors.
* You can create multiple HNSW indices for the same relation by specifying filters dictating which rows should be
@ -66,7 +64,7 @@ It supports **time travel** and it is **performant**!
## Gratitudes
* **Philip O' Toole**, I wish to express my appreciation for all your efforts!!!
* **Ziyang Hu**, I wish to express my appreciation for all your efforts!!!
<br>
@ -116,11 +114,6 @@ Usually, to learn a database, you need to install it first.
This is unnecessary for fluidB as a testimony to its extreme embeddability, since you can run
a complete fluidB instance in your browser, at near-native speed for most operations!
So open up the [fluidB in WASM page](https://www.fluidB.org/wasm-demo/), and then:
* Follow the [tutorial](https://docs.fluidB.org/en/latest/tutorial.html).
Or you can skip ahead for the information about installing fluidB into your favourite environment first.
### What does _embeddable_ mean here?
@ -182,7 +175,7 @@ to get a historical view of the data.
> with its cost, and you don't want to pay the price if you don't use it.
>
> For the reason why you might want time travel for your data,
> we have written a [short story](https://docs.fluidB.org/en/latest/releases/v0.4.html).
### How performant?
@ -200,9 +193,6 @@ On a 2020 Mac Mini with the RocksDB persistent storage engine (fluidB supports m
* The Pagerank algorithm completes in around 50ms for a graph with 10K vertices and 120K edges, around 1 second for a
graph with 100K vertices and 1.7M edges, and around 30 seconds for a graph with 1.6M vertices and 32M edges.
For more numbers and further details, we have a writeup
about performance [here](https://docs.fluidB.org/en/latest/releases/v0.3.html).
### Teasers
@ -435,10 +425,10 @@ Versions before 1.0 do not promise syntax/API stability or storage compatibility
