docs: Updating sqlite-vec docs to show comparison of sqlite-vec and faiss

Signed-off-by: Francisco Javier Arceo <farceo@redhat.com>

docs/source/providers/vector_io/sqlite-vec.md

@@ -10,11 +10,40 @@ That means you're not limited to storing vectors in memory or in a separate serv
 ## Features
 
 - Lightweight and easy to use
-- Fully integrated with Llama Stack
+- Fully integrated with Llama Stacks
+- Uses disk-based storage for persistence, allowing for larger vector storage
+
+### Comparison to faiss 
+
+SQLite-Vec is a lightweight alternative to Faiss, which is a popular vector database provider.
+While faiss is a powerful, fast, and lightweight in line provider, faiss reindexes the 
+entire database when a new vector is added. SQLite-Vec is a disk-based storage provider 
+that allows for larger vector storage and handles incremental writes more efficiently.
+
+sqlite-vec is a great alternative to faiss when you need to execute several writes to the 
+database.
+
+Consider the histogram below in which 10,000 randomly generated strings were inserted 
+in batches of 100 into both `faiss` and `sqlite-vec` using `client.tool_runtime.rag_tool.insert()`.
+
+```{image} ../../../../_static/providers/vector_io/write_time_comparison_sqlite-vec-faiss.png
+:alt: Comparison of SQLite-Vec and Faiss write times
+:width: 400px
+```
+
+You will notice that the average write time for `sqlite-vec` was 788ms, compared to 
+47,640ms for faiss. While the number is jarring, if you look at the distribution, you'll notice that it is rather uniformly spread across the [1500, 100000] interval.
+
+```{image} ../../../../_static/providers/vector_io/write_time_sequence_sqlite-vec-faiss.png
+:alt: Comparison of SQLite-Vec and Faiss write times
+:width: 400px
+```
+For more information about this discussion see [the GitHub Issue](https://github.com/meta-llama/llama-stack/issues/1165) 
+where this was discussed.
 
 ## Usage
 
-To use SQLite-Vec in your Llama Stack project, follow these steps:
+To use sqlite-vec in your Llama Stack project, follow these steps:
 
 1. Install the necessary dependencies.
 2. Configure your Llama Stack project to use SQLite-Vec.