sqlite-vss VS node-redis

I guess this is an answer to the GitHub issue I opened against SQLite-vss a couple of months ago?

https://github.com/asg017/sqlite-vss/issues/124

Perhaps sqlite-vss? It adds vector searches to sqlite.

https://github.com/asg017/sqlite-vss

Utilizing sqlite-vss to store and query vector embeddings managed by a local SQLite database, Semantify conducts fast, precise vector searches within these embeddings to find and recommend relevant content, ensuring readers are presented with articles that truly match their interests.

Whether you’re navigating through well-known options like SQLite, enriched with the sqlite-vss extension, or exploring other avenues like Chroma, an open-source vector database, selecting the right tool is paramount. This article compares these two choices, guiding you through the pros and cons of each, helping you choose the right tool for storing and querying vector embeddings for your project.

Here is a SQLite extension that uses Faiss under the hood.

https://github.com/asg017/sqlite-vss

Not associated with the project, just love SQLite and find it very useful.

Vector Databases: As your data grows, efficiently searching through millions of vectors can become a challenge. Specialized vector databases like FAISS, Annoy, or Elasticsearch's vector search capabilities can be explored to manage and search through large-scale vector data. Your sentence is grammatically correct. In addition, databases like SQLite and PostgreSQL have extensions, such as sqlite-vss and pgvector, that can be used to store and query vector embeddings, respectively.

I had a go at one of those a few months ago: https://datasette.io/plugins/datasette-faiss

Alex Garcia built a better one here as a SQLite Rust extension: https://github.com/asg017/sqlite-vss

Since the problem domain is that of anomaly detection from constructed request feature embeddings, I wonder if an ANN-search methodology using an embedded database (such as https://github.com/asg017/sqlite-vss or similar) was explored.

As I searched for "sqlite vector plugin" I didn't find any results, before a couple of weeks ago. Two weeks ago I found Alex' SQLite VSS plugin for SQLite. The library was an amazing piece of engineering from an "idea perspective". However, as I started playing around with it, I realised it was ipso facto like "Titanic". Beautiful and amazing, but destined to leak water and sink to the bottom of the ocean because of what we software engineers refers to as "memory leaks".

Probably redis.

Did you have an overdose of theory? Let us now taste some code that can help us apply some concepts. This example focuses on the text search. Redis provides us with a straightforward command line interface, along with useful SDK modules in most common languages. Below is a JavaScript code that uses Node Redis module to communicate with the Redis Server. Along with the JavaScript code, we can see the corresponding CLI commands. We need a text-rich dataset to save in our database and demonstrate the search functionality. For this, we will use a dump of poems obtained from Kaggle. The JSON chunk can be found on this link.

You need to call and await the connect method on your clients before you can send commands. For an example, see the sample usage code in the project README.

First thing to deal with is getting the data (using the GeoLite2 free geolocation data from MaxMind) into Redis so can actually query it. This was easier said than done. I used the node-redis lib and well, all the geo stuff in this lib are broken af (mildly speaking).

30 maximum connections may not seem like an issue as long as you are not building an application that has specific requirements for concurrency. This statement could be true if we are establishing connections between a Node server and a Redis cache since it is recommended that only one or two Redis client would be instantiated then reused in the Node server. In this case, there is a limited number of connections (clients are connections in Redis) needed when the server is running and communicating with Redis.

> Sure, the c++ is going to require you to do some sanitizing as you force your data into v8

it's not just sanitizing, there's a lot more to the object creation inside v8 itself. but, even if it were just sanitizing, that mechanism has become a lot more complicated than it ever was in v8 3.1 (timeframe around node 0.4) or 3.6 (timeframe around node 0.6). when interacting with c++, v8 makes no assumptions, whereas when interacting with javascript, a large number of assumptions can be made (e.g. which context and isolate is it being executed in, etc).

> but as we noted that's inevitable no matter how you slice it.

yes, from c++ to javascript and back, but when you need to make that trip multiple times, instead of once, that interchange adds up to quite a bit of extra code executed, values transformed, values checked, etc. sure, banging your head against a wall might not hurt once, but do it 40 times in a row and you're bound to be bloodied.

> Now maybe in some cases the v8 internals offer some advantages the generic c++ api can't access

by a fairly large margin, as it turns out, especially as v8 has evolved from the early 3.1 days to the current 9.8: 11 years. there has been significant speedup to javascript dealing with javascript objects compared to c++ dealing with javascript objects. see below.

> My memories of the redis client is different than yours so I'd be quite interested to see those conversations / benchmarks.

super easy to find, all of that was done in public: https://github.com/redis/node-redis/pull/242 - there are multiple benchmarks done by multiple people, and the initial findings were 15-20% speedup, but were improved upon. the speedup was from the decoding of the binary packet, which was passed as a single buffer, as opposed to parsing it externally and passing in each object through the membrane.

> As a simple thought experiment, in the scenario you're describing we should see a javascript implementation of a JSON parser to beat the pants off the v8 engine implementation, but this doesn't seem to the case.

that's a bit of a straw man argument. especially given that JSON.parse() is a single call and does not require any additional tooling/isolates/contexts to execute, it's just straight c++ code with very fast access into the v8 core:

    Local result = Local::New(isolate, JSON.Parse(jsonString));

I actually found 2 resources which might be useful to help me in setting the ttl expire period for the key: Redis-doc and issue-100 and I wil be dig in to it in couple days to figure it out

The easiest way to connect Redis with Upstash is to use the redis-client as described here.

After filling out the project details, cd into your project and install redis, a Node.js client for Redis, and dotenv, an environment variable loader.