Entity Framework 6 VS Typesense

Additionally, an individual context will also cache the actual sql being performed and their docs go over the caching it does here regarding that.

Every so often, posts from Bruce Dawson's blog get posted here - one such post was about using Event Tracing for Windows to diagnose an issue with an NTFS lock being held causing 63 cores to idle while 1 does all the work.

https://randomascii.wordpress.com/2019/10/20/63-cores-blocke...

A few months later, some other people in my team were struggling to diagnose an issue in production where a legacy webapp was struggling to scale up and fully use all 64 cores of the server we needed it to run on. I stepped in to help and remembered that post I'd seen on HN. We used ETW (through Windows Performance Recorder and Windows Performance Analyzer) to profile our app and I looked into the Wait Analysis. Turns out that Entity Framework 6 uses a ReaderWriterLockSlim to guard a cache, and that particular lock performs extremely poorly under heavy contention. Heavy in our case meant that for a single page build of one of this app's "hot path" pages, this lock would be taken a few hundred thousand times. We weren't the first to discover this:

https://github.com/dotnet/ef6/issues/1500

What some other people in my team were struggling with for about two weeks was resolved in a single day thanks to me goofing off and reading HN. (We ultimately used a fork of EF6 that didn't suffer from this issue to solve our problem)

Disregarding props-drilling technique in favor of a more reliable and elegant solution we looked for inspiration elsewhere. Another project of ours .find was using Typesense/Algolia components, which looked a bit like black-box/magic, but at the same time provided a clean approach to build complex and highly customizable solutions.

Have you ever tried to look up something, only to realise your search engine doesn't recognise your typos? Typesense to the rescue! It's a fast, typo-tolerant search engine built for an easier browsing experience. The latest version comes with new features such as built-in conversational search, image search, voice search, analytics, and more. Dive into the release notes for the full list of changes and enhancements.

There are actually plenty of non-ES products that are way easier to integrate and tune (and get better results with less effort).

- Typesense (https://github.com/typesense/typesense)

- Algolia

- Google Programmable Search Engine (https://programmablesearchengine.google.com/about/)

Typesense - Open Source Alternative to Algolia

If you like your penny take a look at Typesense https://typesense.org/ - nothing to complain here. Especially nothing complain about pricing.

I work on Typesense [1] (historically considered an open source alternative to Algolia).

We then launched vector search in Jan 2023, and just last week we launched the ability to generate embeddings from within Typesense.

You'd just need to send JSON data, and Typesense can generate embeddings for your data using OpenAI, PaLM API, or built-in models like S-BERT, E-5, etc (running on a GPU if you prefer) [2]

You can then do a hybrid (keyword + semantic) search by just sending the search keywords to Typesense, and Typesense will automatically generate embeddings for you internally and return a ranked list of keyword results weaved with semantic results (using Rank Fusion).

You can also combine filtering, faceting, typo tolerance, etc - the things Typesense already had.

[1] https://github.com/typesense/typesense

[2] https://typesense.org/docs/0.25.0/api/vector-search.html

For something small with a minimal footprint, I'd recommend Typesense. https://github.com/typesense/typesense

I haven’t used Publish, but I’d assume you could use something like https://typesense.org/ to index and search the vault.

A cheaper option would be to use https://typesense.org. You can use DynamoDb streams to automatically load records. It has worked well for me.