Vector Databases simply explained! (Embeddings & Indexes)

[@ChrisBrogan]

I just watched an IBM explanation of vector databases and came away lost. Then I watched yours, and got it right away. Point goes to you. ;)

[@dashmasterful]

Same here!

[@ajeffrrterererefdf]

Yep, Same story!. I will just paste this video link there so that someone may benefit.

[@noneyahbiz6976]

Will not watch IBM LOL- we briefly went over vector searches in NN class- but professor was horrible-

[@siddhubhai2508]

Same here.

[@punymagus]

Same, that video is just clickbait

[@nickstaresinic9933]

The concise, high-level explainer that I needed. Thanks.

[@jolly2002me]

Yes please, more on this topic, I would appreciate it.

[@HeyImAK]

👆

[@bobsavage3317]

Yes, a video describing available VDBs in terms of, e.g. Open/Closed, simplicity of operation, and user interaction patterns (quality/expressiveness of API) would be great!

[@ProSaladToss]

Seconded

[@assethotorch2395]

kzbin.info/www/bejne/j6CQcq2MpbyliMk You may find it helpful to start with the time frame of the video above!!

[@RomeoKienzler]

Also important how to extend the vdb with custom distance functions

[@decodingdatascience]

🎯 Key Takeaways for quick navigation: 00:41 📊 Vector databases store Vector embeddings for fast retrieval and similarity search. 01:07 📝 Unstructured data like images, text, and audio can be challenging to store in relational databases, making vector databases valuable. 02:02 🔍 Vector embeddings allow for finding similar items by calculating distances and performing nearest neighbor searches. 03:10 🗂️ Vector databases have various use cases, including equipping language models with long-term memory, semantic search, similarity search, and recommendation engines. 03:50 💽 Examples of vector database options include Pinecone, Chroma, Redis, Cool, Trans, Milvus, and Vespa AI, each with its strengths and capabilities.

[@4XLibelle]

Excellent overview. Many thanks!

[@brunomesquitazamberlan8876]

Very useful. Now I can imagine what is a vector database. Thanks

[@matt_88]

Definitely! I'd love to see comparable benchmarks for common LLM and other tasks (i.e. transfer learning, use-cases in the context of fine-tuning, etc)

[@Mirko-Peters]

Wow, this video makes vector databases so easy to understand! Thanks for breaking it down so clearly-really appreciated! Keep up the great work!

[@upByNune]

My guy came through with knowledge and resources! One word - GOAT!

[@etownrule]

Finally, a sensible explanation. Crystal clear, thanks

[@maneeshs3876]

Nice summary on Vector databases. A comparison of Graph and Vector databases with specific use cases would also help. Thank you

[@GenAIBlackBelt-qs6uh]

Thank you! This is great stuff. Love the simplicity.

[@ksnydertube]

Thank you for this video - just what I needed! If you haven't done one already, please do an explainer comparing. 🙏

[@DanielTorres-gd2uf]

Let's see the more in depth comparison! Also would love to know your take on where it will go? Are they able to automatically generate vectors for your multimodal data already? Are there known companies using vector databases currently? Are there lightweight alternatives to the services you offered? (ie. a numpy verision of a vector database?)

[@lesegotsheole6008]

New to this world of machine learning I have to say job well done on explaining in simple terms. This was insightful and had pleasure watching it. Thanks!

[@08ae6013]

Thank You... It's a great explanation on Vector database. Please make a in depth videos on Pinecone & Redis vector databases

[@leftright1606]

Yes, looking forward to a more in-depth video.

[@Maisonier]

Yes please a video about that. Liked and subscribed

[@otto.bjorkland]

It would be great if you explained how to use vector databases to give LLM's long term memory! 🙏

[@MrVliegendepater]

Interested in a comparison video between the different types of vector databases! Really well explained and to the point!

[@Bloeise]

This was a very clear explanation. Thank you!

[@rezaru2000]

Thanks, this is what I needed to understand the overall idea of vector db.

[@jonmichaelgalindo]

Straight forward and simple. Thanks! 😊

[@SoharabHossain]

Brief and to the point. Great video.

[@olivierrochon3858]

Perfectly clear. Thanks!

[@TeamUpWithAI]

Thanks for putting this together! :)

[@p.j.816]

This was a really good video! Thanks so much :)

[@yubinnng]

Brief and clear!

[@bjugdbjk]

Definitely need a comparisio video and small example code for the top 3 Vector DB's used !! By the way ,Fantastic walk through of the concept !!.

[@ser1ification]

Thank you, more please :)

[@vincerocchi9083]

Love your work Patrick. Definitely would like to see more on vector databases, especially when you would use one over an array or other options and the pros and cons of some of the types you mentioned (I.e. Pinecone, Milvus, etc.)

[@sidharthgovind4356]

Good explanation touching on essential parts of this topic. Well done!

[@VastCNC]

Would definitely be interested in more details, especially on self hosted VDBs

[@sanjeevKumar-eg6hp]

thanks for a such a detailed and easily understandable knowledge

[@caiyu538]

Thank you Patrick.

[@muhammadmursalin8915]

Thanks, describe very simply what the vector database is and its uses.🥀

[@PatrickSeidel-s5y]

Thank you, nice and short overview to get an idea of what a vector db is.

[@karthickmj6312]

Thank you so much, Patrick. Would love to watch a video detailing and comparing all VDBs.

[@kevinli3767]

This is a really good explanation and visualization

[@divakaratanjore1059]

Awesome explanation! Thank you

[@nsitkarana]

to the point and concise explanation !!

[@realjackofall]

Simply explained. Thanks!

[@Naimish_RuuhaaniiAaVaaz]

Very good explanation.

[@alexfowler1683]

Great video, thanks! Short and exactly on point -- much appreciated. Yeah, it'd be cool to see more in-depth comparison of the dbs.

[@lowai8749]

Make complicated concept for easy understanding, thank you very much!

[@mohamedbilal5634]

Explanation On point !!! Thanks

[@Nega_Samurai]

That was very helpful! Thank you!

[@saimanikanta7360]

yup!! looking forward to a detailed analysis and comparison

[@jaylee7864]

Thanks for the Video. you are awesome and very easy to understand what they are. I think Pinecone is quite popular so if there is a video about it, it would be great. Cheers

[@soubinan]

Great video! thank you! A big YES for a Vector DB dedicated video Btw I am happy I have found this channel, let's subscribe !

[@dabravo100]

Great video… please go on with the next one

[@Anonymous-lw1zy]

Yes please, a VDB comparison would be great, and please include FAISS and other self-hosted options.

[@Dkay-gf8ft]

Thanks very easy to understand explaination

[@anirudhgangadhar6158]

Great intro to VD! Would love to see a more in-depth video on some real-world use cases :)

[@mbrochh82]

comparison video for the mentioned VDBs at the end would indeed be awesome!

[@VaibhavPatil-rx7pc]

Cool, please explain more details about each vector db thanks

[@khari_baat]

Good informative video. Thanks!

[@fnmby]

Please continue..)

[@asifmian43]

I would love to see a comparison of the different Vector Databases!

[@SubirSengupta1]

I would love to see a comparison of the different VDB's and perhaps your thoughts on which one or two are the best. Thanks for a great video.

[@nikilragav]

This is a great explanation. But the indexing part is what I was looking for. Nearest neighbor search is already a hard problem in Computer Graphics and gaming (to detect collisions. E.g. if you ever play Madden and do a slow-mo replay, you'll see that the receiver never actually touches the ball. or E.g. cloth simulations for a cape often "clip" into the 3d model of the person wearing the cape).

[@ayoubthegreat]

I love the video. One critique would be to set up further away from the background to possibly reduce the reverb you're getting

[@ryansteiger6960]

Thanks for the video 👍

[@ednavas8093]

Incredible video

[@hughesadam87]

Great video thank you!

[@bindass1000]

Super helpful!

[@talentzunlimited1398]

Great video !

[@beemerrox]

Good explanation. Thumbs up 👍

[@nickmhc]

A breakdown of differences between vector databases would be nice. But also a comparison to graph databases like neo4j and TitanDB et al would help this n00b

[@davidlepold]

It could be interesting to see a case of adding a vector dbase to an existing sql database, if it can replace it, or if a parallel approach might be interesting, using them side by side, each taking advantage of strenghts. etc.

[@soujanya1993]

Please create a video comparing the vector databases

[@ilikegeorgiabutiveonlybeen6705]

yeah nitty gritty indexing options overview and use cases for said options would be higlhy appreciated

[@YogeshVerma-f3e]

An in-depth comparison would be great!

[@slawikus1982]

Thanks for a nice video! Would be great to learn more on how one could use Redis and PostgreSQL as vector databases. Additionally, more examples and use cases for vector databases would be cool.

[@katsunoi]

nice video - thanks!

[@sailendramishra1560]

Short video but very useful

[@jessem2176]

I would love to see.. what is the Best Vector database... ease of use vs performance. and why. This way we can stop guessing which one to try to use and just know this one is by Standard the best.

[@ShaquibKhan]

Which tool are you using to make these beautiful slides? is it excalidraw+ ?

[@vamc256]

Please explain further, any one of the vector databases with an example for each Weaviate, Pinecone..

[@WmSadler]

woud love to see detailed comparison of the vector databases

[@satyamvishuu]

Thanks man

[@OP-g7g]

Can you share the pros and cons of all the vector databases you mentioned in this video. Which one to choose and why?

[@MyWissam]

Yes for a comparison video.

[@lancerkind]

I would enjoy seeing a comparison among these different vector databases. Today I just picked the one that’s most convenient. But there’s probably a better rationale for choosing among them. The other topic I’d like to see is sustainability. For example, if I’m adding a new vector to the database once a week what will happen after 10 years? Is that a sustainable growth when I have a 1016 element vector everyweek of the year or do I need to do something to re-index the database so that my performance doesn’t drop after a number of years? The data I’m creating now would be relevant for many decades.

[@RanitDA]

Good topic 🎉

[@smartfusion8799]

Yes please, i habe to decide soon which database, redisearch is cloud only, pinecone too i think

[@MartinQLynx]

Supabase also joined the vector DB club a while ago.

[@georgelza]

please include Oracle and Mongo as vector database options.

[@MatthewShang]

It would be great to see a comparison of the vector database companies

[@harshjain3122]

This is like that scene from the Matrix where Neo stops the bullets and he sees the Matrix(humans, objects alike) as lines of code. We are now converting objects like banana and apples into a bunch of numbers which even we can no longer understand looking at them via the vector embedding.

[@UDAY-pv5il]

Great content.I noticed the Elastic name is missing from the list of vector databases. Could you please include it in the list?

[@mrfreezey1]

Melvis in-depth plz and thanks

[@hammanadamafarukabubakar8365]

Great one

[@pascalmartin1891]

I remember working on a vector database in the mid 1980s. That was a Pick system, mostly used for accounting, warehouse management and the like. Re-innovation. 😁

[@PrashantKataria-g7t]

Could you provide an overview on the comparison of different Vector Database providers and how to decide which is better?

[@hughster657]

Why isn't KX mentioned in this overview? They have a very strong vector database and support time-series data as well. Formula 1, manufacturing, utilities, and all the banks use them.

[@SonGoku-pc7jl]

thanks, you have a video for the comparate diferences quality between?

[@SonGoku-pc7jl]

you can make a mor explication of diferences and optimitzacions cases :) thanks!

[@pavlotriantafyllides5687]

Would love an explanation of indexing and how to use this with an LLM