Software Huddle Software Huddle

Today's episode is with Nikhil Benesch, who's the co-founder and CTO at Materialize, an Operational Data Warehouse. Materialize gets you the best of both worlds, combining the capabilities of your data warehouse with the immediacy of streaming. This fusion allows businesses to operate with data in real-time.
We discussed the data infrastructure stuff of it, how they built it, how they think about billing, how they think about cloud primitives and what they wish they had.

Today's episode is with Khawaja Shams. Khawaja is the CEO and co-founder of Momento, which is a Serverless Cache. 

He used to lead the DynamoDB team at AWS and now he's doing Memento. We talk about a lot of different things, including multi-tenancy and cellular architecture and what it's like to build on AWS and sell infrastructure products to end customers and just a lot of other really good stuff.
We hope you enjoy this episode.

01:12 Introduction
03:38 multi-tenancy
08:13 S3 and Tigris
15:09 Aurora
19:11 Momento
31:21 Cellular Architecture
41:16 Most people are doing cross-AZ wrong
52:23 Elasticsearch
01:03:08 Rapid Fire

In today's episode with Tim McNamara, we talk all about Rust. Tim is one of the leading educators in the whole Rust educational space. He wrote the Rust in Action book, which is probably the best Rust book out there. He has a YouTube channel, he taught and did a lot of educational work on Rust at Amazon AWS.
We talked about object ownership and object lifetimes and just all these interesting things that Rust has and why is this language loved by so many and why it's continuing to grow.

He also gets into what it's like being an independent educator, creator, and some of the difficulties with that, how to get started, and how he deals with doubt.

Today, we have Kent C Dodds on the show. If you don't know Kent, he's a well known expert in JavaScript, Web Development and Teaching. His courses like Testing JavaScript, Epic React, and Epic Web Dev have helped countless developers uplevel their skills and develop whole new ones.
During our conversation, we discussed how he got to start in creating courses in the background on his latest project, Epic Web Dev. We also picked his brain about JavaScript. Why the heck do we have so many JavaScript frameworks? Are we just perpetually dissatisfied with what we have? Or is there a fundamental problem with how the web is actually designed?
There's a lot of meat in the bone on this one, and we hope you enjoy it.

Show Notes:
The Web’s Next Transition
https://www.epicweb.dev/the-webs-next-transition

Epic Web Conference 2024
CONFERENCE DAY April 11th, 2024
WORKSHOP DAY April 10th, 2024
https://www.epicweb.dev/conf

Timestamps

01:46 Kent’s Background
05:38 Epic Web Dev
15:07 Creating an engaging course
19:07 How long does it take to finish the course
23:01 JavaScript and CS
25:47 Things that you should know
29:09 JS frameworks
36:28 Re-building the Web from Scratch?
42:59 PESPA Architecture
53:04 Rapid Fire

Welcome back to an episode where we're talking Vectors, Vector Databases, and AI with Linpeng Tang, CTO and co-founder of MyScale. MyScale is a super interesting technology. They're combining the best of OLAP databases with Vector Search. The project started back in 2019 where they forked ClickHouse and then adapted it to support Vector Storage, Indexing, and Search.
The really unique and cool thing is you get the familiarity and usability of SQL with the power of being able to compare the similarity between unstructured data.
We think this has really fascinating use cases for analytics well beyond what we're seeing with other vector database technology that's mostly restricted to building RAG models for LLMs. Also, because it's built on ClickHouse, MyScale is massively scalable, which is an area that many of the dedicated vector databases actually struggle with.
We cover a lot about how vector databases work, why they decided to build off of ClickHouse, and how they plan to open source the database.

Timestamps
02:29 Introduction
06:22 Value of a Vector Database
12:40 Forking ClickHouse
18:53 Transforming Clickhouse into a SQL vector database
32:08 Data modeling
32:56 What data can be Vectorized
38:37 Indexing
43:35 Achieving Scale
46:35 Bottlenecks
48:41 MyScale vs other dedicated Vector Databases
51:38 Going Open Source
56:04 Closing thoughts

Today's guest is Yujian Tang from Zilliz, one of the big players in the vector database market. This is the first episode in a series of episodes we’re doing on vectors and vector databases. We start with the basics, what is a vector? What are vector embeddings? How does vector search work? And why the heck do I even need a vector database?
RAG models for customizing LLMs is where vector databases are getting a lot of their use. On the surface, it seems pretty simple, but in reality, there's a lot of tinkering that goes into taking RAG to production.
Yujian explains some of the tripwires that you might run into and how to think through those problems. We think you're going to really enjoy this episode.


Timestamps

02:08 Introduction
03:16 What is a Vector?
07:01 How does Vector Search work?
14:08 Why need a Vector database?
15:11 Use Cases
17:37 What is RAG?
20:34 RAG vs fine-tuning
29:51 Measuring Performance
32:32 Is RAG here to stay?
35:43 Milvus
37:17 History of Milvus
47:44 Rapid Fire

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