hkdulay

Confluent's Tableflow announcement gives us a new perspective on data analytics. Stream-To-Table isn't like Farm-To-Table.

The transition from stream to table isn't clean. If you're not familiar with the Small Files Issue, this post will help you understand the nuances of this transition before you can optionally query the data.

Easy Introduction to Real-Time RAG. Learn how to build one yourself using Apache Pinot.

In this use case, we load pages from rtasummit.com and as the LLM questions.

As part of the massive shift into AI, vector databases have been increasing in popularity. Also known as vectorized databases, they play a crucial role in the context of AI, so it’s important to understand how they work. To do so, we’ll need first to understand what vectors are.

"One Big Table" (OBT) is a database design approach in which all the data is stored in a large table. There are no relations between tables in this schema, and all the information is contained within a single structure. This design simplifies the database structure, making it easy to manage and query.

Materialize and RisingWave have customers in production

The goal of this post is to describe the differences between - stream processing, real-time OLAP databases, and streaming databases. This knowledge will help you to organize and add structure to your research to enable you to make the best product decision for your real-time use case.

Getting started with a real-time analytics use case using an open source streaming database - RisingWave and Apache Pinot. Deploy using Kind and Helm charts!