Micah Wylde

@micahw.com

Co-founder arroyo.dev, building next-gen streaming systems. Prev Splunk, Lyft, Sift, Quantcast.

I built a tool called LinkedOut to solve the "links in the air" problem during my talks. It’s a serverless data lake built on the @cloudflare.social Data Platform. Ingest: Pipelines Store: R2 + Apache Iceberg Security: Access Real-time analytics with zero egress fees. Full build video below.

It's early, but I'm excited about direction that the Cloudflare Data Platform is taking. Trying to set up similar pipelines on other clouds would typically be $$$ and take tons of expertise. Managing kafka and multiple services for ingestion, compaction, etc blog.cloudflare.com/cloudflare-d...

Announcing the Cloudflare Data Platform: ingest, store, and query your data directly on Cloudflare

The Cloudflare Data Platform, launching today, is a fully-managed suite of products for ingesting, transforming, storing, and querying analytical data, built on Apache Iceberg and R2 storage.

blog.cloudflare.com

The news is finally out! Cloudflare has a Data Platform! We're starting with serverless streaming pipelines (powered by arroyo), a managed Iceberg Catalog, and a new distributed SQL engine built on top of DataFusion

Cloudflare@cloudflare.social · last yr.

The Cloudflare Data Platform, launching today, is a fully-managed suite of products for ingesting, transforming, storing, and querying analytical data, built on Apache Iceberg and R2 storage. https://cfl.re/4nHl2lk #BirthdayWeek

Cloudflare is at Snowflake Summit in San Francisco this week! Swing by our booth 2605 to chat about the new Cloudflare R2 Data Catalog and how it can make your data management and analytics easier!

Bild

You'd think that the key to being a fast streaming engine is like clever join algorithms, but it's mostly just being really good at JSON. Arroyo uses Arrow and the arrow-rs JSON decoder along with some streaming extensions. I think it's pretty cool, so I wrote up a long explanation of how it works

Fast columnar JSON decoding with arrow-rs

JSON is the most common serialization format used in streaming pipelines, so it pays to be able to deserialize it fast. This post covers in detail how the arrow-json library works to perform very effi...

arroyo.dev

Our team at Arroyo recently needed to rebuild our (very ad-hoc) analytics infra to account for our growth. We spent some time working out the best way to set up a near-real-time data lake today, and ended up with a pretty sweet approach we're calling the LOAD stack: www.arroyo.dev/blog/buildin...

Building a near-real-time data lake with the LOAD stack

The LOAD stack (log storage/object storage/Arroyo/DuckDB) makes it easy to build an affordable real-time data lake with minimal operational overhead. This tutorial will guide you through the process o...

arroyo.dev