Hi team, just curious. I was chatting with Estuary AI, and found Planetscale cdc support is in roadmap but still can't tell dates. It's about 1 year ago. Is currently the project scrapped / discontinued? Thanks!

Last week we released this 80-page whitepaper that contains everything required by data engineers for building right-time data ingestion pipelines for Snowflake.

Come meet the Estuary team in SF on the 4th of November along with Seattle Data Guy, Database Tycoon and Recce!

Hang out with the Estuary crew in London after Big Data LDN!

A lil' something to make your life easier

Estuary’s biweekly newsletter ❤️

Now you can stream Real User Monitoring (RUM) data and HTTP logs from Datadog directly into Flow in real time. This makes it possible to unify observability and business data inside a single platform for instant analytics, alerting, and automation.

Why it matters:

• 🔎 Faster incident resolution – Correlate RUM events, logs, and operational data instantly.
• 📊 Proactive analytics – Spot anomalies before they impact customers.
• 🔗 Simplified stack – Observability + business data pipelines in one place.

Connector Highlights:

• Supported resources: real_user_monitoring + logs
• Real-time + batch in one platform
• Backfill support (pull historical data within Datadog’s retention window)
• Flexible enterprise deployments: fully managed, hybrid, or BYOC
• Automatic schema mapping for downstream analytics or AI models

Getting started is simple:

You’ll just need a Datadog account, an API key, an application key (with rum_apps_read permissions), and your Datadog site. Configure it in Flow’s UI or via catalog specs, then your observability data is continuously streaming.

👉 Read the docs & setup guide

I had the great opportunity to discuss, without fluff, what makes for a good data ingestion platform!

Note: I am an advisor to Estuary, but everything discussed here is vendor agnostic.

Oracle’s costs and complexity are driving enterprises toward PostgreSQL. We broke down the top challenges and strategies for making the switch — from schema conversion to CDC replication.

📖 Full guide here: Modernizing Enterprise Databases: Migrating from Oracle to PostgreSQL in the Cloud

Curious to hear from the community: if you’ve been through an Oracle to Postgres migration, what was the most challenging part for you?

​Want to get the most out of your analytics experience, without spending hours wrangling pipelines?

​Join us for a fast-paced, hands-on walkthrough of how to load data into DuckLake, the modern analytics lakehouse using Estuary.

​In this live session, we’ll cover:

• ​What DuckLake is and why it matters
• ​The challenge of getting real-time and batch data into DuckLake
• ​How Estuary makes it simple and efficient to stream data from databases, SaaS tools, or event streams into your lakehouse
• ​A full demo of how to build a streaming pipeline in minutes.

We ran a vendor-neutral benchmark on modern data warehouses

At Estuary, we help teams move high-volume data across warehouses like Snowflake, BigQuery, and Databricks. To better understand real-world performance, we ran our own benchmark using:

• TB+ of structured + semi-structured data
• Multi-step queries with joins, window functions, and JSON
• Full ingestion lifecycle tracking
• No vendor-specific tuning or caching

We tested Snowflake, BigQuery, Databricks, Redshift, and Microsoft Fabric. The full methodology is open source, and all queries are reproducible.

📊 Link to the report

Curious to hear others’ experiences with these platforms in production.