Why you don’t actually need a reverse ETL platform
If you set up your architecture right, you just need one, robust data pipeline system.
Data engineering
The complete change data capture guide for MySQL
A comprehensive guide to CDC in MySQL for cross-functional teams.
The complete change capture guide for PostgreSQL
A comprehensive guide to CDC in PostgreSQL for cross-functional teams.
3 reasons to rethink your approach to change data capture
As we navigate this rapidly evolving space, we should be familiar with the challenges of change data capture as it currently exists. But we should not expect them to remain the same for long.
A comprehensive introduction to change data capture (CDC)
Change data capture, or CDC, is the process of recognizing a change in a source data system so that a downstream system can act on that change, usually by updating a target system to reflect new information.
How new pipeline tools are changing data engineering in the 2020s
For the past several years, the workforce has been chronically short on data engineers. But what will happen as vendors build services that automate much of their daily work?
This article won’t tell you how to build a data mesh
Or, how to take an organization-first approach to modern data architecture
The power and implications of data materialization
The simple concept of materialization can tell us a lot about how (and why) data is stored and represented. In this post: logs and tables; data loading and queries; exports, and more.
Connector stories: Snowflake and BigQuery
Data warehouses like Snowflake and BigQuery are essential to your data stack. Today we’re talking with the two software engineers who built Estuary’s Snowflake and Bigquery connectors to get an inside look at their process.
Three data scaling pitfalls and how to avoid them
Being prepared for data scalability challenges and staying aware of best practices can help you avoid common issues.