We'll talk about data storage formats, merge on read, copy on write and more. Plus, a detailed guide to software architecture documentation, how Figma overhauled their performance testing framework and more.

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Grab, a leading tech company in Southeast Asia, uses a data lake to manage its vast data, generated from services like ride-sharing and food delivery. The company uses Apache Avro with a Merge on Read strategy for high-throughput data, allowing efficient writes and periodic compaction to manage read costs. For low-throughput data, Grab uses Parquet with Copy on Write to ensure fast reads and data consistency. The post also discusses various data storage formats and their trade-offs in terms of readability, compression, and schema evolution.

The Architecture of Grab's Data Lake

Our API Could Probably Run a Small Country.