Apache Parquet
ELI5 - The Vibe Check
Parquet is a file format that stores your data by column instead of by row, which sounds boring until you realize most analytics queries only touch a handful of columns out of fifty. Instead of dragging the whole row off disk to read one field, Parquet lets you grab just the columns you need, compressed hard, which is why it's the default file format for basically every modern data pipeline.
Real Talk
Apache Parquet is an open-source columnar storage file format optimized for analytical workloads. It stores data column by column with efficient compression and encoding, letting engines skip irrelevant columns and row groups entirely, which dramatically speeds up scan-heavy queries compared to row-based formats like CSV or JSON.
When You'll Hear This
"Dump the raw events to Parquet before loading them into the warehouse." / "Querying Parquet directly with DuckDB is faster than I expected."
Related Terms
Apache Iceberg
Imagine a giant folder of Parquet files that used to be pure chaos, nobody knew which files were current, nobody could add a column safely, and two people...
ClickHouse
Imagine filing cabinets where instead of storing one person's whole file together, you store ALL salaries in one drawer, ALL names in another.
Data Lake
A data lake is a massive storage dump where you throw every piece of data in its raw format. CSV files, JSON, images, logs, whatever.
DuckDB
DuckDB is like SQLite's nerdy data analyst sibling. Instead of handling web app transactions, it's built for crunching numbers — analytical queries on mill
OLAP
OLAP is all about analyzing huge amounts of data to answer business questions. 'What were total sales by region last quarter?' That's an OLAP query.