DuckDB vs PostgreSQL: Key Differences Every few months someone asks whether DuckDB is “replacing” PostgreSQL, and the honest answer is that the question doesn’t quite make sense. They’re not competing for the same job. PostgreSQL runs your application’s backend, handling thousands of small transactions from […]
DuckDB vs SQLite: Key Differences Both of these databases share a design philosophy that sets them apart from almost everything else in the category: no server, no separate process to manage, a single file on disk, and a library you link directly into your own […]
DuckDB Tutorial for Beginners Spinning up a Postgres server, configuring a connection, and loading a CSV just to run a handful of SQL queries against it is a lot of ceremony for what’s often a five-minute analysis task. DuckDB exists specifically to remove that ceremony. […]
What Is MotherDuck and How Does It Work? Most data warehouses were built on a single assumption: your data is enormous, so your infrastructure needs to be enormous too. Snowflake, BigQuery, and Redshift all trace their design back to a world where “big data” genuinely […]
Delta Lake Architecture Explained: A Complete Guide If you’ve ever tried to run two jobs against the same S3 or ADLS folder at the same time, you already know why Delta Lake exists. Plain files in a data lake don’t know what a transaction is. […]
What Is Delta Lake? Complete Beginner’s Guide Before formats like Delta Lake existed, a “data lake” was really just a folder of Parquet or CSV files in cloud storage, and that folder had none of the guarantees you’d expect from an actual database table. A […]
Apache Hudi Tutorial for Beginners Apache Iceberg and Delta Lake both solve the “a folder of files isn’t a table” problem well, but neither one started life solving the specific problem Apache Hudi was built around: how do you continuously stream row-level changes, inserts, updates, […]
Apache Iceberg vs Delta Lake Both formats set out to solve the same problem: a folder of Parquet files in object storage isn’t a table, it has no atomic writes, no consistent view during concurrent access, and no schema guarantees. Apache Iceberg and Delta Lake […]
Apache Iceberg Architecture Explained Creating a table, inserting some rows, and running a time-travel query gets you comfortable with Iceberg’s basic shape fast. What doesn’t show up in that first hour is the machinery that makes updates and deletes actually correct under concurrent writers, why […]
Apache Iceberg Tutorial for Beginners For years, a “data lake” table meant a folder full of Parquet files and a lot of hope. There was no real schema enforcement, no way to safely have two jobs write to the same table at once, and adding […]