Snowflake 03: Use a catalog-linked database for Apache Iceberg tables

 

Use a catalog-linked database for Apache Iceberg tables”

 🧊 First, what is Apache Iceberg?

Iceberg is like a smart filing system for big data tables.
It keeps track of all your files, versions, and snapshots so querying data is fast and reliable.

🗂️ What’s a Catalog in Iceberg?

Think of the catalog as the master notebook where Iceberg writes:

• Where your tables are stored
• What files belong to each table
• The schema
• The table versions
• The metadata

Examples of catalogs: AWS Glue, Hive Metastore, Nessie, REST Catalog, Snowflake, etc.

🏷️ What is a catalog-linked database?

Imagine you want to organize your toys in boxes.
You don’t write directly on the toy box; instead, you write in a notebook:

• Box 1 → Cars
• Box 2 → Legos
• Box 3 → Action figures

In Iceberg, the catalog-linked database is this organized grouping inside the catalog.

It means:

Your database in Spark or Flink is connected to a catalog. All tables you create inside that database automatically become Iceberg tables managed by that catalog.

Think of it like this:

• The catalog = a big library system.
• A catalog-linked database = a section in that library, like “Kids Books”.
• Iceberg tables = the actual books.

When you create a table in that database (section):

📘 → It is automatically registered in the catalog (library system)
📚 → Iceberg manages how the data files are stored
🗂️ → Everything stays organized

So instead of you manually telling Iceberg where every book is,
the catalog-linked database takes care of that automatically.

🧐 Why do people use catalog-linked databases?

Because:

• You don’t have to specify catalog settings every time
• All tables in that database are Iceberg tables by default
• Easier to organize tables
• Cleaner project structure
• Less code and fewer mistakes