The Netflix Sample Database is a learning database based on public data from Netflix’s Engagement Report and Global Top 10 lists. This article walks through the steps involved when installing it on Oracle Database.
For more background on this database, check out Getting Started with the Netflix Sample Database.
The Netflix sample database is a learning database based on public data from Netflix’s Engagement Report and Global Top 10 lists. This guide walks you through installing it on PostgreSQL.
For more background on this database, see my introduction to the Netflix Sample Database.
Oracle Database 26ai has officially landed. As of January 27, 2026, Oracle finally flipped the switch on the General Availability (GA) for the Linux x86-64 version, bringing the “Enterprise Edition” to data centers everywhere. This marks a major turning point in Oracle’s recent rebranding saga, where the anticipated “23ai” was bumped up to 26ai to signal its role as the long-term support (LTS) foundation for the AI era.
Oracle Database has been a powerhouse in enterprise environments for decades, and the new “AI” branding reflects their recent addition of AI-powered features like vector search.
If you’re learning SQL or looking for a real-world dataset to sharpen your database skills, the Netflix sample database could be an option. This free, open-source database is based on publicly available information from Netflix’s Engagement Report and Global Top 10 weekly lists, making it both relevant and engaging for practice purposes.
Common Table Expressions (CTEs) are a handy way to break down a complex query into readable, reusable pieces. When you need several intermediate results – say, a filtered set, an aggregation, and a ranking – you can stack multiple CTE definitions together. PostgreSQL, SQL Server, MySQL 8+, and many other engines support this syntax.
Prepared statements are a precompiled SQL queries that we can execute multiple times with different arguments. They are limited to the current session, so we can only create them and run them from within the same session.
Sometimes we might want to review how many prepared statements we’ve created. Or we might need to deallocate one, but we’ve forgotten its name.
No problem. We can use the pg_prepared_statements view to see all of our prepared statements.
The SERIAL data type in PostgreSQL is a pseudo-type used to create an auto-incrementing sequence of integers for a column. It is commonly used for primary keys, as it eliminates the need to manually assign unique identifiers for each new record. PostgreSQL handles this by automatically creating a sequence object that supplies a unique number each time a new row is inserted.
PostgreSQL provides three SERIAL types, each with two options for usage; which effectively equates to six different types. So basically, we have six options to choose from when creating a SERIAL column.
When a foreign key is defined in a table, it ensures that the values in the column(s) correspond to values in a primary key or unique key in another table. While PostgreSQL automatically creates an index for primary keys (because these need to be fast for lookups and enforcing uniqueness), it does not automatically create an index for foreign keys.
There are several ways that we can list all indexes in PostgreSQL. These include utilizing various system catalog views and psql commands. Below are five options for returning a list of indexes in PostgreSQL, along with examples of how to filter the results by index name, table name, and other criteria.
If you’ve been working with prepared statements in PostgreSQL, you may get to a point where you no longer need one or more of them. In that case, you might want to remove them, or delete them, drop them, or however you want to say it.
Fortunately, this is one of the quickest, easiest things to do in PostgreSQL.