How to organize the architecture of a table that grows rapidly for fast operation only with fresh data? How to efficiently delete old data?

For tables that grow quickly and where fast access to fresh data is important, the following approaches are usually used:

1. Partitioning the table by date — splitting the table into partitions, for example, by days or months. This allows quick access only to the relevant partition with current data, and old partitions can be easily deleted or archived.

2. Using indexes on date columns to speed up queries on recent data.

3. Archiving old data — moving outdated data to separate archive tables or databases so that the main table remains compact.

4. Deleting old data through partitions — if the table is partitioned, deleting old data reduces to deleting entire partitions, which is much more efficient than deleting by condition.

Example of partitioning in PostgreSQL:

CREATE TABLE events (
    id SERIAL PRIMARY KEY,
    event_time TIMESTAMP NOT NULL,
    data TEXT
) PARTITION BY RANGE (event_time);

CREATE TABLE events_2024_06 PARTITION OF events
    FOR VALUES FROM ('2024-06-01') TO ('2024-07-01');

-- To delete old data, simply drop the partition
DROP TABLE events_2024_05;

This approach allows quick work with current data and efficient management of old information.