From Rainfall to Rows - The Butterfly Effect in PostgreSQL | CYBERTEC PostgreSQL

Table of Contents

I first came across the butterfly effect during college. You have probably heard of it, the idea that a butterfly flapping its wings somewhere could eventually lead to a tornado far away. Sounds dramatic, even mythical. But look at nature closely, and it starts making sense.

Let’s pause here.

Imagine a single droplet of rain falling into a still pond. That ripple touches another. Somewhere downstream, a leaf shifts, a beetle moves, and a bird takes off early. In that slight movement, maybe the wind catches it differently. Now zoom out, weather patterns are altered. And we are still talking about one droplet.

That was my trigger, the moment I began noticing connections. That small things, observed or not, can cause other, bigger things. It’s not superstition. It’s a language that nature speaks quietly.

When PostgreSQL Entered the Scene

Back in 2018, I was building a basic CRUD app for a college project. The stack was modern for the time as I was using Docker, AWS, and a PostgreSQL database. The focus was on deployment i.e., spin up, connect, store, retrieve. Simple.

I was more familiar with MySQL back then, but the moment I explored PostgreSQL, something felt different. It didn’t feel like a tool. It felt like a system. The more I read, the more I realized that this isn’t just a place to store rows. This is something that responds, grows, and reacts like a nervous system might.

I didn’t know it then, but I had just met a butterfly in the world of databases.

Let’s Flap Some Wings with an Interactive Example

Let’s say you are building a rainfall tracker. First, you create a simple table.

CREATE TABLE rainfall (
id SERIAL PRIMARY KEY,
city TEXT,
recorded_at TIMESTAMP,
mm NUMERIC
);

CREATE TABLE rainfall (

id SERIAL PRIMARY KEY,

city TEXT,

recorded_at TIMESTAMP,

mm NUMERIC

);

Now, insert a few rows:

INSERT INTO rainfall (city, recorded_at, mm)
VALUES
('Shillong', now(), 112.5),
('Pune', now(), 45.0),
('Bangalore', now(), 78.9);

INSERT INTO rainfall (city, recorded_at, mm)

VALUES

('Shillong', now(), 112.5),

('Pune', now(), 45.0),

('Bangalore', now(), 78.9);

So far, so good.

But let’s say your system feeds a materialized view. Maybe it calculates daily averages, and a Grafana or any dashboard somewhere picks it up.

CREATE MATERIALIZED VIEW daily_average AS
SELECT city, date_trunc('day', recorded_at) AS day, AVG(mm) AS avg_rainfall
FROM rainfall
GROUP BY city, day;

CREATE MATERIALIZED VIEW daily_average AS

SELECT city, date_trunc('day', recorded_at) AS day, AVG(mm) AS avg_rainfall

FROM rainfall

GROUP BY city, day;

Now, let’s pause.

You are a developer. You notice the Pune number seems off, maybe due to a typo, so you update it.

UPDATE rainfall SET mm = 75.0 WHERE city = 'Pune' AND recorded_at > now() - interval '1 hour';
REFRESH MATERIALIZED VIEW daily_average;

1 2	UPDATE rainfall SET mm = 75.0 WHERE city = 'Pune' AND recorded_at > now() - interval '1 hour'; REFRESH MATERIALIZED VIEW daily_average;

You think that’s it.

But somewhere,

A dashboard lights up.
A water board engineer sees the spike.
An irrigation plan changes.
A policy shifts.

All because you updated one row.

This isn’t fiction. This is how real-world systems work. And PostgreSQL gives you all the tools to let ripples travel, if you let them.

PostgreSQL as a Living System

Let’s keep imagining.

In nature,

A signal in a plant triggers a defense mechanism.
A light touch makes a Venus flytrap close.
A memory in ants helps them find their way back.

In PostgreSQL,

A TRIGGER fires on an update.
A NOTIFY event gets picked up by a listener.
A RECURSIVE query follows a parent-child pattern down a tree of relationships.
And a FOREIGN KEY .. ON DELETE CASCADE makes sure that when one row disappears, its dependents gracefully follow, just like how plucking might cause others to fall.

Here is one more butterfly you can release:

CREATE TABLE last_rainfall_recorded (

city TEXT PRIMARY KEY,

changed_at TIMESTAMP,

mm NUMERIC

);

CREATE OR REPLACE FUNCTION trace_rain()
RETURNS TRIGGER AS $$
BEGIN
INSERT INTO last_rainfall_recorded(city, changed_at, new_mm)
VALUES (NEW.city, now(), NEW.mm);

 ON CONFLICT (city)

 DO UPDATE SET changed_at = now(), mm = EXCLUDED.mm;
RETURN NEW;
END;
$$ LANGUAGE plpgsql;

CREATE TRIGGER rain_summary_trigger
AFTER UPDATE ON rainfall
FOR EACH ROW
EXECUTE FUNCTION trace_rain();

CREATE TABLE last_rainfall_recorded (

city TEXT PRIMARY KEY,

changed_at TIMESTAMP,

mm NUMERIC

);

CREATE OR REPLACE FUNCTION trace_rain()

RETURNS TRIGGER AS $$

BEGIN

INSERT INTO last_rainfall_recorded(city, changed_at, new_mm)

VALUES (NEW.city, now(), NEW.mm);

ON CONFLICT (city)

DO UPDATE SET changed_at = now(), mm = EXCLUDED.mm;

RETURN NEW;

END;

$$ LANGUAGE plpgsql;

CREATE TRIGGER rain_summary_trigger

AFTER UPDATE ON rainfall

FOR EACH ROW

EXECUTE FUNCTION trace_rain();

Now, with this butterfly, your database does not just log blindly, it remembers. Every update finds its place in a living summary.

You can literally watch the wings move, no noise, no mess. Just a ripple and recall.

Butterfly in the Planner’s Brain

Nature is a mystery, you tweak a leaf, and a breeze comes in or changes course.

PostgreSQL responds the same way, quietly but intelligently. A slight change in data, maybe just a few inserted rows or a single ANALYZE, and something deep shifts.

The planner, like a living brain, re-calculates the best route.

So, without changing the query, PostgreSQL can suddenly switch strategies from a sequential to an index scan, all because the underlying conditions changed, and it's just like you didn't rewrite the flight path, but the wind moved.

--Add new data to shift statistics

INSERT INTO rainfall (city, mm) VALUES ('Pune', 78.0);

-- Now, ask PostgreSQL to observe the table again

ANALYZE rainfall;

-- Now, watch the new plan

EXPLAIN ANALYZE

SELECT * FROM rainfall WHERE city = 'Pune';

--Add new data to shift statistics

INSERT INTO rainfall (city, mm) VALUES ('Pune', 78.0);

-- Now, ask PostgreSQL to observe the table again

ANALYZE rainfall;

-- Now, watch the new plan

EXPLAIN ANALYZE

SELECT * FROM rainfall WHERE city = 'Pune';

The same question now takes a smarter route. This is not optimization, but it’s PostgreSQL doing what nature often does i.e., quietly adapting. It does not shout its changes. It waits for the right moment.

Just like a river re-routing around a stone.

And that’s where EXPLAIN ANALYZE helps us see the shift, when we ask, not just query.

The Big Thought is - Systems Within Systems

Look around you. You might see:

A street light blinking.
A phone vibrating.
An alert that goes out.
A developer fixing a number.
A policy being changed.

The link between these things isn’t obvious, but it exists.

PostgreSQL is more than a database. It’s a network of reactions, designed to let you build systems where tiny changes lead to big truths.

So, What’s Your Butterfly?

The next time you write a query, pause for a second. Don’t rush to hit enter. Think,

Who might this affect?
What might it update?
What part of the system might shift?
And will ANALYZE change the way PostgreSQL sees the world?

Because that UPDATE, that INSERT, that TRIGGER might just be the flap that starts the storm.
Not due to chaos, but through connection.

From Rainfall to Rows - The Butterfly Effect in PostgreSQL

When PostgreSQL Entered the Scene

Let’s Flap Some Wings with an Interactive Example

PostgreSQL as a Living System

Butterfly in the Planner’s Brain

The Big Thought is - Systems Within Systems

Leave a Reply Cancel reply

Abhisek Goswami

Blog Tags

NEWSLETTER

Articles by our PostgreSQL Experts