Imagine you’re opening a bakery that becomes super popular. Sales explode. You keep track of every customer, order, and cookie baked. You start with a notebook… then move to a spreadsheet… then *finally* you get a real database. But wait—what kind of data are you storing? What’s the best way to store it?
This is where a Database Analyst comes in. One of their biggest jobs is choosing the right data types. Data types might sound boring, but they’re like the plumbing of your database. Mess that up, and things break—fast!
Why Data Types Matter
Every piece of data you store has a type. Is it a number? A word? A date? A single letter? Choosing the right one helps your system run smoother, faster, and more efficiently.
Think about it like this. Would you use a gallon jug to serve espresso? Of course not. It’s too big for the job. Similarly, you wouldn’t store a customer’s phone number as a floating-point number. It doesn’t make sense!
Let’s Talk About the Usual Suspects
Here are some common types of data and what you’d use them for:
- INT – Use this for whole numbers like counts, IDs, and scores.
- FLOAT / DOUBLE – These handle decimal numbers. Good for prices, distances, or weights.
- VARCHAR – A string of letters and numbers. Great for names, emails, or addresses.
- CHAR – Fixed-length characters. Perfect for things like country codes.
- DATE / DATETIME – Used for, well… dates and times!
- BOOLEAN – It’s either true or false. Think Yes/No, On/Off.
Each one has its strengths. But choosing wisely is key to scaling your database without issues.
Small Now, Huge Later
This is where it gets real. Let’s say you choose an INT for your customer IDs. That can store numbers up to about 2 billion. Sounds like a lot, right?
But what if you expand internationally? What if you’re processing hundreds of transactions per second? Suddenly, 2 billion doesn’t seem too far off.
So, should you always just go big? Use a bigger data type like BIGINT to be safe?
Not really. Bigger types use more space and memory. They slow things down, especially when you have millions—or billions—of rows. Pick the smallest type that can handle your data, even as you scale up.
Real World Example: E-Commerce Store
Let’s say you’re building a store like Amazon. Here’s how you might structure your data:
- User ID – Unsigned INT (no negative numbers needed)
- Email Address – VARCHAR(255). That size covers almost all possible emails.
- Order Total – DECIMAL(10,2). Accurate to two decimal places—perfect for money.
- Order Date – DATETIME
- Is Delivered – BOOLEAN (true or false)
Choosing the right types keeps the data tight. Efficient. Easy to search. Easy to understand.
The Hidden Cost of Poor Choices
Let’s say you use VARCHAR(500) for every string, just in case. That bloats your tables. Queries slow down. Indexes grow large and memory-hungry. Backups take longer. You spend more on servers.
Worse yet? You might not notice the trouble until it’s too late.
Text: VARCHAR vs TEXT
VARCHAR and TEXT both store strings, but they’re not the same under the hood. VARCHAR is stored inline—right where the other data is. It’s fast. TEXT often lives off to the side, and databases treat it differently.
Use TEXT only if you need to store essays, blog posts, or huge amounts of text.
Time to Get Precise with DECIMAL
Floating point numbers (FLOAT, DOUBLE) are fast, but they’re not always exact. Try adding up lots of float-based totals—you might find that 1.1 + 2.2 isn’t quite 3.3.
It’s not a bug; it’s how floating-point math works. For money, always use DECIMAL. It stores exact numbers with defined decimals.
Size Matters: Storage vs Performance
Here’s the balance:
- Smaller data types = faster queries, more rows in memory, less storage.
- Bigger data types = room to grow, but they slow things down.
Always estimate your maximum realistic size, then pick accordingly.
Character Sets and Collation
Characters aren’t just letters. They’re emojis, accented characters, and even scripts like Japanese or Arabic. When working globally, use UTF-8 or UTF-8-MB4.
This makes your app future-proof. And don’t forget about collation—that’s how text is sorted and compared. It affects speed and equality checks.
Scaling Tips from the Pros
Here are a few quick, pro-level tips:
- Index smartly. Indexes work better with fixed and smaller types.
- Don’t over-normalize. Too many tiny tables slow things down. Find a balance.
- Use NOT NULL wisely
- Monitor storage. See which types take the most space.
Red Flags to Avoid
Watch out for these common mistakes:
- Using TEXT for short messages
- Overusing BIGINT when INT is plenty
- Storing numbers in VARCHAR
- Using FLOAT for money
- Leaving fields as NULL when they shouldn’t be
Don’t Be Afraid to Change
You’re not stuck. If you chose a VARCHAR(1000) and realize you only ever store 50 characters—go ahead and change it. Databases evolve, and it’s okay (smart, even!) to adjust as you grow.
Final Thoughts
Choosing the right data types might seem small, but it has big consequences. It affects performance, cost, and even how your apps behave at scale.
Be thoughtful. Be precise. Start small, but plan ahead. And always test before going live.
Your future self (and your database) will thank you.