Why I Ditched Polygon.io and What I Found Instead

Let’s be real for a second. I used to be a big fan of Polygon.io. For a while, it felt like the right tool—decent docs, fair pricing, enough endpoints to get moving. But as my work evolved and my expectations (read: patience) dropped, I started noticing some cracks in the façade.

Some missing candles here, latency weirdness there, and then—the killer—a couple of wildly inaccurate ticks that threw off a backtest enough to make me question everything. If you've ever spent hours tuning a signal only to realize the data was the issue... yeah. You get it.

So, I did what any slightly masochistic quant would do: I went shopping for pain.
Here’s what I found.

Alpha Vantage

I wanted to like Alpha Vantage. It’s one of those platforms that looks clean, feels nice at first glance, and has an API that doesn’t make you scream into a pillow.

But oh boy—the data.

The tick data (or what passes for it) just wasn’t what I needed. Latency on responses was all over the place, and even basic intraday price series sometimes had suspicious gaps. I know some people say “it’s good enough for retail,” but let’s be honest—"good enough" doesn’t cut it when you're pushing signal edges measured in basis points.

Also, their rate limits felt a bit too tight unless you upgrade, and even then, I wasn’t blown away. End of story: I wanted clean, granular, fast data. Alpha Vantage gave me decent-ish data wrapped in a SaaS smile, but it just wasn’t enough.

Alpaca

I’ve got a soft spot for Alpaca. I really do. They make it stupidly easy to open an account, paper trade, and even integrate with some neat tools.

But as a data provider? Not my jam.

Alpaca’s market data API feels like a bonus feature rather than a primary offering—and it shows. Historical data access is okay at best, but granularity is lacking, and the depth isn’t there for serious research. The real dealbreaker, though, was quality: a few inconsistent ticks, and some missing volume data on lower liquidity names.

To be fair, if you're trading through them and want basic context—sure, it's fine. But I’m not using a broker’s side hustle for signal development. That just feels like asking your Uber driver for career advice. Sometimes you get a gem. Most times, you don't.

Alltick.co

Now this one surprised me.

I stumbled across Alltick.co almost by accident. The site didn’t scream “next-gen quant infra” or anything flashy. But something about the positioning made me curious. So I tried it. And… I kept using it.

First of all, their tick-level data is clean. Like, scarily clean. I threw my usual tests at it—backfill consistency, timestamp precision, cross-checking with exchange prints—and it passed better than anything else I’d tried.

Latency? Low.

Missing data? Practically none that I could find.

Historical depth? Solid.

API experience? Surprisingly smooth.

The pricing was reasonable, and I didn’t feel like I had to play some weird freemium upgrade game to get actual value. It just worked—and in this world, that's rarer than it should be.

Final Thoughts

Switching data providers isn’t fun. It’s like switching therapists: time-consuming, awkward, and you always wonder if you're just being too picky.

But trust me—your models are only as good as the stuff you feed them. Garbage in, garbage out, etc. We all know it, but it’s easy to forget when the APIs are "good enough."

I’m still kicking the tires on Alltick.co, but so far, they’ve earned their spot. If you’re frustrated with your current feed—or worse, you’re ignoring your data quality issues—maybe it’s time for your own little search party.

Let me know if you've found something better. Or if you've been burned by any of these too. Misery loves company, right?