🚨 Double release! Opteryx v0.25.0 and v0.25.1 just dropped—because sometimes, performance can’t wait.

v0.25.1 introduces a new optimizer for visibility filters, after we saw just how wild some of those incoming queries were. 😅

One of the worst offenders? 110 seconds down to 4. Yep, we wrote a reducer - and it reduced.

Give it a try and drop us a ⭐!
🔗 https://github.com/mabel-dev/opteryx

#OpenSource #SQL #Databases #Python #Performance #FOSS

🌀 Opteryx now speaks Vortex!

We’ve added support for the Apache Vortex file format, giving you even more ways to work with data fast.

Smaller files, faster reads, and another step toward making Opteryx a lean, mean, query engine machine. 💪

Check it out and drop us a ⭐!
🔗 https://github.com/mabel-dev/opteryx

#OpenSource #SQL #Databases #Python #FOSS #Vortex

🚀 Opteryx v0.24.0 is out today!

This release is all about performance and reliability—smoother execution, faster queries, and fewer surprises. No flashy features, just solid upgrades where it counts.

Because great engines don’t just go fast—they stay fast. ⚙️💨

Check it out and drop us a ⭐!
🔗 https://github.com/mabel-dev/opteryx

#OpenSource #SQL #Databases #Python #Performance #FOSS

📝 We don’t post on Medium often—but when we do, it’s because we’ve got something worth sharing.

Today, we’re diving into how we’ve supercharged JOIN performance in Opteryx: smarter strategies, faster execution, and some seriously nerdy wins.

Read all about it 👉 https://medium.com/opteryx/how-weve-supercharged-join-performance-in-opteryx-156de92e4678
#OpenSource #SQL #Databases #Python #Performance #FOSS #Opteryx

🚀 Opteryx v0.23 has arrived—and it’s leaving v0.22 in the dust.

We’ve overhauled join performance, and the result? Queries now run 40% faster in our internal benchmarks. That’s not just an upgrade—it’s a power-up. 💥

Smarter joins. Faster results. Same love for open source.

Give it a spin and toss us a ⭐!
🔗 https://github.com/mabel-dev/opteryx

#OpenSource #SQL #Databases #Python #Performance #FOSS

🧩 More join magic—this time, it’s LEFT JOIN’s turn

You might’ve noticed - we’ve been busy refactoring joins. CROSS JOINs got a small boost, but the real star? LEFT JOINs.

With smarter Bloom Filter prefiltering and a new approach to handling unmatched rows, our benchmarks show LEFT JOIN queries running in half the time.

Less waiting, more results.

Check it out and drop us a ⭐!
🔗 https://github.com/mabel-dev/opteryx

#OpenSource #SQL #Databases #Python #Performance #FOSS

🛠️ INNER JOIN, Reinvented

We’ve completely rewritten how Opteryx handles INNER JOINs—now with smarter Bloom Filter pre-filtering and more flexible join conditions.

On larger joins (think 10 million x 10 million rows), we’ve seen queries run in just 10% of their previous time. 🔥

Faster, leaner, and smarter where it counts.

Check it out and drop us a ⭐!
🔗 https://github.com/mabel-dev/opteryx

#OpenSource #SQL #Databases #Python #Performance #FOSS

⚔️ SEMI and ANTI joins just got a serious upgrade

We’ve rewritten their internals from the ground up—now they run about 2.5x faster. Less overhead, sharper execution, and better performance where it counts.

Fewer rows, faster joins, cleaner results. What’s not to love?

Check it out and drop us a ⭐!
🔗 https://github.com/mabel-dev/opteryx

#OpenSource #SQL #Databases #Python #Performance #FOSS

📦 CTEs are back, baby!

We’ve reintroduced Common Table Expressions (CTEs) to Opteryx—bringing back clarity, structure, and that sweet, sweet query composability.

Write cleaner SQL, break down complex logic, and nest away to your heart’s content.

Check it out and drop us a ⭐!
🔗 https://github.com/mabel-dev/opteryx

#OpenSource #SQL #Databases #Python #FOSS #CTE

🧠 We taught Opteryx to think before it ORs.

Long chains of OR conditions? Opteryx now rewrites them into smarter, more efficient predicates—a trick we call predicate compaction.

One customer saw a 100x speed-up. Not bad for a bit of clever thinking. 💡⚡

Check it out and drop us a ⭐!
🔗 https://github.com/mabel-dev/opteryx

#OpenSource #SQL #Python #Performance #FOSS #Analytics #Data