Compare Epochly | vs Numba, Cython, PyPy, Mojo, Ray, Dask

The only performance tool built for production

Other tools make Python faster. Epochly makes it faster safely—with observability, rollback, and fleet-wide control that no alternative offers.

vs. Numba

JIT compiler for numerical Python

What you get: JIT compilation for numerical loops

What you give up: Works only on numerical subset. Decorators on every function. Cold-start penalty per function. Object mode fallback can be slower than plain Python.

Epochly advantage: Works on any Python code. No decorators. No cold start.

vs. Cython

Python-to-C compiler

What you get: Near-C performance for rewritten code

What you give up: Full rewrite in .pyx files. C compiler toolchain required. Cryptic build errors. Days of learning curve.

Epochly advantage: Zero code changes. No build step. No new syntax.

vs. PyPy

Alternative Python runtime

What you get: General Python speedup (~3x average)

What you give up: C extension incompatibility (PyTorch, many packages). Stuck on Python 3.10/3.11. Must replace your interpreter entirely.

Epochly advantage: CPython native. Works with every package. Latest Python supported.

Feature comparison

Getting Started

	Epochly	Numba	Cython	PyPy	Mojo	Ray	Dask
Install method	pip	pip	pip + C compiler	Binary download	Modular SDK	pip	pip
Code changes needed	None	Decorators + types	Full .pyx rewrite	None	New language	New APIs	New APIs
Time to first result	Minutes	Hours	Days	Minutes	Weeks	Hours	Hours
Works with existing code
Epochly is the only tool that requires zero changes to your existing Python code.

Safety & Risk

	Epochly	Numba	Cython	PyPy	Mojo	Ray	Dask
Progressive enhancement levels	5 levels (L0–L4)	—	—	—	—	—	—
Automatic anomaly detection
Automatic fallback to safe execution
Runtime disable without code changes
Risk rating per optimization
Zero overhead when disabled			—	—	—
Epochly is the only tool with a progressive safety model. Every other tool is all-or-nothing.

Production Operations

	Epochly	Numba	Cython	PyPy	Mojo	Ray	Dask
Built-in observability
Fleet-wide telemetry
Centralized policy control
Audit-ready telemetry
Epochly is the only single-machine performance tool with enterprise-grade observability.

Compatibility

	Epochly	Numba	Cython	PyPy	Mojo	Ray	Dask
Python version support	3.9+	3.9–3.12	Wide	3.10–3.11	—	3.9–3.12	3.9–3.13
CPython compatible
Works with all packages
Jupyter support
Docker-friendly deployment
Epochly works everywhere CPython runs, with no compatibility surprises.

Performance

	Epochly	Numba	Cython	PyPy	Mojo	Ray	Dask
Speedup without code changes	Up to 193x	—	—	~3x	—	—	—
Multi-technique (JIT + GPU + parallel)
GPU acceleration
Automatic optimization
Graceful on unsuitable code			—		—
Epochly is the only tool that delivers up to 193x speedup without touching a single line of code.

Epochly is the fastest path to faster Python. For specialized needs, combine it with Numba (numerical hot loops), Cython (maximum single-function speed), or Ray/Dask (distributed workloads). Epochly optimizes everything else—and gives you the safety net and observability that no other tool provides.

Need faster Python? Start here.

Answer these questions to find the right tool for your situation.

1. Can you rewrite your code?

Use Epochly— Zero changes required

Yes, numerical code

Consider Numba— But watch for object mode slowdowns

Yes, need max single-function speed

Consider Cython— Significant learning curve

Yes, starting fresh

Evaluate Mojo— New language, nascent ecosystem

2. Do you need distributed computing?

Yes, across machines

Use Ray or Dask— Add Epochly on each node

No, single machine

Use Epochly— No cluster infrastructure needed

3. Do you need production safety features?

Yes

Use Epochly— Only option with progressive enhancement + rollback

No, scripts/notebooks only

Epochly, Numba, or PyPy— All viable for non-production use

4. Do you need fleet observability?

Yes

Use Epochly— Only option with built-in telemetry

Any tool works— Pick based on other requirements

Use Epochly when...

You need faster Python today, not in 6 months
Your codebase is large and refactoring is not feasible
You need fleet-wide visibility into performance
Safety, rollback, and observability matter in production

Works alongside your stack

Already using Numba? Epochly optimizes everything else
Planning a Mojo migration? Get gains today while you transition
Using Ray/Dask? Epochly speeds up each worker node
Have Cython extensions? Epochly handles the pure Python

See real benchmark data