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Compare crypto trading infrastructure

Disclosure up front: we build godzilla.dev, which appears in the table below. This page is not a ranking and we have not tried to make one — we do not think anyone can credibly rank their own project. What follows is a decision framework: the attributes that actually separate these tools, the same facts for every entry, and an explicit statement of which workloads each one is wrong for, including ours.

Every figure below comes from a public source — repository metadata, licenses, published documentation — and is dated. Where we do not know something, the cell says so rather than guessing.

How to read this table

These five projects are not substitutes for each other. They sit at three different layers:

  • CCXT is a library. It gives you a unified API across exchanges. You still write the system.
  • Freqtrade, Hummingbot, and NautilusTrader are frameworks. They give you a strategy runtime, backtesting, and connectors.
  • godzilla.dev is execution infrastructure for a narrow set of strategies. It gives you a short, auditable, process-isolated path from market data to order, and much less of everything else.

Picking the wrong layer is a more expensive mistake than picking the wrong project within a layer.

The matrix

Repository figures as of September 2026.

godzilla.dev Hummingbot Freqtrade NautilusTrader CCXT
Best for Funding rate arbitrage and market making where the local execution path is the constraint Individual traders who need many venues, including DEXs Backtest-driven retail algo trading with a large indicator/ML toolkit Event-driven systems needing backtest-to-live parity across asset classes Building your own system on a unified exchange API
Layer Execution infrastructure Framework Framework Framework Library
Language C++ core, Python strategies (pybind11) Python (some Cython) Python Rust core, Python API TS / Python / C# / PHP / Go / Java / Rust
License Apache 2.0 Apache 2.0 GPL 3.0 LGPL 3.0 MIT
Self-hosted / non-custodial ✅ Yes ✅ Yes ✅ Yes ✅ Yes ✅ Yes
Exchange coverage ⚠️ Small — Binance spot and perpetuals in the public repository; more in enterprise deployments ✅ 300+ connectors, CEX and DEX ✅ Broad, via CCXT ✅ Major crypto venues plus traditional-market adapters ✅ 100+ exchanges — the widest of any entry here
DEX support ❌ No, and none planned ✅ Yes, via Gateway ⚠️ Limited ⚠️ Selected venues ✅ Yes
Published reproducible latency measurement ✅ Yes — methodology, scripts, raw event records, and stated limitations, all public ❌ None we are aware of ❌ None we are aware of ⚠️ Component micro-benchmarks in the repository; no published end-to-end methodology with raw records that we are aware of ➖ Not applicable — a library, not an execution path
Community size (GitHub stars) ⚠️ ~0.4k ~20.0k ~54.3k ~28.8k ~44.0k
First public release 2025 2019 2017 2018 2017
Commercial model Enterprise private deployment and support contracts Foundation, exchange partnerships, HBOT token governance Community open source Open source, Nautech Systems Open source library, commercially supported integrations

Two rows deserve comment because they cut in opposite directions.

The latency row is the one place godzilla.dev is unambiguously ahead, and it is worth being precise about why: not because the others are slow, but because nobody publishes the measurement. A ✅ here means the event boundaries, the workload, the hardware, the raw per-event records, and the list of excluded factors are all public and re-runnable. Our benchmark measures a single-host software path only — no network, no exchange, no fills — and says so at length. If any of the other projects publish a comparable artifact, send it to us and we will update this row.

The community and coverage rows are the places godzilla.dev is unambiguously behind, by an order of magnitude or more. For most people reading this page, those rows matter more than the latency row.

Which one should you choose?

Choose CCXT if you are building your own execution system and want venue normalisation without inheriting someone else's runtime.

Choose Freqtrade if you are an individual trader whose main activity is researching and backtesting directional strategies, and whose fills are not the hard part.

Choose Hummingbot if you are new to algorithmic crypto trading, if you need DEX venues or long-tail exchanges, or if you value a large community over anything else. This is the right answer for most individuals. We wrote a detailed Hummingbot comparison that includes the places Hummingbot beats us.

Choose NautilusTrader if you need one event-driven engine spanning crypto and traditional markets with the same code running in backtest and live.

Choose godzilla.dev only if you are in a narrow band: funding rate arbitrage or market making, on major centralized venues, where you leg in near settlement or quote both sides all day, and where you need the system running inside your own infrastructure with support. If you are not sure whether internal latency is your constraint, it almost certainly is not — and your network path to the exchange will dominate it anyway unless you are co-located.

What we deliberately did not do on this page

  • We did not rank these projects. A vendor-authored ranking with the vendor at the top is not evidence of anything.
  • We did not compare performance across frameworks. A fair cross-framework latency benchmark needs pinned versions, identical workloads and strategy semantics, disclosed tuning on both sides, and independent review. Nobody has done that study. We would co-design one.
  • We did not score anything out of ten. Composite scores hide which attribute did the work.

Individual comparisons

More comparisons are in progress: Freqtrade, CCXT, NautilusTrader, and build-versus-buy for teams deciding whether to write their own market data, execution, and risk stack.