Comparing Cryptofeed and XChange Libraries
| Library | Language | Primary Use | Highlights |
|---|---|---|---|
| Cryptofeed | Python | Real-time market data + trading via unified async interface. | WebSocket aggregation, order-book verification, optional Redis/Kafka sinks, CCXT trading adapter. |
| XChange (Knowm/XChange) | Java | Unified REST/WebSocket client for exchanges. | Mature since 2012, integrates with JVM stacks (Spring, Vert.x), supports REST trading, streaming adapters. |
When to Choose Cryptofeed
- You build Python-based trading bots, research pipelines, or data capture services.
- Need out-of-the-box order-book depth, funding, and liquidation channels across >70 exchanges.
- Prefer asyncio and plug-ins for writing directly to databases/message buses.
Example (Python):
from cryptofeed import FeedHandler
from cryptofeed.exchanges import Coinbase
async def handle_book(book, receipt_timestamp):
best_bid = book.book.bids.index(0)
best_ask = book.book.asks.index(0)
print(best_bid, best_ask)
fh = FeedHandler()
fh.add_feed(Coinbase(symbols=['BTC-USD'], channels=['l2_book'], callbacks={'l2_book': handle_book}))
fh.run()
When to Choose XChange
- You run on the JVM and need a unified interface for spot/derivatives REST APIs.
- Integrate with enterprise Java stacks, Spring Boot microservices, or Kafka-based ingestion.
- Require fine-grained control over rate limiting, authentication, and retry policies in Java.
Example (Java):
Exchange exchange = ExchangeFactory.INSTANCE.createExchange(CoinbaseProExchange.class);
MarketDataService dataService = exchange.getMarketDataService();
Ticker ticker = dataService.getTicker(CurrencyPair.BTC_USD);
System.out.println(ticker.getLast());
Selection Tips
- Mix both when you need Python analytics but enterprise JVM backends—Cryptofeed for capture, XChange for order execution via microservices.
- Monitor API deprecations; crypto exchanges change endpoints frequently.
- Always respect exchange rate limits and local regulations when trading or capturing data.