What are the core architectural differences between a crypto trading bot and a custom-built one?
I've been researching automated crypto trading bot development and trying to understand the technical trade-offs between white-label solutions and custom-built bots from scratch. From what I've read so far, white-label bots come pre-built with: Multi-exchange API connectivity (Binance, Bybit, OKX, KuCoin, Kraken etc.) Pre-configured strategies like grid trading, DCA, and scalping Built-in backtesting engines AML/KYC compliance layers Risk management modules (stop-loss, smart order routing) Whereas custom bots built from scratch typically use stacks like: Python for ML/quant strategies Go or C++ for low-latency execution engines Node.js for real-time WebSocket handling TimescaleDB or InfluxDB for time-series price data Apache Kafka for high-throughput event streaming I came across this detailed breakdown on crypto trading bot development which covers the architecture, bot types, AI/ML integration, and cost tiers, but I still have some specific technical questio...