The stack.
Tools grouped by the job they do on the desk — not a badge list. The question is which layer owns a failure when the market is open.
Languages
- Python
- SQL
- C++
Python across the desk and the services. C++ on the exchange feed path, where the packet loop is hot.
Storage and caching
- ClickHouse
- Redis
- Redis Streams
- MongoDB
Column store for ticks and bars, cache for what has to be instant, streams for fan-out, document store for order and desk state.
Services and interfaces
- FastAPI
- REST
- WebSockets
- ZeroMQ pub/sub
- Django
- Binary exchange protocols
- Broker APIs
Asynchronous services with REST and socket surfaces, plus the binary and broker interfaces underneath them.
Runtime and operations
- Linux
- Docker
- Git
- Dagster
- Pipeline builds
- Structured logging
- Health checks and alerting
Containerised services on Linux hosts, orchestrated pipelines, and systems that report their own problems.
Quantitative
- NumPy
- pandas
- Options pricing and Greeks
- Walk-forward
- Market microstructure
- scikit-learn
Vectorised computation over market data, derivatives pricing, and evaluation that holds up out of sample.
Brokers and venues
- Zerodha Kite
- Motilal XTS
- IBKR
- Nuvama
- JLite
- NSE
- BSE
- NFO
- BFO
- MCX
Five broker APIs behind one interface, across cash, index and stock derivatives, and commodities.
Different layers, different tools.
The same stack read by layer — feed, store, simulation, OMS, brokers, venues — as drawn on the systems page.