Design a system for real-time stock market data.

Question

Anonymous · Accepted Answer

Functional requirements

* Users should be able to buy/sell shares

* Users should be able to check the status of their orders

* Users should be able to check history of orders

Non functional requirements

* Low latency of 200 ms

* High Consistency of orders with no partial orders

* High volume support of 20M DAU, 1000 symbols, 5 orders per day

API endpoints

* POST /v1/orders/
   { Type: buy/sell, orderplacedat:timestamp, price:buyprice or sellprice,
   symbol:def, usermetadata }

* GET /v1/orders/:userID?fromtime=xyz&totime=abc

Workflow placing an order

User places an order -> API gateway and load balancer -> Order Service (check
valid order and enough money to buy) -> Post order details in DB (orderID,
userID, timestamp, price, symbol, status of order, metadata) and block the money
-> pushes to job queue -> order worker service picks it up, aggregates over 1
second and passes it stock exchange APIs -> stock exchange return order details
-> Order Service adds in DB (stockexchangeOrderID, other metadata) -> Order
details sent to users via websocket

Workflow order settled

Stock exchange calls webhook or via websocket -> Settlement service ->

Scaling the system

* Create a websocket layer between user-clients and order service. Use L4 WS
   gateway and routing based on userID.

* Create a websocket connection between exchange and order service. Batch
   orders from every users and every symbol in one second interval and send it
   to exchange. Reduces cost

* Order service can be scaled horizontally using consistent hashing method
   based on userID

* Kafka to be used as queue for message durability and replay in case of
   failures

* Settlement services can be scaled horizontally based on the traffic

* Create http based view historical orders and their status

Design a system for real-time stock market data.

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