Building a Real-Time Trading Platform with Redis

The wealth and asset management industry relies heavily on portfolios as their foundation. With the advent of modern portfolio theory by Harry Makowitz, professionals in this field have been obsessed with maximizing returns while minimizing risk. However, the landscape has changed dramatically with the entry of millions of retail investors into trading infrastructure. The GameStop stock mania is a prime example of how these new entrants can cause market volatility and pressure on brokerages to provide real-time access to prices for their clients. To tackle this challenge, Redis Enterprise, an in-memory database platform, has the potential to handle millions of operations per second with ease. This blog series will cover various real-time use cases in the financial world, including portfolio management and valuation. The first implementation records the id's of all the lots in the account using a SET, while the second model flattens the LOT entity structure and represents each attribute using keys identified by account ID. Both models have an overall time complexity of O(N+T), but Data Model B runs 4.13 ms faster due to reduced network hops. In conclusion, brokerage apps can provide real-time portfolio updates that perform and scale to handle millions of accounts with the help of Redis Enterprise. This data model and architecture can also be applied to use cases beyond securities, such as crypto and ad exchanges.