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Real Time Intelligent Decision Making Using ScyllaDB - Ola Cabs' Journey

Ola Cabs is India's leading on demand ride-hailing business. Learn how they are using ScyllaDB to support various critical real time use-cases.




In the above video, Anil Yadav, Engineering Manager at Ola Cabs, shares how Ola Cabs was using ScyllaDB’s NoSQL database to power their applications.

OlaCabs began using ScyllaDB in 2016, when it was trying to solve for the problem of spiky intraday traffic in its ride hailing services. Since then they have developed multiple applications that interface with it, including Machine Learning (ML) for analytics and financial systems.

The team at OlaCabs determined early that they did not require the ACID properties of an RDBMS, and instead needed a high-availability oriented system to meet demanding high throughput, low-latency, bursty traffic.

OlaCabs’ architecture combines Apache Kafka for data streaming from files stored in AWS S3, Apache Spark for machine learning and data pipelining, and ScyllaDB to act as their real-time operational data store.

OlaCabs needs to coordinate data between both the demand of the passengers side of transactions and transportation as well as the supply-side of the drivers, matching up as best as possible which drivers and vehicles would be best suited for each route. It also makes these real-time decisions based on learning from prior history of traffic patterns and even the behavior of their loyal customers and experiences of their drivers.

Anil shared some of the key takeaways from his experiences running ScyllaDB in production.