Docstore is Uber's in-house, distributed database built on top of MySQL®. Storing tens of PBs of data and serving tens of millions of requests/second, it is one of the largest database engines at Uber used by microservices from all business verticals. Since its inception in 2020, Docstore users and use cases are growing, and so are the request volume and data footprint. The growing number of demands from business verticals and offerings introduces complex microservices and dependency call graphs. As a result, applications demand low latency, higher performance, and scalability from the database, while simultaneously generating higher workloads.

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Uber has built an integrated cache called CacheFront that improves request latencies, reduces load on the storage engine, and saves resources. CacheFront is transparent to users and helps scale the read workload on Docstore, providing high throughput and low-latency reads.

How Uber Serves Over 40 Million Reads Per Second from Online Storage Using an Integrated Cache