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 caching solution called CacheFront for their in-house distributed database called Docstore. CacheFront helps Uber serve over 40 million reads per second from online storage, overcoming challenges such as low-latency read access, high scalability, and cost efficiency.

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

<p>I really enjoy Uber blogs like this about the “distributed systems” they build and the problems they solve. Not many companies share this kind of experience and problem-solving about their Eng channels. Good read.</p>
