---
title: "Discussion on \"Database Sharding Explained — How Uber Stores 15 Million Rides a Day\" | Hashnode"
description: "Discussion on \"Database Sharding Explained — How Uber Stores 15 Million Rides a Day\". A backend engineer's guide to sharding strategies, real production pain points, and the Schemaless architecture that saved Uber in 2014\"\ntags: SystemD"
url: "https://hashnode.com/posts/database-sharding-explained-how-uber-stores-15-million-rides-a-day/69b844792ad6ae5184d7efa5"
---

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# [Database Sharding Explained — How Uber Stores 15 Million Rides a Day](https://how-uber-stores-15-million-rides-a-day-shubhamgore.hashnode.dev/database-sharding-explained-how-uber-stores-15-million-rides-a-day?utm_source=hashnode&utm_medium=feed)

A backend engineer's guide to sharding strategies, real production pain points, and the Schemaless architecture that saved Uber in 2014" tags: SystemD

Mar 16 · 9 min read · how-uber-stores-15-million-rides-a-day-shubhamgore.hashnode.dev  
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-   [#uber](https://hashnode.com/tag/uber)
-   [#sharding](https://hashnode.com/tag/sharding)
-   [#databases](https://hashnode.com/tag/databases)
-   [#distributed-system](https://hashnode.com/tag/distributed-system)
-   [#system-design](https://hashnode.com/tag/system-design)

## Written by

[Shubham Gore](https://hashnode.com/@shubhamagore)

@shubhamagore · Hyderabad, India

  
[View profile](https://hashnode.com/@shubhamagore)

Backend Engineer | Java · Kafka · Distributed Systems · Spring Boot

Java backend engineer with 3+ years building scalable, event-driven systems in production. I work with Spring Boot, Kafka, Elasticsearch, Redis, and MongoDB — designing real-time data pipelines, microservices, and distributed systems that handle high-throughput workloads. I write about backend engineering and distributed systems.

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