Stripe’s Post

Ever wondered how Stripe maintains 99.999+% availability? Our internal Database as a Service system handles version upgrades, resharding, and more while ensuring consistency without any downtime. Check out our latest blog post to lean!

It's amazing to watch a plan come together! This article details the world class engineering work that my Document Database teams have been working on. Five nines (99.999%) of reliability with zero-downtime data migrations supporting $1T+ in payments volume. Totally EPIC! https://lnkd.in/eKJRhYsY

Interesting - another complex proxy layer built in house. Reminds me a bit of the recent Figma blog about their Postgres sharding. And I've seen lots of other companies do it too - even with Oracle for data persistence. I have mixed feelings about this. I wonder if simpler solutions would suffice in many cases, like multiple parallel full app stacks each with a single HA database setup, but not trying to support all the flexibility of a "platform" that's managed more like a single large distributed system. Seems like adding a lot of complexity to the code base you own and maintain, mainly for more sophisticated cross-shard queries and rebalancing. Rebalancing processes and cross-shard query capabilities that are more manual might be ok, in exchange for a much simpler stack.

Customers and businesses now expect payments to be processed immediately! 💳 In 2023 Stripe processed $1 trillion in payments—all while maintaining 99.999% uptime with zero-downtime data migrations. Check out this blog post that explores how Stripe’s DocDB, an extension of MongoDB Community, expertly manages enormous amounts of real-time data at scale. ⬇️ https://lnkd.in/gbDsDXYH #database #documents #data

Database systems lie at the heart of almost all modern applications, and managing data transactions within these systems is a crucial aspect of software engineering. Database transactions are handled using two widely-used models: ACID and BASE. ACID (Atomicity, Consistency, Isolation, Durability) is used where data consistency and reliability are critical, like in banking systems. It ensures all database operations are reliably processed, but it might impact performance and scalability. BASE (Basically Available, Soft State, Eventual Consistency) is used where scalability and performance are more important than immediate consistency, like in large-scale distributed systems. It provides high availability and performance, though it may not guarantee immediate data consistency. AWS Lambda, Node.js, and PostgreSQL can be used to build ACID-compliant applications, while AWS Lambda, Node.js, and DynamoDB can be used for BASE model applications. Choosing between ACID and BASE depends on your application's specific needs for consistency, performance, and scalability. Source: https://lnkd.in/g8XnfzvD #databasetransactions #acid #base #database

<!-- Above-the-toolbox --> (adsbygoogle = window.adsbygoogle || []).push({}); Mastering Database Scalability: Strategies for Seamless Growth Mastering Database Scalability: Strategies for Seamless Growth Introduction In today’s data-driven world, databases play a crucial role in storing and managing vast amounts of information. As businesses grow and

This post will walk you through the steps used to manually #shard, scale, and - in so doing – completely break a #Postgres #database. In contrast to this, #CockroachDB takes the pain out of #scaling and gives you operational efficiency! Check out more details here: https://lnkd.in/gvHyNKgi

Our recent customer success story with YNAB details how they optimized their Postgres database performance and reduced costs with Crunchy Bridge. Read more to learn about why those chose to work with us over other vendors. https://lnkd.in/e4XCNFz4

Customers and businesses now expect payments to be processed immediately! 💳 In 2023 Stripe processed $1 trillion in payments—all while maintaining 99.999% uptime with zero-downtime data migrations. Check out this blog post that explores how Stripe’s DocDB, an extension of MongoDB Community, expertly manages enormous amounts of real-time data at scale. ⬇️ https://lnkd.in/e6JZV3Xi

🔔Big feature alert!🔔 A lot of the world today shards their #MySQL backends because it’s what they know. It has been standard for scaling transactional data workloads for quite a while. It can be very annoying to do that, but worse, it’s the underlying cause of a ton of tech debt. We talk a lot about using #NewSQL to avoid the complexity of sharding. We even go so far as to propose combining workloads into the same database. In this blog, I want to discuss in more detail the new feature that supports that proposal: Resource Control. https://lnkd.in/gF5vWRuk