How Discord Stores Trillions of Messages

Have you ever thought about how Discord delivers messages instantly, supports real-time search, and processes trillions of messages without slowing down? With more than 150 million monthly active users, Discord has had to continuously redesign its backend to remain fast, scalable, and dependable. This is the story of how its engineering team transformed message storage to meet massive scale.

What Is Discord?

Discord is a cloud-based communication platform that combines text messaging, voice calls, video calls, and community management into a single application.

At its core, Discord is built around servers (private or public spaces), which are divided into channels for different topics or purposes:

Text channels for persistent chat
Voice channels for real-time conversations
Media sharing, bots, and integrations

Unlike traditional messaging apps that focus on one-to-one conversations, Discord is designed for many-to-many communication at massive scale.

How Discord Works (In Simple Terms)

Servers: Independent communities (public or private)
Channels: Topic-based conversations inside servers
Roles and permissions: Fine-grained access control
Persistent messages: Conversations do not disappear unless deleted
Real-time and asynchronous communication

Every message sent in Discord is stored, indexed, and retrievable—sometimes years later. This design choice is key to why Discord has accumulated trillions of messages globally.

So why Discord can store trillion of messages: Understand the first database MongoDB

In its early stages, Discord relied on MongoDB to store chat messages. At first, it performed well. But as servers grew larger and message volumes exploded, limitations quickly emerged.

Picture a single server with hundreds of active users sending messages nonstop. Now multiply that scenario across thousands of servers worldwide. Eventually, MongoDB struggled to handle the growing write volume and indexing demands.

To overcome this, Discord migrated to Apache Cassandra — a distributed NoSQL database designed for fault tolerance and horizontal scaling. Cassandra enabled data to be spread across many machines, allowing Discord to process far more messages reliably.

Also see: Dify AI for SaaS: Automating Customer Interactions at Scale

Scaling Cassandra: Power at a Cost

By 2022, Discord’s infrastructure was managing more than 4 trillion messages across 177 Cassandra nodes — essentially a massive digital library with shelves spread across data centers.

However, the system came with trade-offs:

Inconsistent response times, particularly during traffic spikes
Operational complexity, as data rebalancing could take hours or even days
Poor storage efficiency, caused by compaction overhead and disk waste

While Cassandra delivered resilience, it became increasingly expensive and difficult to operate at Discord’s scale.

ScyllaDB: Familiar Interface, Faster Core

Discord eventually adopted ScyllaDB, a database compatible with Cassandra’s API but built in C++ instead of Java. This architectural shift brought major performance benefits:

No garbage collection pauses
Better CPU and memory utilization
Lower and more predictable latency

It was like swapping out an aging engine for a high-performance alternative — same controls, dramatically better output.

After the transition:

The cluster size dropped from 177 nodes to just 72
95th-percentile read latency improved by ten times
Write performance improved by roughly 50 percent

Intelligent Middleware with Rust

To further optimize performance, Discord introduced a Rust-based middleware layer that acts as a smart message router.

This layer:

Combines multiple identical requests into a single query
Temporarily caches frequently accessed data
Automatically retries and routes failed requests

By reducing redundant queries and preventing traffic spikes on popular partitions, this system significantly lowered database load and improved reliability.

Custom Storage: Built for Speed and Safety

ScyllaDB depends heavily on fast disk I/O, so Discord engineered custom “super disks” using optimized RAID configurations:

RAID 0 for high throughput
RAID 1 for redundancy

This setup delivered fast reads for real-time messaging while ensuring data protection if a drive failed.

In addition, Discord adopted Zstandard compression, cutting disk usage by 50–60 percent without sacrificing data integrity.

Migrating Trillions of Messages — Live

Transitioning to ScyllaDB meant moving hundreds of terabytes of live data while keeping Discord fully operational.

To achieve this, the team:

Built a custom data migration tool in Rust
Migrated data while continuing to serve live traffic
Verified accuracy using checksums
Rolled out the change incrementally rather than all at once

The entire migration — covering more than 4 trillion messages — was completed in just nine days, with no downtime.

The Results: Faster, More Efficient Messaging

Following the migration

Overall system stability improved significantly
Read and write latencies dropped
Message storage became more cost-efficient and scalable

Most importantly, users never noticed the transition — messages continued to flow seamlessly.

Quick Summary

MongoDB → Cassandra → ScyllaDB
Rust middleware enabled smarter request handling
RAID storage and compression boosted performance and efficiency
Over 4 trillion messages migrated in nine days with zero downtime

Conclusion

Discord’s message storage overhaul is a standout example of real-world systems engineering. Instead of simply adding more hardware, the team rethought their architecture, built purpose-driven tooling, and removed bottlenecks using modern technologies like ScyllaDB, Rust, and C++.

For anyone building at scale, the lessons are clear:

Choose technologies that grow gracefully with both performance and team productivity
Invest in abstraction layers that reduce complexity
Continuously measure, refine, and optimize