Meta

TAO: The power of the graph

TAO is Facebook's geo-distributed graph cache over sharded MySQL, serving the social graph at more than a billion reads per second.

Published
2013-06-25
Scale
over 1 billion reads/sec, millions of writes/sec
Techniques
caching geo-distribution graph data model
Stack
MySQL Memcache

Try this stack yourself

  • Railway · Deploy something like this on Railway: spin up MySQL plus your app in a few clicks. New accounts get $20 in credit (applied when you pick a paid plan).
    Railway isn't part of Meta's setup in this story. It's just an easy place to try the same building blocks.

Some links above are affiliate links: if you sign up, How They Scaled may earn a commission at no extra cost to you. We only list tools that fit the stack in the story.

See also

Meta architectureRedis vs MySQL at scalePostgreSQL vs MySQL at scale

The best scaling write-ups, weekly

One email a week. No spam.

Subscribe

Related stories

Canva · 2026

Session revocations at scale

Canva keeps 12 hours of session revocations in memory on every gateway, but hundreds of pods each loading over a million revocations from MySQL on deploy caused a stampede on the database. A worker now packs revocations into sorted 16-byte records in 30-minute chunks on S3, using conditional PUTs for optimistic concurrency and ZooKeeper leader election to avoid conflicts, and reaches over 2,000 revocations per second. Gateways binary-search the downloaded bytes directly and poll with conditional GETs, which shrank the cache by 87.5% and cut the revocation database down to two read replicas kept for redundancy.

hundreds of millions of usershundreds of thousands of session checks/seccachingobject storageoptimistic concurrency controlMySQLAmazon S3ZooKeeper
GitHub · 2026

Building Git infrastructure for agent-scale development

GitHub explains why agent workloads strain Spokes, which keeps five durable copies of each repo on fileserver disks, so every added read replica slows writes. The new design coordinates only the ref update, moves compaction and GC to separate workers, and separates storage from compute: Azure Blob Storage holds the authoritative data while lightweight caching workers serve reads.

473.3 billion Git events/month7.38 billion commits in Sept 2026control plane separationread replicascachingGitSpokesAzure Blob Storage
Zalando · 2026

Client-Side Load Balancing at a Million Requests Per Second

Zalando moved the internal fan-out of its Product Read API off the shared Skipper ingress into an in-process JVM load balancer that rebuilds the same xxHash64 consistent-hash ring. They added N-ring fade-in so new pods warm only the products they will keep, bounded load based on occupancy (Little's Law) weighted by latency, and a capped ring walk. Pods ran more evenly, the autoscaler target rose from 50% to 65% CPU, and the fleet shrank by over 25%.

1 million+ requests/sec moved off shared ingressup to 100 downstream calls per batchload balancingconsistent hashingcachingJavaKubernetesSkipper
Shopify · 2026

We replaced Redis with MySQL for inventory reservations—and it scaled

Shopify moved checkout inventory reservations from Redis to MySQL using one row per sellable unit, a bounded pool of 1,000 rows per item/location and SELECT ... FOR UPDATE SKIP LOCKED. The real ceiling was connections held by other checkout code: tagging SQL by business process and measuring hold time in ProxySQL found it, and the cleanup removed 50% of reads and 33% of transactions on the primary.

$5.1 million sales/minute (Black Friday 2025 peak)database migrationdual writesquery optimizationMySQLRedisProxySQL