1. They mention that the largest tables ran into several TBs, and they would have soon topped the max IOPS supported by RDS. RDS for PostgreSQL peaks at 256,000 IOPS for a 64 TB volume. For a multi-AZ setup, this costs ~$70K/mo.
2. Let's assume the final outcome was a 5-way shard with each shard supporting ~50,000 IOPS and ~12 TB data. For a multi-AZ setup, this costs ~$100K/mo.
3. It took 9 months to shard their first table. Since it required application changes as well, let's assume this was 9mo * 20 work days/mo * (3 DB engineers + 2 app engineers) = 900 work days. Even at $100K avg. annual pay for an engineer, this is ~$400K.
4. A PostgreSQL-compatible NewSQL like YugabyteDB should cost ~$15K/mo to match top-of-the-line RDS performance. So Figma spent ~25x ($400K/$15K) to implement horizontal sharding in-house, and is still on RDS which costs ~6x ($100K/$15K)
2. Let's assume the final outcome was a 5-way shard with each shard supporting ~50,000 IOPS and ~12 TB data. For a multi-AZ setup, this costs ~$100K/mo.
3. It took 9 months to shard their first table. Since it required application changes as well, let's assume this was 9mo * 20 work days/mo * (3 DB engineers + 2 app engineers) = 900 work days. Even at $100K avg. annual pay for an engineer, this is ~$400K.
4. A PostgreSQL-compatible NewSQL like YugabyteDB should cost ~$15K/mo to match top-of-the-line RDS performance. So Figma spent ~25x ($400K/$15K) to implement horizontal sharding in-house, and is still on RDS which costs ~6x ($100K/$15K)