65 articles on database — what drives the cost, how it is priced, and where the savings actually are.
The function is cheap, the database it talks to often is not. Connection limits, proxies, and idle capacity turn a per-request compute model into a per-hour database bill. Here is how to pair them well.
A managed proxy bills per vCPU-hour of the database it fronts. A self-hosted pooler bills as a small container. Both let you run a smaller database instance, which is where the real money is. Here is the arithmetic.
A read replica is a full copy of your database with a full copy of its price. A cache node is a fraction of that. The choice comes down to hit ratio, data freshness, and how many distinct queries you are serving. Here is the cost-per-read math.
The per-hour rates for managed MySQL and PostgreSQL are nearly identical on every major cloud. The cost difference shows up somewhere else entirely: in how each engine uses storage, connections, and replication. Here is where it actually lands.
Atlas M30 costs about $394 per month. The same three-node replica set on EC2 costs about $230 in instances. The $164 gap is not the whole story, and for most teams it is not even the important part. Here is the full accounting.
Storage autoscaling grows your database disk automatically and never shrinks it. A one-off bulk load can leave you paying for terabytes you deleted years ago. Here is how the ratchet works and what it costs.
io2 Block Express charges $0.065 per provisioned IOPS per month on top of storage. Provision 40,000 IOPS and you have added $2,600 to the monthly bill before a single byte is stored. Here is when that is the right call.
PITR is billed on change volume, not database size, which is why a small write-heavy database can cost more to back up than a large static one. Here is how the meters work across AWS, Azure, and GCP.
Manual snapshots never expire. Every pre-migration safety copy taken over five years is still billing. A typical mid-sized account holds hundreds of gigabytes of snapshots nobody could name the purpose of.
HA doubles compute and storage on every major cloud, so the question is not whether availability is good but what outage cost the second node avoids. Here is how to do that arithmetic honestly.
CPU utilization alone is a bad sizing signal for databases, because the binding constraint is usually memory or connections. Here is a four-signal method that produces a defensible instance choice instead of a guess.
Serverless databases promise you pay only for what you use, but most of them have a floor. Understanding the minimum capacity charge is the difference between a $5 development database and a $44 one.
Autovacuum tuning is usually framed as a performance topic. It is also a storage bill: dead tuples on a ratcheting volume become permanent cost, and a badly tuned vacuum can add 40 percent to your database size.
Adding an index that turns a sequential scan into a lookup can remove more load than doubling your instance size, and it costs one afternoon rather than $378 a month forever. Here is how to find the queries worth fixing.
Indexes routinely occupy more space than the tables they serve, and a bloated or duplicated index set can be half your database volume. Here is how to measure it and what removing it is worth.
A migration is not a one-line move. You pay for both databases in parallel, for replication tooling, for cross-region transfer, and for the oversized target you provisioned to be safe. Here is a budget that holds.
Non-production databases often outnumber production ones five to one and run identical configurations. Scheduling, sizing, and sharing them typically cuts that spend by 70 to 85 percent with no impact on anyone's work.
RDS storage autoscaling prevents out-of-space outages by growing your volume automatically, and the feature itself is free. The catch is that it never shrinks, so a one-time spike can leave you paying for oversized storage for the life of the instance. Here is how to use it without the ratchet.
RDS gp3 gives a free IOPS and throughput baseline for a flat per-GB price, while io1 charges separately for every provisioned IOPS. For most databases gp3 is dramatically cheaper. Here is the pricing, the break-even, and when io1 still earns its cost.
RDS Reserved Instances cut the hourly rate of a database by up to about 40 percent for a one-year term and 60 percent for three years, in exchange for a commitment. Here is how the payment options compare, where the size-flexibility applies, and how to avoid over-committing.
Aurora Global Database gives sub-second cross-region replication and fast disaster recovery, but it bills replicated write I/O, storage in every region, secondary instances, and cross-region transfer. Here is the full cost breakdown and how to keep a global database from multiplying your bill.
A DynamoDB Global Secondary Index has its own throughput and storage, and every write to the base table that touches indexed attributes is also billed against the GSI. Here is how GSI cost works, why projections matter, and how a few indexes can double your write bill.
DynamoDB offers on-demand backups, point-in-time recovery, and S3 exports, each priced differently. Here is what each costs per GB, when continuous backup is worth double the on-demand rate, and how restores and exports are billed.
DynamoDB Accelerator (DAX) is a managed in-memory cache that can cut read latency to microseconds and read cost on hot data, but it runs on always-on nodes with a three-node minimum for production. Here is what DAX costs and the read volume where it starts to pay for itself.