Memorystore Capacity Calculator
Size Memorystore for Redis from your dataset plus fragmentation headroom, then price replicas and high availability.
About Memorystore Capacity Calculator
Redis needs materially more memory than the dataset it holds, because fragmentation and copy-on-write during a snapshot both consume headroom — sizing to exactly the dataset is how instances start evicting keys under load. Every copy is billed, so Standard tier plus one read replica is three times the capacity charge of a Basic instance. A cache that starts evicting keys silently shifts load back onto your database, which looks like a database problem, and the fix is memory headroom rather than tuning. Confirm the GB-hour rate for your capacity tier and region in the Google Cloud pricing calculator, since the rate steps down as instances get larger.
Formula
Memorystore Capacity
provisioned GB = ceil(dataset ÷ (1 − headroom) ÷ step) × step; billable GB = provisioned × copies, where Standard counts 2 copies plus one per read replica; cost = billable GB × GB-hour price × hours.
- headroom
- Spare memory Redis needs for fragmentation, snapshots and the replication backlog
- copies
- Primary plus the Standard-tier failover replica plus any read replicas
- throughput per GB
- Network bandwidth Memorystore grants per provisioned GB, up to the tier ceiling
Worked example
With the default values below, Memorystore Capacity Calculator returns Capacity to Provision of 27.0. Change any input above and every figure here is recalculated in your browser.
Inputs used
- Working dataset sizeaccepts 0.1–10,000 GB
- 20 GB
- Headroom for fragmentation and replication buffersaccepts 0–60 %
- 25 %
- Service tierone of Basic (single node, no failover), Standard (replica in a second zone)
- Standard (replica in a second zone)
- Additional read replicasaccepts 0–5 replicas
- 1 replicas
- Price per GB-houraccepts 0–10 USD/GB-hour
- 0.054 USD/GB-hour
- Hours in the billing monthaccepts 1–744 hours
- 730 hours
- Capacity stepaccepts 0.1–16 GB
- 1 GB
- Network throughput per GBaccepts 1–500 MB/s
- 12 MB/s
- Network throughput ceilingaccepts 100–100,000 MB/s
- 16,000 MB/s
- Average value sizeaccepts 0.05–1,024 KB
- 4 KB
Results
- Capacity to Provision
- 27.0 GB
- Total Billable Capacity
- 81.0 GB
- Monthly Cost
- $3,193.02
- Billable Copies of the Data
- 3 copies
- Network Throughput
- 324 MB/s
- Keys the Dataset Holds
- 5,000,000 keys
- Cost per Usable GB
- $159.65
- Failover Behaviour
- Automatic failover to the replica in a second zone, typically under a minute
Step by step
- 1Values used
- 2Memorystore Capacity
- 3Capacity to Provision= 27.0 GB
- 4Total Billable Capacity= 81.0 GB
- 5Monthly Cost= 3,193.02
- 6Billable Copies of the Data= 3 copies
- 7Network Throughput= 324 MB/s
- 8Keys the Dataset Holds= 5,000,000 keys
Assumptions and limits
- The result is derived only from the 10 inputs listed above. Anything not among them is not part of the calculation.
- In particular, this calculator does not take inflation, tax, fees or charges or compounding frequency into account.
- Figures are rounded for display to 2 decimal places, so totals built from several rounded parts can differ slightly from the unrounded arithmetic.
How these calculators are built and tested is described on the Methodology page. If a figure looks wrong, please report it.
Frequently Asked Questions
How is Memorystore Capacity calculated?
provisioned GB = ceil(dataset ÷ (1 − headroom) ÷ step) × step; billable GB = provisioned × copies, where Standard counts 2 copies plus one per read replica; cost = billable GB × GB-hour price × hours. Redis needs materially more memory than the dataset it holds, because fragmentation and copy-on-write during a snapshot both consume headroom — sizing to exactly the dataset is how instances start evicting keys under load. Every copy is billed, so Standard tier plus one read replica is three times the capacity charge of a Basic instance.
Why does Memorystore Capacity matter?
A cache that starts evicting keys silently shifts load back onto your database, which looks like a database problem, and the fix is memory headroom rather than tuning. Confirm the GB-hour rate for your capacity tier and region in the Google Cloud pricing calculator, since the rate steps down as instances get larger.
What values do I need to enter?
This calculator takes 10 inputs: Working dataset size, Headroom for fragmentation and replication buffers, Service tier, Additional read replicas, Price per GB-hour, Hours in the billing month, Capacity step, Network throughput per GB, Network throughput ceiling, Average value size. The pre-filled defaults are a realistic starting point — replace them with figures from your own environment for a result you can act on.
Is a read replica a substitute for high availability?
No. Read replicas scale read throughput; automatic failover comes from the Standard tier. A Basic instance with no replica loses its entire dataset on a node failure and every request falls through to the origin datastore until the cache is warm again.