Understand Cloud Spanner performance

This page describes the approximate performance that Cloud Spanner can provide under optimal conditions, factors that can affect performance, and tips for testing and troubleshooting Spanner performance issues.

Performance for typical workloads

Spanner's throughput is linearly scalable with the number of nodes. Each node (1,000 processing units) of compute capacity in a Spanner instance can provide the following approximate throughput (Queries per second) based on the instance configuration:

Instance Configuration Type Peak Reads (QPS per region)   Peak Writes (QPS total)
Regional 15,000 or 2,300
Multi-Region (Breakdown by base config) 10,000 or 1,800

Read guidance is given per region (because reads can be served from any read-write or read-only region), while write guidance is for the entire configuration. Read guidance assumes you're reading single rows of 1KB. Write guidance assumes that you're writing single rows at 1 KB of data per row.

In general, both the read and write throughputs of a Spanner instance scale linearly as you add more compute capacity (nodes or processing units) to the instance. For example, if a single-region Spanner instance with 2 nodes can provide up to 30,000 reads per second, then a single-region Spanner instance with 4 nodes can provide up to 60,000 reads per second.

If you are not seeing desired performance for your workload from Spanner, see troubleshooting performance regressions for information about common causes.

Performance for regional configurations

At 100% CPU utilization, each 1,000 processing units (1 node) of compute capacity can support up to 15,000 reads per second or 2,300 writes per second (reads and writes are both at 1KB per row). Each optional read-only replica can support an additional 5,000 reads per second.

Performance for multi-region configurations

Each Spanner configuration has slightly different performance characteristics based on the replication topology.

Each 1,000 processing units (1 node) of compute capacity can provide the following peak performance (at 100% CPU):

Base Configuration Name Approximate Peak Reads (QPS per region) Approximate Peak Writes (QPS total)
asia1 10,000 1,800
eur3 10,000 1,800
eur5 10,000 1,800
eur6 10,000
5,000 for each optional read-only replica
1,800
nam3 10,000
5,000 for each optional read-only replica
1,800
nam6 10,000 in us-central1 and us-east1
5,000 in us-west1 and us-west2 [1]
1,800
nam7 10,000
5,000 for each optional read-only replica
1,800
nam8 10,000 1,800
nam9 10,000 1,800
nam10 10,000 1,800
nam11 10,000
5,000 for each optional read-only replica
1,800
nam12 10,000 1,800
nam13 10,000 1,800
nam-eur-asia1 10,000 1,000
nam-eur-asia3 10,000 1,000
  • [1]: us-west1 and us-west2 provide only half of the QPS performance because they contain one replica per region instead of two.

Read guidance is given per region (because reads can be served from anywhere), while write guidance is for the entire configuration. Read and write guidance assume that you're reading and writing single rows at 1 KB of data per row.

Run your typical workloads against Spanner

Always run your own typical workloads against a Spanner instance when doing capacity planning, so you can figure out the best resource allocation for your applications. Google's PerfKit Benchmarker uses YCSB to benchmark cloud services. You can follow the PerfKitBenchmarker tutorial for Spanner to create tests for your own workloads. When doing so, you should tune the parameters in the benchmarking configuration yaml files to make sure that the generated benchmark reflects the following characteristics in your production environment:

Reproducing benchmark numbers

To reproduce the benchmark numbers, follow the tutorial using the corresponding yaml files in the throughput_benchmark folder.

Zonal and regional failure protection

When running your workloads in production, it is important to provision enough compute capacity to continue to serve your traffic in the event of the loss of an entire zone (for regional instances) or an entire region (for multi-region instances). See alerts for high CPU utilization for more information on the recommended maximum CPU.

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