Performance
Sequin change data capture (CDC) performance benchmarks
Sequin delivers industry-leading performance for change data capture (CDC), consistently achieving sub-200ms latency at 2,000 sustained operations per second. Here’s how Sequin compares to other solutions:
Tool | Latency at 2k ops/s |
---|---|
Sequin | 192ms |
Debezium | 234ms |
Fivetran | 5 minutes |
Airbyte | 1+ hours |
Test setup
Our benchmarks are conducted in a production-like environment. Sequin and Debezium are compared head-to-head capturing changes from AWS RDS and delivering to AWS MSK Kafka:
- AWS RDS Postgres
db.r6g.xlarge
instance (4 vCPUs, 16GB RAM) - AWS MSK Kafka provisioned with 3 brokers
- Sequin running via ECS on an
m8g.xlarge
instance (4 vCPUs, 16GB RAM) - Debezium deployed on MSK Connect with 8 MCUs.
- Continuous load of 2,000 operations per second applied to a single Postgres table
- 30-minute test duration
- Latency determined end-to-end from the time a change occurs in Postgres until it’s available in AWS MSK Kafka
Methodology
We measure end-to-end latency from the time a change occurs in Postgres until it’s available in Kafka. This includes:
- WAL read time
- Processing time (filters, transformations, etc.)
- Network transit time
- Destination write time
The test is conducted with dedicated EC2 instances that simultaneously write to the RDS instance and read from AWS MSK Kafka.
The load generation script applies a mixed workload of INSERT
, UPDATE
, and DELETE
operations to the benchmark_records
table at a total throughput of >= 2,000 operations per second.
The Posgres schema includes a single table with this schema:
Records delivered to Kafka are annotated with a delivered_at
timestamp. Full end-to-end latency is calculated by subtracting the delivered_at
timestamp from the updated_at
timestamp.
Throughput stability
Sequin maintains consistent performance even under sustained load:
By comparison, Debezium achieves a slightly higher latency of 234ms at similar throughput:
Resource utilization
Sequin was deployed to EC2 via Elastic Container Service (ECS). During the test, the Sequin ECS task averaged 34% CPU utilization and 10% memory utilization.
Next Steps
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