"We process $1.2T in payments annually. Zipline is how we move transaction events to our analytics stack with zero data loss - even during Black Friday peaks when we see 40× normal throughput."
"We evaluated Debezium, Kafka Connect, and Fivetran. Zipline was the only one that gave us exactly-once at scale without a dedicated team to maintain it. One YAML file replaced 14,000 lines of custom pipeline code."
"One engineer, one afternoon, 30-second brew install. We now stream all issue events to BigQuery in real time. The CLI is the best developer experience I've seen in infrastructure tooling - period."
Stream OLTP changes directly to your data warehouse. Eliminate batch ETL lag and query data seconds after it commits - not hours. Works with BigQuery, Snowflake, ClickHouse, and Redshift.
Use Kafka as the source of truth and CDC as the trigger. Decouple services without adding write-path complexity. Publish database changes as domain events with zero application-layer changes.
Invalidate Redis or Memcached keys the moment Postgres commits. No polling, no TTL guesswork. Zipline delivers the row key and operation type in under 200ms P99 from WAL commit.
Every row change captured, immutable, and replayable. Full audit trail with before/after values, user context, and transaction timestamps. Export to your SIEM or immutable S3 archive.
Continuous S3 and GCS writes with zero-copy Apache Iceberg table updates. Merge strategies handle upserts and deletes natively. No custom Spark jobs, no nightly full extracts.
Replicate data across AWS, GCP, and Azure regions with built-in conflict detection and configurable resolution strategies. Active-active replication with last-write-wins or custom merge logic.
"We were losing ~0.3% of events in our previous pipeline during Kafka broker failovers. Since switching to Zipline's exactly-once delivery, we've had zero event loss across 140B events. The WAL-based approach is just architecturally sound."
"We stream all Notion block changes to our search indexing pipeline via Zipline. Before, search lag was 8–30 seconds. Now it's under 400ms. The schema evolution handling is what really sold us - we add columns constantly and the pipeline just adapts."
"Figma's design data model is complex - hundreds of table types, high write volume, very low tolerance for inconsistency. Zipline handles the cardinality and throughput without breaking a sweat. The Terraform provider made our rollout completely automated."
"Retool's internal analytics pipeline was a mess of cron jobs and manual SQL dumps. Zipline replaced all of it. We went from T+1 data to sub-second freshness for our own product analytics. The zipline plan command alone has saved us from several foot-gun moments."
"Segment processes billions of events daily and we use Zipline to keep our internal Postgres metadata stores in sync with our event warehouse. The replay API was critical for us - when we had a schema migration incident, we replayed 6 hours of data in under 12 minutes."
"We deploy on Vercel's edge network and our backend Postgres databases are distributed across 16 regions. Zipline's multi-region sync keeps our read replicas fresh within 50ms globally. Honestly the easiest infrastructure decision we've made this year."
Set up in 30 seconds. No credit card required. Scales to billions of events per day.