Change data capture · Artie

Artie

Managed real-time data replication that streams row-level database changes to a warehouse with sub-minute latency.

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Artie is a Y Combinator-backed CDC platform that replicates row-level inserts, updates and deletes from a source database to a data warehouse or storage layer continuously, citing typical end-to-end latency of 10-20 seconds and under 60 seconds worst case. For PostgreSQL it reads directly from the write-ahead log, so capturing changes adds no meaningful load to the source database. It handles schema evolution automatically, applying new or removed columns to the destination without manual intervention, and offers a History Mode that writes a Slowly Changing Dimension (SCD) table recording every change rather than overwriting rows in place. It is a fully managed cloud service with connectors set up in minutes rather than requiring pipeline code, and is listed on the AWS Marketplace. Backfills are free on every plan and never count toward billable row volume.

At a glance

Vendor Artie
Pricing model Usage-based
Free tier Yes
Deployment Cloud
Open source No
Best for Teams wanting fast, no-code CDC replication to a warehouse without operating pipeline infrastructure.

Pricing

Priced by billable rows replicated per month, with a free tier, a flat-rate growth tier, and custom enterprise pricing.

Plan Price Notes
Free $0/month Up to 1M billable rows/month, up to 2 active pipelines, backfills always free
Growth From $500/month (billed annually) / $600/month month-to-month Unlimited active pipelines, billed by row volume, backfills always included
Enterprise Custom pricing Adds Oracle/SQL Server support, bring-your-own-cloud, unlimited PrivateLink, uptime guarantees, 24/7 support

Prices read from the vendor's own page on September 21, 2026. Vendors change prices; check the source before you budget.

Features

  • Log-based CDC with sub-minute latency
  • Write-ahead-log reads for PostgreSQL with no added source load
  • Automatic schema evolution on the destination
  • History Mode for Slowly Changing Dimension (SCD) tracking
  • Connectors set up in minutes, no pipeline code required
  • Free backfills that never count toward billable volume

Integrations

Profile last reviewed September 21, 2026

Alternatives

Decodable Fully managed stream-processing platform built on Apache Flink and Debezium for CDC pipelines and real-time transformation. Streamkap Managed streaming CDC platform that replicates database changes to warehouses and lakes in under a second. Maxwell's Daemon Open-source application that reads MySQL binlogs and writes each change as JSON to Kafka, Kinesis or similar streams.

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Terms to know

Change data capture (CDC) A technique for detecting and streaming only the rows that changed in a source system, instead of reloading everything. Data pipeline The automated sequence of steps that moves data from source systems to a destination, transforming it along the way. Data warehouse A centralized, structured database optimized for fast historical reporting rather than day-to-day transactions. Schema evolution The ability of a table to accommodate structural changes, like an added or renamed column, without breaking data. Slowly changing dimension The techniques for recording how a dimension table's attributes change over time without breaking historical reporting.

Related guides

How to choose a change data capture tool Pick CDC by how it reads the source log, who has to operate it, and whether you actually need sub-second delivery or just a fresh warehouse table.