Artie vs. Debezium

Debezium captures change events. Artie captures changes, runs the streaming platform, handles schema drift, and stays accountable when something breaks at 2am.

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Open-source CDC is powerful.
Operating it isn't free.

Factor
Debezium (DIY stack)
Artie
Built for
Open-source DIY CDC framework
Fully managed real-time database replication
Architecture
Debezium connectors + Kafka + Schema Registry + sink connectors

Often paired with Flink or Kafka Streams for transforms
Durable streaming, managed end-to-end (Kafka-backed under the hood)
Operational ownership
Your team operates Kafka, connectors, schema registry, and sinks
Fully managed by Artie
Time to first pipeline
Weeks to months
Minutes
Replication latency
Seconds, with tuning of partitions, batch sizes, and sink flush intervals
Seconds, out of the box
Delivery semantics
At-least-once by default

Exactly-once requires significant engineering
Exactly-once
Schema evolution
Emits DDL events; downstream merge logic is yours
Auto-applies DDL, deletes, and type changes
Backfill behavior
DIY (initial snapshot + custom incremental backfill logic)
Free, online, parallel with CDC, replica-aware
Failure recovery
Build your own replay and dedupe; runbooks are yours
Kafka offset replay, exactly-once delivery
Impact on source DB
Configure replica routing yourself
Reads from read replica out of the box, no impact on primary
Sharded / multi-tenant fan-in
DIY routing across Kafka topics
Many-to-one fan-in
1,000s of shards → unified schema
Observability
Stitched together: Kafka metrics, connector logs, Flink job health, custom dashboards
Per-table lag, throughput, and alerting via Datadog/PagerDuty
PII controls
Custom Single Message Transforms (SMTs) you maintain
Column include/exclude/hashing on all plans
Enterprise compliance
You own SOC 2 / HIPAA evidence for your stack
SOC 2 Type II, HIPAA
Deployment options
Self-managed anywhere
Cloud or BYOC (your VPC)
Total cost shape
Low vendor spend, high engineer-hours and opportunity cost
Predictable contracted volume tier
Support / SLA
Community + paid Confluent or Aiven for the Kafka piece

No single point of accountability
Vendor-backed SLA, single point of accountability

Where Artie wins

Skip the streaming platform tax

Kafka tuning, connector babysitting, consumer-lag debugging, and rebalancing storms are ours to own. Your engineers go back to shipping product.

Schema evolution that just works

Add a column, drop a field, change a type. Artie auto-propagates DDL, deletes, and type changes downstream. No firefighting, no manual refreshes.

Exactly-once, with a recovery playbook

Durable streaming with offset replay and exactly-once delivery. When something goes sideways at 2am, our on-call answers – not yours.

Run it where your data lives

Artie Cloud or BYOC in your VPC (Enterprise) – same product, same UX. SOC 2 Type II and column-level PII controls (include, exclude, hash) on every plan. HIPAA-ready for regulated industries. Keep the control DIY gave you and lose the maintenance.

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Switching from Debezium to Artie
takes hours, not weeks

What stays the same

The cutover playbook

  • Your sources: Postgres, MySQL, MongoDB, and more
  • Your destinations: Snowflake, BigQuery, Redshift, Databricks, Iceberg
  • Your downstream stack: transformations, dashboards, BI tools keep reading the same tables
  • Your existing Kafka cluster: keep it running for non-CDC workloads if you want
  1. Run Artie in parallel with Debezium during a validation period. Both write to the same warehouse without conflict.
  2. Compare row counts, latency, and correctness side by side.
  3. Repoint downstream consumers to read from Artie tables.
  4. Decommission the Debezium connectors (and Kafka topics, if no longer needed).
Frequently asked questions

Is Artie a direct replacement for Debezium?

We've already invested in Kafka. Does that work with Artie?

What about flexibility and customization for our edge cases?

What's the migration risk?

Can we still control where the pipeline runs (BYOC)?

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