Matillion ETL

Build and run cloud data pipelines for BigQuery, Redshift, and Snowflake
4.3 
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Open the canvas, pick your warehouse, and start building a pipeline in minutes. Matillion ETL connects to BigQuery, Redshift, and Snowflake, plus a wide range of apps and databases. Authenticate once, choose tables or API endpoints, and drop a Load step into your job. Use guided setup to stage files in cloud storage, auto-detect schemas, and map fields. Add parameters for source and target so the exact same job runs in dev, test, and prod. Preview sample rows to confirm you’re ingesting the right data before you hit Run.

Shape and model data with drag-and-drop steps instead of writing SQL by hand. Join systems, clean and standardize columns, compute metrics, and pivot or unpivot for reporting. Components push work down to the warehouse engine, so large joins and aggregations rely on native performance. Insert validation checks for nulls, ranges, and referential rules; route bad records to quarantine tables. Capture audit fields, deduplicate, manage slowly changing dimensions, and publish tables or views your analysts can query immediately.

Chain tasks into end-to-end flows that load, transform, and publish in one run. Schedule by time or event, set dependencies to control order, and limit concurrency to protect shared resources. Use variables for dates and partitions to process only new or changed data. Monitor progress in real time, inspect logs by run, and push alerts to Slack, email, or webhooks. On failure, retry with backoff or trigger cleanup steps. Track lineage from source to output, version jobs in Git, and promote changes safely across environments. more

Review Summary

Features

  • Visual pipeline builder with drag-and-drop components
  • Connectors for SaaS apps, databases, and files
  • Warehouse pushdown for high-performance transforms
  • Job orchestration and time/event scheduling
  • Data validation rules and error quarantines
  • Parameters, variables, and environment management
  • Git-based version control and promotion
  • Monitoring, logging, and alerting (email, Slack, webhooks)
  • Metadata, lineage, and audit tracking
  • REST API and webhook integration
  • Incremental loads and partitioned processing patterns
  • Managed file movement via cloud storage or FTP/HTTP
  • Role-based access and operational controls

How It’s Used

  • Daily load from Salesforce and Postgres into Snowflake; model revenue KPIs; publish Looker views.
  • Marketing attribution: combine ads, web analytics, and spend data; build multi-touch metrics for dashboards.
  • Finance close: extract ERP data, normalize chart of accounts, and produce reconciled trial balance tables.
  • Product analytics: ingest clickstream from S3 into BigQuery, sessionize events, and create cohort tables.
  • Data science: deliver feature pipelines and training datasets on schedule with incremental processing.
  • Compliance: mask PII, enforce validation checks, and maintain lineage for audits.
  • Operations: monitor runs, alert on failures, and rerun only affected partitions to recover quickly.

Plans & Pricing

Developer

Free

Two Users
Move, Transform and Orchestrate Pipelines
No-code Custom Connectors
Unlimited Read Only Users
Unlimited Account/Billing Admin Users
Community Support

Basic

$1,000.00 per month

Includes Features of Developer Plan, Plus
Standard Support
Five Users

Advanced

$2,000.00 per month

Includes Features of Basic Plan, Plus
Unlimited Users
Project-level Permissions

Enterprise

Custom

Includes Features of Advanced Plan, Plus
Copilot and Auto Documentation
Allows for Hybrid Cloud Deployment
Streaming Change Data Capture Pipelines
Premium Support Options
Data Lineage
Option to Build AI Pipelines

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4.3
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