Automated data ingestion. Full visibility. Full control.
Trusted by data teams that process billions of rows per month




Extract data from databases, SaaS tools, and operational systems with stable connectors built to handle schema changes, retries, and partial failures — without custom code.
APIs and SaaS
HubSpot, Stripe, Google Ads, Meta, and dozens of other tools.
Databases
PostgreSQL, MySQL, SQL Server, MongoDB, and others.
Data Warehouses
BigQuery, Databricks, Redshift, S3, and more.
Configure ingestion behavior at the table or endpoint level instead of relying on global settings per data source.
Block Window
Block updates during specific time windows
Custom backfill
Avoid full reloads, and apply filters to load only what matters.
Custom Retry Strategy
Select how many retries Erathos should make before reporting the error — and the interval between each attempt.
Track ingestion behavior over time — without opening logs or manually monitoring pipelines.
Email, Slack, and Discord alerts
Real-time alerts when a job fails — before the issue reaches downstream.
Job details
Understand the execution history, data freshness, and when the next job is scheduled.
Execution details
Monitor every data update without opening logs.
Integrate data ingestion into the rest of your workflow. Trigger jobs in Databricks when ingestion is complete, orchestrate with Airflow or Dagster, and run dbt transformations once the data is ready.
Orchestrate your runs
Use an external orchestrator to trigger Erathos jobs.
Create automations
Use the completion of a run as a trigger for other automations across your stack.
Increase your observability
Connect our API to your observability system to centralize pipeline information in one place.






















