
Beta
Runrun.it for data warehouses: processes and projects
The Runrun.it connector on Erathos extracts operational task and project management data, including tasks, subtasks, projects, internal clients, users, deadlines, custom fields, tags, and productivity reports, delivering everything directly to your data warehouse. Operations teams and PMOs use this integration to combine Runrun.it data with other sources (finance, CRM, HR) and build dashboards for workload, SLA compliance, and team productivity, without relying on manual spreadsheet exports.
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Create a single source of truth
What is Erathos?
Consolidate data from different sources into a single place
Erathos is a complete ELT platform that extracts data from Runrun.it and over 100 other sources via instant integrations. With plug-and-play connectors, you can centralize all your data in a single analytical environment and build a Data Warehouse in minutes.
Why Erathos?
Automated incremental sync
Erathos continuously extracts tasks, projects, and deadline updates from Runrun.it using incremental sync by default. No unnecessary reprocessing: only new and updated records are loaded during each run.
Observability and alerting
Monitor every Runrun.it pipeline run with detailed logs and automatic alerts via email, Slack, or Discord. Smart retries ensure that temporary failures don't disrupt your productivity data ingestion.
No code to write or maintain
Connect Runrun.it to your data warehouse without writing a single line of pipeline. Erathos automatically manages pagination, rate limits, retries, schema evolution, and backfills—even when Runrun.it updates its API.
Our customers
Trusted by data-driven companies
Simplified data ingestion
1
Select your data source
More than 80 plug-and-play connectors to consolidate data from multiple sources, eliminate time-consuming manual processes, and establish a pipeline.
2
Setup your pipeline
Manage your pipeline seemlessly. Select a sync hour, frequency and type at a table/endpoint level.
3
Select your data warehouse
Choose between BigQuery, Databricks, Redshift and PosgreSQL to centrlize your data
FAQ
Data ingestion with control, observability, and scale

































