
Centralize your data in Databricks
Databricks is a unified platform for data analytics and machine learning that enables the processing of large volumes of data with speed and scalability. Its integration with Apache Spark and collaborative tools makes it easier to build data pipelines and AI models efficiently.
Erathos and Databricks offer an integrated solution to accelerate data ingestion, processing, and analysis. With Erathos’s ready-made connectors and Databricks’ scalable platform, your team can focus on insights and innovation without worrying about the complexity of data pipelines.
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Create a single source of truth
What is Erathos?
Connect all your data sources to Databricks and create a single source of truth
Erathos is a complete ELT software that extracts data from various sources through instantaneous integrations. With plug & play connectors, you concentrate all your data in a single analytical environment and build a Data Warehouse in minutes.
Why Erathos?
Plug and play connectors
Send data from more than 80 sources directly to Databricks with plug-and-play connectors. Eliminate manual processes and consolidate all your information in a single analytics repository.
Greater control over pipelines
Set up Databricks ingestion pipelines fast: choose sources, define schedules and frequencies without writing code. You decide what to sync and when.
End-to-end observability
Monitor the health of your Databricks pipelines with real-time alerts via email, Slack, or Discord. Always up-to-date data with full traceability.
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






















