
Firebird + Redshift
Firebird is an open-source relational database management system known for its lightweight and efficient design. Amazon Redshift, on the other hand, is a cloud data warehouse designed for fast and efficient analysis of large volumes of data.
With Erathos, you can integrate data from Firebird into Redshift in just a few minutes. Our platform simplifies the redshift integration process by handling the entire data movement to your analytical environment — with no need for custom scripts or manual routines. This redshift integration also allows your Firebird data to be cross-referenced with other sources already present in your Data Warehouse. That way, your time is focused on what truly adds value — extracting valuable insights and making more data-driven decisions through a reliable redshift integration flow.
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Why Erathos?
Plug and play connectors
More than 50 plug and play connectors to consolidate information from multiple sources, eliminating time-consuming manual processes and establishing a clear path to actionable and reliable insights — including seamless redshift integration for your data pipelines.
Greater control over pipelines
Transform the way you manage data. Quickly create pipelines by selecting relevant data, setting the schedule, frequency, and type of update without a line of code.
Edge observability
Stop being caught off guard by data update errors. Set up alerts and notifications to your email, Slack, or Discord to closely monitor the status and execution metrics of your data pipelines.
What is Erathos?
Gather data from different sources in one place
Erathos is a complete ELT software that extracts data from various sources through instant integrations. With plug & play connectors, you concentrate all your data in a single analytical environment and build a Data Warehouse in minutes.
Our customers
Simplified data ingestion
1
Select your data source
Choose your data source between over 50 plug'n'play connectors. You can test each connector for 14 days.
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 Amazon S3, BigQuery, Databricks, Redshift and PosgreSQL to centrlize your data
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