Etleap
Etleap provides an integrated pipeline platform built around Apache Iceberg, enabling continuous data ingestion, coordinated transformation with dbt Core, and automated table maintenance. The platform handles the full pipeline lifecycle—ingest, transform, coordinate, and operate—so production teams can adopt Iceberg as their data foundation without managing fragmented tooling. Customers include Moderna, PagerDuty, and Morningstar.
- Enterprise Software
- Software Only
Funding
Funding not disclosed
Founders
Founder details are not available yet.
Product
Problem
Adopting Apache Iceberg as a data foundation introduces operational complexity: teams must keep tables continuously fed with operational data, coordinate transformations with tools like dbt Core, and perform ongoing table maintenance. Without a dedicated pipeline layer, production teams are forced to stitch together separate tools for ingestion, transformation, and maintenance, leading to inconsistent data state, fragile pipelines, and increased operational overhead.
Solution
Etleap provides a single, integrated pipeline platform built around Apache Iceberg, covering the four core capabilities required for production: ingest, transform, coordinate, and operate. The platform continuously loads operational data into Iceberg tables, supports data wrangling and dbt Core models within a single pipeline, and coordinates ingestion and transformation from shared data state. Automated maintenance keeps Iceberg tables healthy, while the platform's architecture supports low-latency use cases such as streaming CDC with sub-5-second, exactly-once delivery. Etleap connects directly to databases, applications, files, and streaming sources, unifying data management in one place.
Target Audience
Primary customers are data engineering and analytics teams at production-scale companies—such as Moderna, PagerDuty, Morningstar, and Bill.com—that need to adopt Apache Iceberg as their data foundation and require a reliable, integrated pipeline layer for continuous ingestion, transformation, and table maintenance.
Features
- Continuous ingestion from a wide range of sources including PostgreSQL, MySQL, MongoDB, Oracle, Salesforce, SAP OData, Google Analytics, and streaming event sources
- Coordinated transformation using dbt Core and built-in data wrangling capabilities within a single pipeline
- Automated table maintenance to keep Iceberg tables healthy, including compaction and deletion vector handling for streaming updates
- Support for low-latency CDC ingestion with sub-5-second, exactly-once delivery, leveraging Iceberg branching for position deletes at scale
- Integration with major data platforms including Snowflake, Redshift, Databricks, and AWS DMS
- Managed pipeline reliability with automatic deltas and fully managed operations