y42

Emerging

Berlin Germany full-stack data platform; raised $31M+; combines ELT pipeline, dbt-based transformation, and BI in a single no-code/low-code environment.

Company Overview

y42 is a full-stack data platform founded in 2020 and headquartered in Berlin, Germany. The company was founded by Hung Dang and Fabian Schuh to build a unified platform that covers the entire modern data stack — ELT data ingestion, dbt-based SQL transformation, and business intelligence visualization — in a single integrated product. y42's thesis is that the fragmentation of the modern data stack, while enabling best-of-breed component selection, also creates significant operational overhead from maintaining multiple tools with separate authentication, monitoring, and support relationships. y42 integrates these layers into a single, cloud-hosted environment.\n\ny42 raised $31 million in funding from investors including Sequoia Capital, La Famiglia, and Creandum. The platform's ELT component provides pre-built connectors to more than 200 data sources, with the data delivered directly into the customer's own cloud data warehouse — Snowflake, BigQuery, or Redshift — ensuring data ownership and compliance. The transformation layer is powered by dbt under the hood, allowing analytics engineers familiar with dbt to work in their existing paradigm while benefiting from y42's visual interface and managed execution. The BI layer provides a drag-and-drop dashboard builder that connects to the transformed data models in the warehouse.\n\ny42 is particularly popular in the European market among data teams at growing technology companies and scale-ups that want the full modern data stack without the complexity of managing and integrating three or four separate tools. Its single-vendor support model and GDPR-compliant European data infrastructure make it a strong fit for EU-based organizations with compliance requirements.

Revenue
$31M
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Key Differentiators

Emerging Innovator

y42 is an emerging player bringing innovative solutions to the Modern Data Stack & Analytics Engineering market.

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