Looker vs Steep
Side-by-side comparison of AI visibility scores, market position, and capabilities
Google Cloud BI platform with LookML semantic layer ensuring consistent metric definitions across enterprises; $2.6B Google acquisition competing with Tableau and Power BI for enterprise self-service analytics.
About
Looker is a business intelligence and data analytics platform now part of Google Cloud — providing the LookML data modeling language, self-service exploration tools, embedded analytics, and natural language querying capabilities that enable data teams to define metrics once and make them available consistently across the organization. Founded in 2012 in Santa Cruz, California by Lloyd Tabb and Ben Porterfield, Looker was acquired by Google for $2.6 billion in 2019 and has been integrated into Google Cloud as the primary BI platform alongside Google Looker Studio (formerly Data Studio).
Copenhagen Denmark BI platform for modern data teams connecting to Snowflake and BigQuery; metric-centric analytics with fast warehouse-native query execution and clean opinionated UI designed as an alternative to legacy BI paradigms for analytics engineering teams.
About
Steep is a business intelligence and analytics platform founded in 2021 and headquartered in Copenhagen, Denmark. The company was founded by former product and engineering leaders to build a BI tool optimized for the modern data team workflow — fast, warehouse-native query execution, a clean and opinionated UI, and first-class support for the metric-centric analytics workflows that analytics engineering teams are building. Steep positions itself as an alternative to legacy BI tools that carry the weight of decade-old UI paradigms and to overly complex enterprise platforms.\n\nSteep has raised pre-seed funding and operates as a lean, product-focused startup primarily targeting analytics engineering teams in Europe and growing technology companies. Its platform connects directly to Snowflake, BigQuery, and Redshift as the query engine, ensuring that all analysis runs against live warehouse data without intermediate caching layers that can serve inconsistent results. Steep's metric layer allows teams to define business metrics centrally and build dashboards around those metrics rather than one-off SQL queries, promoting consistency in how the company measures performance.\n\nSteep's dashboard experience is designed for both analysts building data products and business stakeholders consuming them, with a clean viewer mode that removes technical noise for non-technical audiences. The platform supports scheduled email and Slack delivery of dashboard snapshots, data alerting for metric threshold monitoring, and embedding for sharing dashboards in internal tools. Steep's European roots and GDPR-compliant data architecture make it a strong fit for European organizations with data residency requirements.
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