Product descriptions:
Hafnia, one of the world’s largest product and chemical tanker companies, set out to modernize a shipping industry that has historically been known for its lack of digital innovation. With siloed systems, manual processes and a growing demand for data-driven decision-making, the company needed a unified platform that could empower both technical and nontechnical teams. By adopting the Databricks Data Intelligence Platform, Hafnia built a centralized “data supermarket” that fuels self-service analytics, accelerates development and enables AI-powered applications. Today, employees utilize Lakebase and governed datasets to build their own tools and get to insights faster, transforming the data team from a cost center into a strategic driver of innovation.
Operational teams needed real-time, data-driven action
Managing more than 200 vessels, 4,500 crew members and 300 on-shore employees in Copenhagen, Singapore, Dubai, Monaco and Houston, Hafnia prioritized data early to avoid the technical debt common among legacy maritime shipping operators. “The shipping industry is not the most forefront in tech,” Simon Fassot, General Manager and Global Head of Data Analytics at Hafnia, said. “Our management made a bet on building data capabilities in-house.”
Before Databricks, Hafnia relied on a classic business intelligence (BI) stack centered on SQL Server, SSIS and Power BI. As Hafnia matured into a data and AI-driven organization, domain experts needed more than dashboards; they needed the ability to work directly with governed data and build advanced analytics. The data team built a self-serve “data supermarket” on the Databricks Data Intelligence Platform. Soon, domain experts across 10 departments were building their own dashboards and running analytics without waiting on the data team. As adoption grew, so did ambition. The dashboards gave leaders visibility into fleet and commercial performance, but now they wanted to run day-to-day processes on the same platform. “We wanted to move beyond reports and create real business applications,” Simon said.
Running operational apps required extending their architecture. Analytics workloads and transactional applications have distinct needs: Interactive apps require low-latency writes, high concurrency and frequent updates. After exploring external PostgreSQL providers, Hafnia realized they needed something that lived natively inside their existing Databricks environment. “We needed a purpose-built transactional layer that integrated seamlessly within our existing data stack — Lakebase was a perfect fit,” Simon recalled.
Lakebase as the engine for operational apps
After evaluating Snowflake and Databricks, Hafnia chose Databricks for its unified compute model, flexibility and support for Python, SQL, Scala and R. This decision also made it possible to adopt Lakebase as the company’s new foundation for delivering data-driven applications with consistent governance.
Lakebase is a fully managed PostgreSQL database natively integrated into the Databricks Platform, unifying operational workloads with analytics and AI on a single foundation. For Hafnia, this allowed the team to add operational capabilities without introducing a separate system. They deployed Lakebase as the transactional engine while keeping Delta Lake as the analytical system of record. Governance remains unified through Unity Catalog, ensuring that the same policies protecting analytics also apply to application data. “Lakebase allowed us to keep analytics where they belong and run our applications on a real database,” Simon said.
This architecture powers DNA Port, Hafnia’s internal operating portal built on Databricks. Instead of switching between dashboards and spreadsheets, commercial, technical and finance teams now work inside Lakebase-powered applications that run day-to-day operations. When users update records or progress workflows, data is written to PostgreSQL on Lakebase and synchronized into Delta tables for downstream analytics. “Data is not just being analyzed anymore,” Simon noted. “It is being acted on.”
Lakebase also supports Hafnia’s AI strategy. Marvis, the company’s internal copilot built on AI/BI Genie and Databricks Assistant, queries governed data while logging its interactions into Lakebase. Databricks Apps completes the stack, and back-end services are moving from Azure Web Apps to Databricks with Databricks Asset Bundles, simplifying CI/CD. By adopting Lakebase rather than adding another operational database, Hafnia keeps data, applications and AI on one platform. This reduces vendor sprawl, lowers infrastructure costs and enables a small team to deliver new capabilities quickly.
From dashboards to execution across the fleet
Lakebase is now central in Hafnia’s execution. Operational teams rely on DNA Port to execute core fleet, commercial and finance workflows end to end, rather than stitching together tools. What once took around two months from requirement to production dashboard or app now takes four or five days, roughly 12x faster. “Lakebase has removed one of the biggest blockers to delivering production applications quickly,” Simon said. “We now build production applications in days instead of months and the acceleration is beyond anything I expected.”
Regulatory and audit work has also been improved. Hafnia can deliver production-ready regulatory dashboards in two to three days, with lineage and access controls enforced through Unity Catalog and Lakebase logs. A few dozen of the most manual regulatory and finance processes are already automated or in progress on Databricks and Lakebase, turning previously ad hoc workflows into governed, observable applications. As of November 2025, around 40 processes and dashboards have been moved into DNA Port across the business, with the team steadily expanding coverage and prioritizing the most time-consuming workflows out of their 300–400 internal processes.
For an industry where communication often relies on emails and manual tools, Hafnia’s vision sets a new standard. The company is exploring extending their platform to partners and customers, which would reduce operational friction and redefine what modern shipping operations look like. “We want to show the industry what’s possible,” Simon explained. “A small team of 10 can build capabilities once reserved for giant enterprises. Lakebase makes that possible.”