Databricks has acquired a cutting-edge German startup, 8080 Labs. 8080 Labs is the maker of bamboolib, a popular UI-based data science tool that enables fast and easy data exploration and transformation with a matter of clicks, not code. The new UI-driven capabilities will be integrated across Databricks’ Lakehouse Platform, marking the company’s expansion into the low-code/no-code space. This strategic acquisition broadens the accessibility of its lakehouse platform to a wider audience of citizen data scientists and data team personas, enabling further democratisation of data and AI throughout the enterprise. The terms of the deal were not disclosed.
With the acquisition of 8080 Labs, Databricks is lowering the barrier to entry for more people to uncover actionable insights from their data with only a few clicks. 8080 Labs' flagship product, bamboolib, empowers citizen data scientists with no-code workflows while seamlessly integrating with the Python ecosystem and generating production-ready code behind the scenes. Databricks plans to integrate the no-code capabilities with its new AutoML, visualisation, and dashboard offerings to extend simple, UI-based features across its lakehouse platform, making Databricks more accessible and easy-to-use for both experts and citizen data scientists alike. Now, anyone with just a very basic understanding of data science, can train advanced models on their datasets.
“We are thrilled to welcome 8080 Labs to the team as we accelerate the adoption and accessibility of lakehouse as the data architecture of the future,” said Ali Ghodsi, Co-Founder and CEO of Databricks. “Together with last year’s acquisition of Redash, we are broadening the focus of our user base to a wider audience that prefers low-code/no-code solutions. Bringing simple capabilities to Databricks is a critical step in empowering more people within an organisation to easily analyse and explore large sets of data, regardless of expertise.”
Citizen data scientists play a vital role in an organisation’s ability to streamline and productionise machine learning (ML) at scale, bridging the gap between the analysts and highly-specialised data scientists to build meaningful models that can impact all areas of the business. As data and AI become a strategic priority for businesses of every size, it's critical that everyone within an organisation is empowered to ask questions and take action based on data. While many tools for citizen data scientists only offer exploratory capabilities, the acquisition of 8080 Labs combined with Databricks’ unique ‘glass box’ approach to AutoML, empowers people to perform comprehensive data tasks with ease, from data analysis and data transformation, to machine learning workflows. The platform automatically generates high-quality code behind the scenes, allowing data teams to easily put their key findings and results to work without the added demand on expert engineers to reimplement the process for production.
“We founded 8080 Labs to bring simplicity to complex data tasks and make the power of data science and machine learning accessible to data teams of any skill set,” said Tobias Krabel, Co-Founder of 8080 Labs. “With open-source roots and an incredible vision to reshape the data landscape with the lakehouse category, we see endless opportunities with Databricks and could not be more excited to join the team on this journey.”
This acquisition bolsters Databricks’ focus on fostering a global culture of innovation and is its latest addition to a growing pool of engineering talent in the EMEA market. Earlier this year, the team from Cubonacci, a data science solutions startup based in Amsterdam, also joined Databricks to support the development of scalable and secure data storage and machine learning capabilities. Amsterdam is now home to Databricks’ second largest engineering office. Databricks recently raised $1.6 billion at a $38 billion valuation, to help the company accelerate the global adoption and development of its lakehouse platform and to invest in cultivating world-class talent throughout the regions.