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Databricks Grows >55% YoY, Surpasses $4.8B Revenue Run-Rate, and is Raising >$4B Series L at $134B Valuation

Company accelerates investments in Agent Bricks, Lakebase and Databricks Apps to power Data Intelligent Applications

Databricks Inc., a data and AI company, announced it is raising a >$4 billion Series L investment, valuing the company at $134 billion.Additionally, the company crossed a $4.8 billion revenue run-rate during its Q3, growing >55% year over year, including >$1 billion revenue run-rate from its Data Warehousing business and >$1 billion revenue run-rate from its AI products – all while delivering positive free cash flow over the last 12 months.

The parallel rise of vibe coding and generative AI is accelerating the development of data intelligent applications in the enterprise. Databricks will use this new capital to help customers build AI apps and agents on their proprietary data, leveraging Lakebase as the system of record, Databricks Apps as the user experience layer, and Agent Bricks to power multi-agent systems.

The round was led by Insight Partners, Fidelity Management & Research Company, and J.P. Morgan Asset Management with additional participation from Andreessen Horowitz, funds and accounts managed by BlackRock, funds managed by Blackstone (“Blackstone”), Coatue, GIC, MGX, NEA, Ontario Teachers Pension Plan, Robinhood Ventures, accounts advised by T. Rowe Price Associates, Inc., Temasek, Thrive Capital and Winslow Capital. This new investment builds on Databricks’ accelerating financial results and underscores the company’s vision to make data and AI accessible to all organizations.

Databricks’ Financial Momentum
This funding follows continued strong momentum across Databricks’ business, including:

  • Surpassing $4.8 billion revenue run-rate, growing >55% YoY
  • Continuing to achieve positive free cash flow over the last 12 months
  • Achieving >$1 billion revenue run-rate for its AI products
  • In its first six months, Lakebase already has thousands of customers and is growing revenue at twice the pace of its Data Warehousing product
  • Achieving >$1 billion revenue run-rate for its Data Warehousing product in less than four years from general availability
  • Net retention rate sustaining >140%
  • >700 customers consuming at over $1 million annual revenue run-rate

The Rise of Data Intelligent Applications
Databricks’ Series L funding will advance product development across three strategic products, helping customers build data intelligent applications

  • Lakebase is the first serverless Postgres database purpose-built for the age of AI
  • Databricks Apps offers world-class speed and security to build and deploy data and AI applications
  • Agent Bricks makes it easy for organizations to build and scale high-quality agents on their data

In addition to fueling its growth, this capital is expected to be used to provide liquidity for employees. The investment is also expected to support future AI acquisitions and deepen AI research.

“Enterprises are rapidly reimagining how they build intelligent applications, and the convergence of generative AI with new coding paradigms is opening the door to entirely new workloads. With this investment, we’re deepening our commitment to help every organization innovate with AI on their own data,” said Ali Ghodsi, co-founder and CEO, Databricks. “By anchoring transactional data in Lakebase, delivering intuitive experiences through Databricks Apps, and enabling advanced multi-agent systems with Agent Bricks, we’re giving customers a unified foundation to build trusted, high-performance data intelligent applications at scale.”

“Our continued investment in Databricks reflects our deep conviction in their extraordinary momentum today and their ambitious vision for the future,” said John Wolff, MD, Insight Partners. “Databricks leads the way in turning AI innovation into enterprise impact. We’re thrilled to deepen our investment in a team that continues to pair strong financial performance with real customer results, setting the standard for how AI creates value for businesses. Databricks is just getting started.”

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Comments

This new and last financial round for Databricks is just phenomenal when you realize the numbers mentioned, especially a L round - wow - of $4 billion - wow #2 - at $134 billion - wow #3 - for a total funding of $25.3 billion - wow #4 - according to Crunchbase. The previous round of $1 billion in September was at $100 billion post-money. But why Databricks needs to secure all this cash? We don't speak here about $500 million or $1 billion.

It confirms the current wave of AI with this kind of players coming from big data and analytics and new fueled with generative and agentic AI targeting data intelligence in enterprises.

This story illustrates also the open source impact on the market in this domain and the power of the Apache Foundation and its large members community. Companies founders and its extended teams are super active in Apache Spark, Delta Lake, Iceberg, Unity Catalog, MLFlow, Delta Sharing or Redash and many of these they even initiated, launched, developed and maintained. The firm supports also TensorFlow, PyTorch, RStudio or TerraForm among others. You probably recognize now some famous faces on the image below, a real cosmopolite team of experts.

Databricks really leads the pack and pulls others and also attracts ideas and talents with some hot acquisitions. The company produces a real magnetism in the field. Founded in 2013, the firm became a giant in a few years and it;s trajectory is spectacular, pretty unique in the IT industry and software segment.

Applications change within enterprises and how teams have to integrate new methods to collect, manipulate and compute data at scale with AI algorithms and techniques.

Today, Databricks promotes a advanced data platform evolution to AI platform coupling data warehousing, analytics, ML and AI workflows within a global lakehouse approach. And this developed in 3 directions inside its portfolio: Lakebase, Databricks Applications and Agent Bricks and clearly the team jumped into AI and wishes to control a serious piece of the enterprise market cake.

But one question remains open, why the company needs all this cash and so fast? And what kind of exit would be possible for investors? This level makes things different from other models we have in mind...

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