The Databricks valuation now stands at US$188 billion — roughly ₱11.6 trillion — after the data and AI platform company signed a term sheet for a new strategic funding round led by existing investor Coatue. The company confirmed the round on its newsroom, saying it expects to close later this summer with both new and existing investors participating. Reporting puts the raise at about US$3 billion (around ₱185 billion).
A 40% jump in five months
Databricks has been raising almost continuously, and the valuation curve is steep:
| Round | Date | Valuation |
|---|
| ~US$10B raise | December 2024 | US$62B (around ₱3.8 trillion) |
| US$1B raise | September 2025 | US$100B (around ₱6.2 trillion) |
| ~US$5B raise | February 2026 | US$134B (around ₱8.2 trillion) |
| ~US$3B raise | July 2026 | US$188B (around ₱11.6 trillion) |
That is a 40% increase in five months. Conversions use a mid-July rate of about ₱61.55 to the US dollar.
Where the money goes
Databricks says the capital will fund four things: its Unity AI Gateway (a control layer for governing which AI models a company uses and what they cost), Genie (its AI coworker platform), Lakebase (a serverless Postgres database designed for AI agents to read and write), and further acquisitions and AI research.
The framing from chief executive Ali Ghodsi is about cost discipline rather than raw capability. "Enterprises are moving from tokenmaxxing to valuemaxxing," he said. "They don't want to burn expensive tokens on the smartest model for every task — they want the best outcome per dollar."
That is a notable shift in tone. For two years the enterprise AI pitch was about access to the most powerful model available. Ghodsi is describing companies that now want to route cheap tasks to cheap models and pay premium rates only where it matters — which is exactly what a gateway product is for. Databricks has also published research arguing that open-weight models such as Z.ai's GLM 5.2 cost less than proprietary alternatives for coding work.
From big data to AI's second act
Founded in 2013, Databricks started in big data analytics before repositioning around AI infrastructure. It competes most directly with Snowflake, and TechCrunch notes it is widely viewed as a public-listing candidate alongside OpenAI and Anthropic. The company has not announced IPO plans.
The round also lands in a market where AI infrastructure is being financed on an unusual scale — the same environment in which Amazon raised at least $25 billion in bonds to fund its AI buildout.
Why this matters to Philippine businesses
Databricks is not a consumer product, so the local relevance runs through the companies Filipinos already use. Several Philippine firms are named Databricks customers:
- Coins.ph runs fraud detection, anti-money-laundering and financial reconciliation on the platform. Databricks' own customer case study on Coins.ph reports a 70% cut in operating costs, a 50% cut in infrastructure costs, and machine-learning features shipping in days or hours instead of weeks, serving a customer base of more than 10 million.
- Maya uses the Data Intelligence Platform as its central data layer for personalised customer experiences.
- Aboitiz Data Innovation applies it to predictive maintenance and demand-and-supply forecasting.
In plain terms: when a Filipino sends money on Coins.ph or Maya and the fraud check clears in a second, that pipeline is likely running on infrastructure this funding round is meant to expand. There is no Philippine office listed on the company's official locations page, and no local pricing is published — Philippine customers buy through cloud marketplaces and regional teams. The practical effect of a better-funded Databricks here is indirect but real: faster feature development at the fintechs and utilities that already depend on it, and more pressure on rivals to match its per-dollar cost story.
