Data and AI software company Databricks has officially closed a $5 billion strategic funding round led by Coatue, boosting its private valuation to $190 billion amid surging enterprise demand for its AI agent technologies.
Databricks closed a $5 billion strategic funding round at a $190 billion post money valuation. This is the company’s second major capital raise of 2026 (following a ~$5 billion equity + ~$2 billion debt package at a $134 billion valuation in February) and continues a rapid valuation climb from $62 billion in early 2025. The round was led by existing investor Coatue, with participation from Blackstone, MGX, accounts advised by T. Rowe Price Associates and T. Rowe Price Investment Management, and new investor Sixth Street Growth.
Databricks simultaneously reported that it surpassed a $7 billion annualized revenue run-rate in the second quarter of 2026, with year over year growth exceeding 80%. This builds on prior milestones: ~$5.4 billion run-rate (>65% YoY) in Q4 2025 / early 2026 and ~$4.8 billion (>55% YoY) in late 2025. The company has maintained positive adjusted free cash flow over the trailing 12 months.
Product level traction highlights the shift toward AI centric workloads:
- Lakehouse (data warehousing) surpassed a $1.5 billion revenue run-rate.
- Lakebase (serverless Postgres database purpose built for AI agents and applications) crossed a $100 million revenue run-rate.
- Broader AI products had previously reached ~$1.4–1.7 billion run-rate levels earlier in the year.
- Customer scale includes more than 1,000 customers at >$1 million annual run-rate and more than 100 at >$10 million. Net retention has remained above 140% in recent periods.
The accelerated growth (from mid 50s to >80% YoY) is attributed heavily to agentic AI driving higher platform consumption, more queries, iterative workloads, and data movement as enterprises deploy AI agents at scale.
How will Databricks use the funds?
The capital is directed primarily at three enterprise AI priorities that address the gap between model intelligence and real world business impact:
- Unity AI Gateway: A governance and routing layer for AI workloads. It enables enterprises to route tokens across models (proprietary and open source), set budgets, control spending, and shift from “token maxing” to “value maxing.” It is open sourced via MLflow in parts and pairs with Unity Catalog for unified data + AI governance.
- Lakebase: Serverless Postgres optimized for AI agent generated software. Agents can spin up isolated database environments (including branches of large databases) in under a second without full physical copies, supporting rapid experimentation, testing, and discard cycles that traditional databases handle poorly. Databricks reports very high daily database start volumes driven by this pattern.
- Genie: Conversational AI assistant / agent that grounds models in enterprise context (data, emails, meetings, internal systems) while preserving security and permissions, enabling broader employee access to insights and actions.
Additional capital supports hiring, acquisitions, and further product expansion in the agentic AI stack (including related efforts such as Agent Bricks and Databricks Apps). CEO Ali Ghodsi has framed the raise as reflecting both the cost of scaling the AI business and the opportunity to invest more aggressively while investor demand remains strong.
The $190 billion valuation (up from the $188 billion term sheet figure announced in July) represents a significant step-up from the $134 billion mark just six months earlier and continues the trajectory from $62 billion (Series J, early 2025, which included Meta as a strategic investor). At these levels, Databricks ranks among the most valuable private technology companies globally, frequently compared with OpenAI and Anthropic as a leading IPO candidate.
The multiple reflects sustained high growth, expanding AI product mix, strong customer retention/expansion, and the market’s premium on platforms that sit under the model layer, providing data, governance, orchestration, and operational infrastructure that pure model companies do not fully address. Analyst commentary has noted that sustained 50%+ ARR growth with gross margins stabilizing in the 70%+ range would support the valuation, though rising infrastructure costs from agentic workloads have introduced near term margin pressure.
Recommended: WindBorne Systems Raises $37 Million In Series B Funding Round
Databricks competes most directly with Snowflake in the data platform space while expanding into transactional databases (Lakebase challenging traditional players such as Oracle and SAP) and AI governance/orchestration layers. Its open data format philosophy (Lakehouse architecture) and multicloud stance are positioned as advantages against lock-in concerns. The company emphasizes that AI models still lack sufficient enterprise context and reliable operational infrastructure, creating durable demand for its platform even as models improve.
Ghodsi has argued that AGI (under earlier, narrower definitions focused on performing intellectual tasks better than most humans most of the time) has effectively arrived, but real enterprise impact remains constrained by context, governance, cost control, and systems of record, precisely the problems Databricks is targeting with the funded products.
The round provides substantial runway and reduces near term pressure to IPO. Management has indicated it is unlikely to go public ahead of peers such as OpenAI or Anthropic given market volatility, valuation dynamics, and the desire to continue investing aggressively while private. It also underscores investor conviction in the “picks and shovels” layer of enterprise AI: platforms that increase consumption of data and compute as agents proliferate, while solving the practical problems of cost, governance, and context that pure generative models leave unaddressed.
The $5 billion raise at $190 billion valuation crystallizes Databricks’ evolution from a leading lakehouse/data platform into a full stack Data + AI company centered on enabling production grade, governed, cost controlled agentic applications at enterprise scale. The combination of accelerating revenue growth, product traction in new categories (especially Lakebase), and strategic capital from sophisticated growth and institutional investors positions the company for continued aggressive investment in the AI infrastructure layer.
Please email us your feedback and news tips at hello(at)techcompanynews.com
