Databricks announced on June 11, 2025, that it expects to reach US$3.7 billion in annualized revenue by July 2025, marking a 50% increase from the previous year.

CFO Dave Conte shared that the company generated US$2.6 billion in revenue for the fiscal year ending January 2025, with a net retention rate over 140%.

Nearly 50 of its 15,000+ customers spend more than US$10 million annually. The company is also nearing free cash flow positivity.

In December 2024, Databricks raised US$10 billion, reaching a US$62 billion valuation. It competes with Snowflake, which has a US$70 billion market cap and slightly over US$4 billion in annualized revenue.

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🔗 Source: CNBC

🧠 Food for thought

1️⃣ Meteoric growth trajectory reveals enterprise appetite for integrated data and AI

Databricks has achieved one of the fastest scaling trajectories in enterprise software, growing from just over $100 million in annual recurring revenue in 2018 to an expected $3.7 billion by July 2025, representing roughly 35x growth in seven years 1.

This acceleration mirrors the company’s valuation climb from $2.75 billion in February 2019 to $6.2 billion just eight months later in October 2019, before reaching its current $62 billion valuation, a 22.5x increase in five years 2.

The growth rate remains remarkably strong at 50% year-over-year despite the company’s size, though it has moderated from the 60% reported in late 2024, reflecting the natural scaling challenges of maintaining hypergrowth at multi-billion revenue levels.

Databricks’ expansion demonstrates how enterprises are increasingly viewing unified data platforms as mission-critical infrastructure, with nearly 50 customers now spending over $10 million annually and a net retention rate exceeding 140%, indicating significant expansion within existing accounts.

The company’s ability to raise $10 billion in December at its current valuation shows investors’ continued confidence in both Databricks’ growth potential and the broader market for data intelligence platforms, even as other tech valuations have moderated.

2️⃣ The diverging paths of data platform competitors reveal market segmentation

The race between Databricks and Snowflake illustrates how the data platform market is dividing along technical specialization lines, with Snowflake commanding 18.33% market share versus Databricks’ 8.67% despite similar valuations ($70B vs. $62B) 3.

This market segmentation is evident in their technical approaches: Snowflake has optimized for SQL analytics and data warehousing workloads, while Databricks’ Apache Spark foundation makes it stronger for complex data science and machine learning applications 3.

The pricing models reflect these different focuses, with Snowflake charging based on warehouse size and usage (benefiting traditional analytics), while Databricks uses a computing unit-based model that accommodates varied workloads including intensive machine learning 3.

Databricks’ $1 billion acquisition of Neon to develop Lakebase database software signals its strategic intent to expand beyond its data science strengths and directly challenge Snowflake’s core data warehousing capabilities.

The competition highlights how the $40+ billion data platform market continues to expand rather than consolidate, with different vendors establishing specialized positions while still maintaining enough overlap to compete directly.

3️⃣ Aggressive hiring bucks industry trend toward selective recruitment

Databricks’ plan to hire 3,000 employees in 2025 stands in stark contrast to broader tech industry hiring patterns, where companies are prioritizing strategic, targeted recruitment over aggressive expansion due to economic uncertainty 4.

The company’s hiring ambitions would increase its workforce by approximately 37.5% from its current 8,000 employees, indicating extraordinary confidence in future growth even as it approaches free cash flow positivity.

This expansion comes during a period when elite tech companies are focusing primarily on AI and specialized technical roles, with AI skills now appearing in 25% of tech job listings across the industry 5.

Databricks’ ability to execute such large-scale hiring will be challenging in a market where backend engineers and AI specialists are in particularly high demand, potentially requiring significant compensation packages and creative recruitment strategies.

The company’s approach suggests it views the current market as an opportunity to acquire talent that might otherwise be employed at Big Tech companies that have slowed hiring, potentially giving it an advantage in innovation velocity against larger competitors.

Recent Databricks developments

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