OpenAI

Databricks

OpenAI

OpenAI makes money primarily through API access and subscriptions. The API charges developers per token (roughly per word) for using GPT models in their applications.

ChatGPT Plus costs $20/month for individual users, ChatGPT Team is $25-30/user/month, and ChatGPT Enterprise is custom-priced. Microsoft pays OpenAI licensing fees and also resells OpenAI models through Azure OpenAI Service.

OpenAI reportedly generates over $5 billion in annualized revenue as of 2025, growing at an extraordinary rate.

Databricks

Databricks runs on a consumption-based pricing model. Companies pay for the compute and storage they actually use on the Databricks platform, measured in "Databricks Units" (DBUs).

The more data you process, the more you pay. This is brilliant because it means revenue grows automatically as customers' data volumes grow — which in the age of AI, they always do.

The platform runs on top of the major cloud providers — AWS, Azure, and Google Cloud. Databricks doesn't own servers.

They're a software layer that makes those clouds dramatically more useful for data work. They take a margin on top of the underlying cloud compute costs, essentially acting as a "toll booth" between companies and their data.

They also pioneered the "lakehouse" architecture — a mashup of data warehouses (structured, fast querying) and data lakes (cheap, handles any data format). Before Databricks, companies had to maintain both.

The lakehouse collapses them into one system. This isn't just clever marketing — it genuinely saves enterprises millions in duplicate infrastructure.

OpenAI

OpenAI was founded in December 2015 as a nonprofit AI research lab. The founding donors — including Elon Musk, Sam Altman, Peter Thiel, Reid Hoffman, and Jessica Livingston — pledged $1 billion with a mission to build artificial general intelligence (AGI) that would benefit all of humanity.

The idea was that AI was too important and too dangerous to leave in the hands of Google alone.

Sam Altman became chairman while Greg Brockman (former CTO of Stripe) became president. Ilya Sutskever, one of the most respected AI researchers alive, left Google Brain to become chief scientist.

The early team was stacked with world-class researchers who published their work openly — hence "Open" AI.

But AI research turned out to be staggeringly expensive. Training large models required millions of dollars in compute.

In 2019, OpenAI created a "capped-profit" subsidiary — investors could earn up to 100x their money, but profits beyond that would flow to the nonprofit. Microsoft invested $1 billion.

The mission was still to save humanity. The method now involved making a lot of money first.

Databricks

Databricks started as a research project at UC Berkeley's AMPLab around 2009. Matei Zaharia, a PhD student, was frustrated with how slow Hadoop MapReduce was for iterative machine learning workloads.

His answer was Apache Spark — an open-source engine that could process data up to 100x faster than MapReduce by keeping data in memory instead of writing to disk after every step.

Spark took off fast in the open-source community. By 2013, it was the most active open-source project in big data.

Zaharia and six Berkeley colleagues — Ali Ghodsi, Andy Konwinski, Arsalan Tavakoli-Shiraji, Ion Stoica, Patrick Wendell, and Reynold Xin — decided to build a company around it. They incorporated Databricks in 2013 with the idea that Spark was powerful but brutally hard to set up and manage.

The company would offer a managed cloud platform that made Spark accessible to data teams who weren't distributed systems engineers.

Their first product was essentially "Spark as a service" — a collaborative notebook environment where data scientists and engineers could write Spark jobs without managing clusters. The bet was that enterprises had massive data problems but not enough PhDs to solve them.

They were right.

OpenAI

ChatGPT's launch in November 2022 was the growth strategy — it just wasn't planned that way. The team expected a modest research preview.

Instead, ChatGPT hit 1 million users in 5 days and 100 million monthly active users in 2 months, making it the fastest-growing consumer application in history. The product went viral because it felt like magic — for the first time, anyone could have a natural conversation with a machine that seemed to understand them.

The Microsoft partnership provided distribution at massive scale. Microsoft integrated OpenAI models into Bing, Office 365 (Copilot), GitHub (Copilot), and Azure.

Overnight, hundreds of millions of Microsoft users had access to OpenAI technology. Microsoft's $13 billion investment was the largest AI bet in history and gave OpenAI nearly unlimited compute.

The API created an ecosystem. Thousands of startups built products on top of OpenAI's models — from customer service bots to coding assistants to content generators.

Each API customer locked themselves into OpenAI's ecosystem, creating switching costs and recurring revenue.

Databricks

Databricks grew by being genuinely useful before being profitable. They contributed massively to Apache Spark's open-source ecosystem, which meant thousands of companies were already using Spark when Databricks offered to manage it for them.

The open-source-to-enterprise pipeline is the most powerful go-to-market motion in software.

They also bet big on partnerships. The Microsoft partnership was transformational — Azure Databricks became a first-party service on Azure, meaning Microsoft's sales force was effectively selling Databricks to every enterprise customer.

That single deal probably added billions in annual recurring revenue.

Acquisitions were strategic and well-timed. MosaicML in 2023 for $1.3 billion gave them proprietary AI training capabilities right when every enterprise wanted to build custom AI models.

Tabular in 2024 brought the creators of Apache Iceberg, another critical open-source data format. They bought the talent and the technology simultaneously.

OpenAI

The board crisis of November 2023 nearly destroyed the company. The nonprofit board fired Sam Altman as CEO on a Friday, citing a loss of confidence.

Within 48 hours, 95% of employees threatened to quit and follow Altman to Microsoft. By Tuesday, Altman was reinstated and the board was restructured.

The incident exposed the fundamental tension between OpenAI's nonprofit governance and its for-profit ambitions — a tension that still hasn't been fully resolved.

The cost of training frontier models is eye-watering. Each new GPT generation costs hundreds of millions to train.

OpenAI is reportedly spending over $7 billion annually on compute. The company is burning through cash faster than almost any startup in history, which is why it keeps raising at higher and higher valuations.

If revenue growth slows before costs stabilize, the math gets ugly.

Safety concerns are not going away. Multiple prominent researchers have left OpenAI over disagreements about the pace of development versus safety research.

Ilya Sutskever, the chief scientist who was central to the board's decision to fire Altman, left in 2024 to start a safety-focused AI lab. The public debate about whether OpenAI is moving too fast — and whether its safety commitments are genuine — grows louder with every capability improvement.

Databricks

The elephant in the room is Snowflake. Both companies want to be the single platform where enterprises do all their data work, and the overlap is growing fast.

Snowflake started in SQL analytics and is pushing into data engineering and ML. Databricks started in data engineering and ML and is pushing into SQL analytics.

The collision is inevitable and expensive — both are spending billions on sales and R&D.

There's also the cloud provider threat. AWS, Azure, and Google Cloud all have their own data analytics services and could theoretically squeeze Databricks by making their native tools better or cheaper.

Databricks runs ON these clouds, which means their biggest partners are also their biggest potential competitors. It's the classic platform risk problem.

So far, Databricks has stayed ahead by innovating faster than the cloud providers' internal teams, but it's a race that never ends.

OpenAI

ChatGPT is the consumer chatbot — the product that made AI mainstream overnight. GPT-4o is the flagship multimodal model that handles text, images, and audio.

The OpenAI API lets developers integrate GPT into any application. DALL-E generates images from text descriptions.

Whisper transcribes and translates audio. Sora generates videos from text prompts.

GPT Store lets users create and share custom GPT agents. ChatGPT Enterprise gives businesses a private, secure version of ChatGPT with admin controls and no data training.

Databricks

Unity Catalog — a universal governance layer that lets companies manage permissions, lineage, and access control across all their data and AI assets in one place. Delta Lake — an open-source storage layer that brings reliability to data lakes with ACID transactions, schema enforcement, and time travel (yes, you can query your data as it existed at any point in the past).

Databricks SQL — a serverless SQL analytics product that competes directly with Snowflake on their home turf. Mosaic AI — their machine learning and generative AI platform, supercharged after acquiring MosaicML in 2023 for $1.3 billion.

Databricks Notebooks — collaborative workspaces where data teams write code, visualize results, and build pipelines together in real time.

OpenAI

Microsoft ($13B), Thrive Capital, Khosla Ventures, Sequoia Capital, Founders Fund, Tiger Global, SoftBank, a16z

Databricks

Andreessen Horowitz led multiple early rounds and has been the longest-standing institutional backer. Microsoft made a massive strategic investment alongside the Azure Databricks partnership.

T. Rowe Price, Tiger Global, and Franklin Templeton participated in later growth rounds.

NEA was an early investor. The $10 billion Series J in 2024 valued the company at $62 billion and was led by Thrive Capital with participation from Andreessen Horowitz, DST Global, GIC, Insight Partners, and WCM Investment Management.