Anthropic

Databricks

Anthropic

Anthropic makes money through API access and subscriptions, similar to OpenAI. The Claude API charges developers per token for input and output.

Claude Pro costs $20/month for individuals with priority access and higher usage limits. Claude Team is $25-30/user/month for businesses.

Claude Enterprise offers custom pricing with enhanced security, admin controls, and longer context windows. Amazon Web Services resells Claude through Amazon Bedrock and Google Cloud offers it through Vertex AI, both generating revenue-sharing income for Anthropic.

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.

Anthropic

Dario Amodei was VP of Research at OpenAI. His sister Daniela Amodei was VP of Operations.

They were two of the most senior people at the company. In 2020-2021, they grew increasingly concerned that OpenAI was prioritizing commercialization over safety research.

The board crisis that would eventually happen in 2023 was already brewing beneath the surface — the tension between "move fast and ship products" and "slow down and do the safety work" was real.

In early 2021, Dario and Daniela left OpenAI and took a group of key researchers with them. They founded Anthropic as a public benefit corporation — a structure that legally requires the company to consider its impact on society, not just shareholder returns.

The name comes from "anthropic principle" in physics — the idea that the universe's fundamental parameters seem fine-tuned for human existence.

The founding thesis was simple: AI was going to become incredibly powerful whether anyone wanted it to or not. The safest path was to have a safety-focused lab at the frontier of capabilities, not watching from the sidelines.

Build the most powerful AI you can, but build it with safety baked into every layer.

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.

Anthropic

Anthropic grew through a deliberate "safety as a brand" strategy. While OpenAI chased consumer virality with ChatGPT, Anthropic positioned Claude as the thoughtful, reliable, safety-conscious alternative.

Developers who found ChatGPT inconsistent or who worried about data privacy gravitated to Claude.

The enterprise partnerships were the real growth engine. Amazon invested $4 billion and made Claude the featured AI on Amazon Bedrock.

Google invested $2 billion and integrated Claude into Google Cloud. These partnerships gave Anthropic instant distribution to millions of enterprise developers without building a sales team.

Claude's strength in specific use cases drove adoption. Claude became known as the best AI for long-document analysis, nuanced writing, and careful reasoning.

Law firms, financial analysts, researchers, and enterprise customers who needed accuracy over speed chose Claude. The reputation for quality over flash built a loyal and growing user base.

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.

Anthropic

The funding arms race is existential. Training frontier AI models costs billions.

Anthropic has raised $13.7 billion and needs to keep raising because each generation of Claude costs more to train. If a funding round fails or investors lose confidence, Anthropic can't compete at the frontier.

The company is in a spending war with OpenAI (backed by Microsoft) and Google (with DeepMind) — two of the richest companies in history.

Being second in consumer awareness hurts. ChatGPT is a household name.

Claude is not. Most non-technical people have never heard of Anthropic.

This matters because consumer brand recognition drives enterprise adoption — CIOs buy what they've heard of. Anthropic has to fight for mindshare against a competitor with a massive head start in public awareness.

The safety-capabilities tension is real. Anthropic's entire brand is built on being the "safe" AI company.

But to stay competitive, they must build increasingly powerful models. Every capability improvement creates new risks.

If Anthropic ships something that causes harm, the reputational damage is catastrophic because safety is their core promise. If they move too slowly, they become irrelevant.

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.

Anthropic

Claude is the flagship AI assistant — available via web app, mobile app, and API. Claude excels at long-document analysis, coding, writing, and reasoning.

Claude's context window handles up to 200,000 tokens (roughly 500 pages) — dramatically more than most competitors. The Claude API lets developers build applications powered by Claude.

Claude for Enterprise provides businesses with a private, secure deployment. Constitutional AI is Anthropic's research framework for training AI systems to be helpful, harmless, and honest — the safety methodology that differentiates Claude from competitors.

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.

Anthropic

Google ($2B+), Amazon ($4B), Spark Capital, Salesforce, Menlo Ventures, SK Telecom, Lightspeed

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.