Databricks

SpaceX

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.

SpaceX

SpaceX makes money three ways. First, launch services — companies and governments pay SpaceX to put their satellites into orbit.

A Falcon 9 launch costs about $67 million, which undercut the competition by 75% when it debuted. Second, Starlink — SpaceX's own satellite internet constellation, which is now generating over $6 billion in annual revenue from 4+ million subscribers.

Third, government contracts — NASA pays SpaceX to ferry astronauts to the International Space Station and the DoD pays for national security launches.

The secret sauce is reusability. Before SpaceX, every rocket was used once and thrown into the ocean.

SpaceX figured out how to land the first stage booster back on Earth and fly it again. A single Falcon 9 booster has flown over 20 times.

That's like the difference between throwing away an airplane after every flight versus keeping it for decades.

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.

SpaceX

In 2001, Elon Musk had just sold PayPal to eBay for $1.5 billion and was sitting on roughly $180 million after taxes. Most people would buy an island.

Musk decided to buy rockets. His original idea was even weirder — he wanted to send a small greenhouse to Mars called "Mars Oasis" to reignite public interest in space exploration.

He flew to Russia three times to buy refurbished ICBMs. The Russians kept raising the price and at one point literally spat on him.

On the flight home from that last failed Russia trip, Musk opened a spreadsheet and started calculating the raw material costs of building a rocket from scratch. He realized the materials were only about 3% of the typical price of a rocket.

The rest was markup, inefficiency, and monopoly pricing by companies like Boeing and Lockheed Martin. He decided to build his own.

SpaceX was founded in June 2002 in a warehouse in El Segundo, California. Musk put in $100 million of his own money.

He hired Tom Mueller, a legendary rocket propulsion engineer who had been building rocket engines in his garage as a hobby. The first rocket, Falcon 1, was supposed to be the cheapest orbital rocket ever built.

It took six years and three spectacular explosions before it finally worked.

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.

SpaceX

SpaceX's growth strategy was simple: be cheaper than everyone, then be better than everyone, then be the only option.

They started by undercutting the launch market. The United Launch Alliance (Boeing + Lockheed Martin joint venture) was charging $300-400 million per launch.

SpaceX offered $67 million. Government agencies and commercial satellite companies started lining up.

Reusability was the real game-changer. Landing a rocket booster looked like science fiction when SpaceX first attempted it in 2013.

They failed over and over — spectacular ocean landings, explosions on drone ships, near-misses. But in December 2015, a Falcon 9 first stage landed back at Cape Canaveral.

It was the first time an orbital-class rocket had ever landed after a mission. Now they do it routinely — it's almost boring.

Starlink created a completely new revenue stream. Instead of just launching other people's satellites, SpaceX launched thousands of its own.

By 2024, Starlink had over 4 million subscribers and was generating billions in revenue. It turned SpaceX from a launch company into a telecom company.

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.

SpaceX

The early days nearly killed the company. SpaceX's first three Falcon 1 launches all failed.

The first one in 2006 crashed 25 seconds after liftoff due to a corroded fuel line nut. The second in 2007 reached space but the second stage shut down early.

The third in 2008 failed because the first and second stages collided during separation. Musk had enough money for one more attempt.

If flight four failed, SpaceX was dead.

Flight four worked. On September 28, 2008, Falcon 1 became the first privately developed liquid-fuel rocket to reach orbit.

Musk has said he was so stressed during that period he was throwing up regularly.

The financial pressure was existential. Musk was simultaneously funding Tesla, which was also on the brink of bankruptcy in 2008.

He had to split his last $40 million between the two companies. He borrowed money for rent.

But right at the end of 2008, NASA awarded SpaceX a $1.6 billion contract to resupply the International Space Station. That contract saved the company.

Starship development has been its own saga. The rocket has exploded multiple times during testing.

Each failure costs hundreds of millions. But SpaceX treats failures as data — they move faster by blowing things up and iterating than competitors do by being cautious.

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.

SpaceX

Falcon 9 is the workhorse — the most-launched rocket in the world. It carries satellites to orbit and astronauts to the ISS, and the first stage lands itself for reuse.

Falcon Heavy is three Falcon 9 boosters strapped together — the most powerful operational rocket in the world until Starship came along. Dragon is the spacecraft that carries astronauts and cargo to the ISS.

It's the only American vehicle currently flying humans to space. Starlink is the satellite internet service — over 6,000 satellites in orbit delivering broadband to 100+ countries.

Starship is the big one — the tallest and most powerful rocket ever built, designed to carry 100+ people to Mars. It's still in testing but has already completed a full flight.

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.

SpaceX

Founders Fund, Draper Fisher Jurvetson, Google, Fidelity Investments, Valor Equity Partners, Baillie Gifford, a]6z (Andreessen Horowitz), NASA (as customer/partner)