In the rapidly evolving world of big data and cloud computing, two companies have emerged as rivals, vying for supremacy in the market of data analytics and AI — Snowflake and Databricks. We first covered this rivalry in a deep dive in a deep dive in September 2022. Since then, this rivalry has only intensified, with both companies pushing the boundaries of innovation and competing aggressively for market share.
Founded in the early 2010s, Snowflake and Databricks initially occupied separate niches in the data software landscape.
Snowflake was founded in 2012 by former Oracle architects Benoit Dageville and Thierry Cruanes. They set out to create a cloud-native data warehouse that could overcome the limitations of traditional on-premise solutions. Snowflake's platform has since evolved into a comprehensive "data cloud" enabling efficient data sharing, application development, and advanced analytics. It’s known for its user-friendly solutions, which make it particularly appealing to business analysts and data engineers.
Databricks, founded a year later in 2013 by a group of researchers from UC Berkeley, took a different path. Initially centered around Apache Spark, Databricks quickly expanded its platform to introduce the "data lakehouse" architecture — a hybrid of data lakes and warehouses. This platform is heavily favored by data scientists and machine learning engineers, offering advanced capabilities for data analysis and machine learning.
In the beginning, their relationship was even cooperative, with Databricks' marketing team using Snowflake for analytics.
However, as both companies expanded their offerings, they found themselves increasingly in direct competition. Snowflake's growth was meteoric, culminating in the largest-ever software IPO in 2021. Databricks, while still private, has become one of the world's highest-valued startups, with a highly anticipated IPO.
Databricks, once considered the "little brother," has taken on a more antagonistic stance with aggressive marketing and sales tactics. Their "SnowMelt" initiative aims to poach Snowflake's clients, especially in data warehousing. Databricks offers bonuses to salespeople who convert Snowflake clients and even helps pay off prospects' existing Snowflake contracts to encourage switching. When Snowflake held its 2023 user conference in Las Vegas, Databricks had billboards waiting at the airport and conference venue, claiming their product was nine times cheaper.
Databricks' pitch centers on being less expensive and offering a wider suite of advanced features, particularly for AI model building. They've equipped their sales team with tools to estimate potential savings for clients switching from Snowflake. Meanwhile, Snowflake maintains that its offering is more cost-effective. Christian Kleinerman, Snowflake's product chief, encourages customers to run their own benchmarks to compare costs.
The latest chapter in this fierce rivalry unfolded when Snowflake, looking to enhance its AI capabilities, entered exclusive negotiations to acquire Tabular for more than $600 million. Tabular was seen as a potentially meaningful asset to help Snowflake catch up in AI.
However, Databricks swooped in and ended up paying nearly $2 billion for Tabular. This price tag was a lofty valuation for a startup generating only about $1 million in annual recurring revenue.
As the battle continues, each company continues to enhance their offerings, all while facing the looming threat of Microsoft, which could leverage their vast resources to capture market share in this space.
The Snowflake / Databricks rivalry represents more than just a corporate competition — it is shaping the future of data analytics and cloud computing by driving innovation and expanding the capabilities of cloud data platforms. As both companies continue to blur the lines between data warehousing and data lake functionalities, the real winners may well be the customers who benefit from increasingly powerful and sophisticated data solutions.
