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Databricks Reviews

San Francisco, California

5.0/ 5

2 reviews

Databricks, Inc. is a prominent American enterprise software company that pioneered the "data lakehouse" architecture, effectively unifying data engineering, data science, business intelligence, analytics, and artificial intelligence into a single collaborative platform. Founded in 2013 by the original creators of Apache Spark at the University of California, Berkeley's AMPLab—including CEO Ali Ghodsi, Matei Zaharia, Ion Stoica, Reynold Xin, Patrick Wendell, Andy Konwinski, and Arsalan Tavakoli-Shiraji—the company was established to address the operational complexities of deploying and managing big data tools at scale. Headquartered in San Francisco, California, Databricks has grown into one of the world's most valuable private companies, reporting an annualized revenue run rate (ARR) of $5.4 billion as of early 2026 and securing equity financing at a valuation of approximately $134 billion. The cornerstone of Databricks' product strategy is its Data Intelligence Platform, which combines the flexibility, low-cost storage, and scalability of a data lake with the structure, reliability, ACID transactions, and governance typical of traditional data warehouses. Unlike proprietary systems that mandate moving data into closed environments, Databricks operates directly on top of open-source file formats like Delta Lake and Apache Iceberg within a customer’s own cloud account. This approach isolates compute from storage, mitigating vendor lock-in and eliminating costly data egress fees. The platform runs natively across major cloud infrastructures, including Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP). Technically, the platform is built upon four foundational open-source pillars originally developed or heavily supported by its founders: Apache Spark for distributed cluster computing, Delta Lake for robust storage governance, MLflow for tracking and managing machine learning lifecycles, and Unity Catalog, which provides centralized, fine-grained access control and compliance across all data and AI assets. To eliminate structural management friction, Databricks features a serverless tier that automatically provisions, sizes, and terminates compute infrastructure based on shifting workloads. In response to the rapid evolution of artificial intelligence, Databricks has integrated generative AI capabilities across its ecosystem, notably through its Mosaic AI framework—developed after acquiring MosaicML—which enables enterprises to securely build, deploy, and ground custom AI models using their corporate data. Additionally, products like Lakebase optimize transactional layers for AI applications, while autonomous agents like Genie assist technical teams with natural language analytics. Today, Databricks services more than 20,000 customers globally, including over 60% of the Fortune 500, such as Shell, Microsoft, AT&T, Mastercard, and Disney. The platform supports diverse cross-functional data teams, allowing data engineers, analysts, and data scientists to build data pipelines, run complex SQL queries, and deploy production-grade machine learning workflows seamlessly.