Databricks

Databricks, Inc. is a global data, analytics, and artificial intelligence (AI) company, founded in 2013 by the original creators of Apache Spark.^{[1] [4]} The company provides a cloud-based platform to help enterprises build, scale, and govern data and AI, including generative AI and other machine learning models.^[5]

Databricks pioneered the data lakehouse, a data and AI platform that combines the capabilities of a data warehouse with a data lake, allowing organizations to manage and use both structured and unstructured data for traditional business analytics and AI workloads.^[6] The company similarly develops Delta Lake, an open-source project to bring reliability to data lakes for machine learning and other data science use cases.^[7]

Databricks grew out of the AMPLab project at University of California, Berkeley that was involved in making Apache Spark, an open-source distributed computing framework built atop Scala. The company was founded by Ali Ghodsi, Andy Konwinski, Arsalan Tavakoli-Shiraji, Ion Stoica, Matei Zaharia,^[8] Patrick Wendell, and Reynold Xin.^{[citation needed ]}

In November 2017, the company was announced as a first-party service on Microsoft Azure via integration Azure Databricks.^[9]

In February 2021, together with Google Cloud, Databricks provided integration with the Google Kubernetes Engine and Google's BigQuery platform.^[10] At this point in time, the company said more than 5,000 organizations used its products.^[11]

Fortune ranked Databricks as one of the "Best Large Workplaces for Millennials" in 2021.^[12]

In November 2023, Databricks unveiled the Databricks Data Intelligence Platform, a new offering that combines the unification benefits of the lakehouse with MosaicML’s Generative AI technology to enable customers to better understand and use their own proprietary data.^[13]

The firm was valued at 62ドル billion in December 2024,^[14] following a funding round that raised one of the largest amounts in history, an equivalent to the largest single AI investment ever made.^[15]

In June 2020, Databricks bought Redash, an open-source tool for data visualization and building of interactive dashboards.^[16] In 2021, it bought German no-code company 8080 Labs whose product, bamboolib, allowed data exploration without any coding.^[17] In May 2023, Databricks bought data security group Okera, extending Databricks data governance capabilities.^[18] In June, it bought the open-source generative AI startup MosaicML for 1ドル.4 billion.^{[19] [20]} In October, Databricks bought data replication startup Arcion for 100ドル million.^[21] In what is believed to be its sixth acquisition, Databricks bought Tabular, a data-management system used by open source AI, for over 1ドル billion.^[22]

In March 2023, in response to the popularity of OpenAI's ChatGPT, the company introduced an open-source language model, named Dolly after Dolly the sheep, that allowed developers to create chatbots. Dolly uses fewer parameters to produce similar results as ChatGPT, but Databricks had not released formal benchmark tests to show whether its bot actually matched the performance of ChatGPT.^{[23] [24] [25]}

Databricks reported 1ドル.6 billion in revenue for the 2023 fiscal year, more than doubling its previous level.^[26]

In September 2013, Databricks announced it raised 13ドル.9 million from Andreessen Horowitz and said it aimed to offer an alternative to Google's MapReduce system.^{[27] [28]} Microsoft was a noted investor of Databricks in 2019, participating in the company's Series E at an unspecified amount.^{[29] [30]} The company has raised 1ドル.9 billion in funding, including a 1ドル billion Series G led by Franklin Templeton at a 28ドル billion post-money valuation in February 2021. Other investors include Amazon Web Services, CapitalG (a growth equity firm under Alphabet Inc.) and Salesforce Ventures.^[11] In August 2021, Databricks finished its eighth round of funding by raising 1ドル.6 billion and valuing the company at 38ドル billion.^[31] In December 2024, Databricks announced a 10ドル billion financing at a valuation of 62ドル billion.^[14]

Databricks develops and sells a cloud data platform using the marketing term "lakehouse", a portmanteau of "data warehouse" and "data lake".^[41] Databricks' Lakehouse is based on the open-source Apache Spark framework that allows analytical queries against semi-structured data without a traditional database schema.^[42] In October 2022, Lakehouse received FedRAMP authorized status for use with the U.S. federal government and contractors.^[43]

The company has also created Delta Lake, MLflow and Koalas, open source projects that span data engineering, data science and machine learning.^{[44] [45]}

In June 2020, Databricks launched Delta Engine, a fast query engine for Delta Lake,^[46] compatible with Apache Spark and MLflow.^[47]

In November 2020, Databricks introduced Databricks SQL (previously called SQL Analytics) for running business intelligence and analytics reporting on top of data lakes. Analysts can query data sets with standard SQL or use connectors to integrate with business intelligence tools like Holistics,^[48] Tableau, Qlik, SigmaComputing,^[49] Looker, and ThoughtSpot.^[50]

Databricks offers a platform for other workloads, including machine learning, data storage and processing, streaming analytics, and business intelligence.^[51]

In early 2024, Databricks released the Mosaic set of tools for customizing, fine-tuning and building AI systems. It includes AI Vector Search for building RAG models; AI Model Serving, a service for deploying, governing, querying and monitoring models fine-tuned or pre-deployed by Databricks; and AI Pretraining, a platform for enterprises to create their own LLMs.^[52]

In March 2024, Databricks released DBRX, an open-source foundation model. It has a mixture-of-experts architecture and is built on the MegaBlocks open-source project.^[53] DBRX cost 10ドル million to create. At the time of launch, it was the fastest open-source LLM, based on commonly-used industry benchmarks. It beat other models like Llama 2 at solving logic puzzles and answering general knowledge questions, among other tasks. And while it has 136 billion parameters, it only uses 36 billion, on average, to generate outputs.^[54] DBRX also serves as a foundation for companies to build or customize their own AI models. Companies can also use proprietary data to generate higher-quality outputs for specific use cases.^[55]

In addition to building the Databricks platform, the company has co-organized massive open online courses about Spark^[56] and a conference for the Spark community called the Data + AI Summit,^[57] formerly known as Spark Summit.^[58]

In December 2024, Databricks along with Wiz and Workday has decided to run their products on top of AWS via the new button called "Buy with AWS button".^[59]

Databricks is headquartered in San Francisco.^[60] It also has operations in Canada, the United Kingdom, and elsewhere.^[61]

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