Databricks has a total of 24 patents globally, out of which 19 have been granted. Of these 24 patents, 100% patents are active. United States of America is where Databricks has filed all the patents, it has generated an annual revenue of $425 million in the year 2020. Parallelly, United States of America seems to be the main focused R&D center and is also the origin country of Databricks. Databricks’ initial public offering (IPO) has yet to be declared, but anticipation is building for its impending listing.
Databricks was founded in the year 2013 by Ali Ghodsi, Reynold Xin, Matei Zaharia, and Ion Stoica. Company is doing business in open source projects that span data engineering, data science and machine learning. As of December 2021, Databricks has a market valuation of over $38 Billion.
Do read about some of the most popular patents of Databricks which have been covered by us in this article and also you can find Databricks’ patents information, the worldwide patent filing activity and its patent filing trend over the years, and many other stats over Databricks’ patent portfolio.
How many patents does Databricks have?
Databricks has a total of 24 patents globally. These patents belong to 13 unique patent families. Out of 24 patents, 24 patents are active.
How many Databricks patents are Alive/Dead?
Worldwide Patents
Patent Families
How Many Patents did Databricks File Every Year?
Are you wondering why there is a drop in patent filing for the last two years? It is because a patent application can take up to 18 months to get published. Certainly, it doesn’t suggest a decrease in the patent filing.
| Year of Patents Filing or Grant | Databricks Applications Filed | Databricks Patents Granted |
| 2015 | 4 | – |
| 2016 | 2 | – |
| 2017 | 8 | 4 |
| 2018 | 3 | 3 |
| 2019 | 3 | 4 |
| 2020 | 4 | 6 |
| 2021 | – | 2 |
How Many Patents did Databricks File in Different Countries?
Countries in which Databricks Filed Patents
| Country | Patents |
| United States Of America | 24 |
Where are Research Centers of Databricks Patents Located?
10 Best Databricks Patents
US10769130B1 is the most popular patent in the Databricks portfolio. It has received 12 citations so far from companies like Data. World, Dell and Snowflake.
Below is the list of 10 most cited patents of Databricks:
| Publication Number | Citation Count |
| US10769130B1 | 12 |
| US20210011901A1 | 8 |
| US20200409768A1 | 8 |
| US10810051B1 | 8 |
| US20200257689A1 | 8 |
| US20200241950A1 | 8 |
| US10691433B2 | 8 |
| US10678536B2 | 8 |
| US10606675B1 | 8 |
| US10558664B2 | 8 |
What Percentage of Databricks US Patent Applications were Granted?
Databricks (Excluding its subsidiaries) has filed 13 patent applications at USPTO so far (Excluding Design and PCT applications). Out of these 13 have been granted leading to a grant rate of 100%.
Below are the key stats of Databricks patent prosecution at the USPTO.
Which Law Firms Filed Most US Patents for Databricks?
| Law Firm | Total Application | Success Rate |
| Van Pelt Yi & James Llp | 13 | 100.00% |
“Databricks takes the pain out of cluster management, and puts the real power of these systems in the hands of those who need it most: developers, analyst, and data scientists are now freed up to think about business and technical problems.” — Shaun Elliott
The use of data is at the heart of how these modern businesses are evolving. With this information, businesses can take advantage of AI’s promise to produce disruptive technologies that will influence practically every company on the planet. The problem most businesses confront is figuring out how to succeed with both data and AI.
The Unified Analytics Engine, Apache Spark
Enterprises are increasingly using Apache Spark to circumvent the challenges associated with walled data and diverse platforms for managing different analytic operations. Due to its record-breaking speed, ease of use, and support for advanced analytics, Spark, which was built by the founders of Databricks, has become the de facto standard for data processing and AI today. Spark makes AI data preparation easier by combining data from a variety of sources, including cloud storage systems, distributed file systems, key-value stores, and message buses, at a large scale. Spark also brings together data and AI with a consistent set of APIs for data loading, batch/stream processing, SQL analytics, stream analytics, graph analytics, machine learning, and deep learning, as well as seamless integration with popular AI frameworks and libraries like TensorFlow, PyTorch, R, and SciKit-Learn.
List of Databricks Patents
| Databricks Patents | Title |
| US11113043B2 | Split front end for flexible back end cluster processing |
| US11068447B2 | Directory level atomic commit protocol |
| US20210011901A1 | Update and query of a large collection of files that represent a single dataset stored on a blob store |
| US20200409768A1 | Autoscaling using file access or cache usage for cluster machines |
| US10810051B1 | Autoscaling using file access or cache usage for cluster machines |
| US10769130B1 | Update and query of a large collection of files that represent a single dataset stored on a blob store |
| US20200257689A1 | Structured cluster execution for data streams |
| US20200241950A1 | Query watchdog |
| US10691433B2 | Split front end for flexible back end cluster processing |
| US10678536B2 | Callable notebook for cluster execution |
| US10606675B1 | Query watchdog |
| WO2020046441A1 | Split front end for flexible back end cluster processing |
| US10558664B2 | Structured cluster execution for data streams |
| US10474501B2 | Serverless execution of code using cluster resources |
| US10474736B1 | Multiple display views for a notebook |
| US10361928B2 | Cluster instance management system |
| US10296329B2 | Callable notebook for cluster execution |
| US10095735B2 | System for exploring data in a database |
| US9990230B1 | Scheduling a notebook execution |
| US9959337B2 | Independent data processing environments within a big data cluster system |
| US9836302B1 | Callable notebook for cluster execution |
| US9769032B1 | Cluster instance management system |
| US9760602B1 | System for exploring data in a database |
| US9659081B1 | Independent data processing environments within a big data cluster system |