Databricks Unified Data Analytics on AWS

Databricks Competencies

  • Machine Learning Competency
  • Data & Analytics Competency
  • Life Sciences Competency
  • Retail Competency
  • Public Sector Partner

Databricks Unified Data Analytics on AWS

Unified data analytics platform for accelerating innovation across data science,
data engineering, and business analytics, integrated with your AWS infrastructure.


One reliable and scalable data lake
for all analytics


One collaborative workspace for data and ML teams


One platform for data science, ML, and analytics

Amazon Redshift

Databricks can read data securely from Redshift and integrate it with other datasets. With Delta Lake, Databricks can make that data into simplified and reliable data pipelines using optimized cluster resources. Data can then be used for machine learning in Databricks, or put back into Redshift for data warehouse workloads.


AWS Glue Integration

The AWS Glue service is an Apache compatible Hive serverless metastore which allows you to easily share table metadata across AWS services, applications, or AWS accounts.

This provides several concrete benefits:

  • Simplifies manageability by using the same AWS Glue catalog across multiple Databricks workspaces.
  • Simplifies integrated security by using Identity and Access Management Credential Passthrough for metadata in AWS Glue. Refer to the Databricks blog introducing Databricks AWS IAM Credential Passthrough for a detailed explanation.
  • Provides easier access to metadata across the Amazon services and access to data catalogued in AWS Glue.


Amazon SageMaker

Databricks is integrated with Amazon SageMaker using MLflow to enable distribution of machine learning models. Databricks is used to build collaborative ML models and train them at scale. The deployment enables real-time model serving and REST API integration.


Automated, High Scale Data Pipelines

Created automated data pipelines at scale that minimize cost with features such as auto-clustering and spot pricing. Using Delta Lake, you can scale up to the largest datasets, with high velocity data providing constant updates, instantly available for analytics.


Read this ebook to learn how to unify big data and AI in the financial services industry

Quickly prepare clean data at massive scale, and continuously train and deploy state-of-the-art ML models for best-in-class AI applications. Common use cases include:

  • Risk, Fraud, Intrusion Detection & Prevention
  • Customer 360 Engagements , Ad Targeting
  • Predictive Maintenance, SCM Seasonal Costing
  • Sentiment & Customer Churn Analysis
  • Security Compliance & Intelligence



Healthcare and Life Sciences

Enabling Patient-centric Healthcare with Unified Analytics

Built by the original creators of Apache SparkTM, the Databricks Unified Data Analytics Platform enables data processing and machine learning at massive scale — empowering healthcare organizations to drive innovations in care while reducing costs.



Engage Shoppers at Every Interaction

Harness the power of big data and AI to deepen customer insights and deliver tailored shopping experiences that captivate customers across every channel


Enabling AWS Single Sign-On (SSO) Service Integration with Databricks Control Plane

Databricks integrates with Amazon security and single sign-on, making it easy to roll out across your organization. Users can access Databricks with their corporate credentials using AWS SSO. This delivers a better user experience without the need for managing separate sets of credentials.


Customer Testimonial

Digital Turbine

“We needed to be able to deliver fast query responses to enable internal
business analysts. Now they are using Notebooks to query Delta Lake
directly.” – Daniel Ferrante, Director of Platform Engineering

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Customer Case Study


“Databricks, through the power of Delta Lake and Structured Streaming, allows us to deliver alerts to our product’s users with a very limited latency, so they’re able to react to problems within their home before it affects their comfort levels.” – Steven Galsworthy, Head of Data Science at Quby

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ShopRunner ingests over 1TB a day to drive online retail merchandise recommendations. They use Databricks for ingesting data, as well as for running their machine learning jobs. With the Databricks ML runtime that includes machine learning frameworks like TensorFlow, ShopRunner is making recommendations based up physical item appearance.

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Conde Nast customer testomonial

Customer Testimonial

Conde Naste

“Databricks enables us to decide in real time, without having to commit until we know this is a viable solution for our business.”

Paul Fryzel, Conde Nast

Edmunds customer testimonial

Customer Testimonial


“Our pipeline has gone from over 24 hours to refresh to less then 4 hours using Databricks.”

Josh McNutt, Showtime

Edmunds customer testimonial

Customer Testimonial


“Databricks democratizes data engineering and machine learning, and enables us to instill data driving principles.”

Gregory Rokita, Edmunds

Health Direct customer testimonial

Customer Testimonial

Health Direct

“Databricks enabled us to hit the time to market and analytics and operational uplift to meet the new demands of the healthcare sector.”

Peter James, Health Direct

Customer Case Study


“We were looking for a leader to partner with on analytics infrastructure. With Databricks we can focus our time and resources on innovating new solutions that drive our business.” – John Wulf, Principal Engineer

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FIS global customer testimonial

Customer Testimonial

FIS Global

“Databricks enables you to unlock your imagination.”

Aaron Colcord, FIS Global