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
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.
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:
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.
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.
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:
Patientenorientierte Gesundheitsversorgung – mit Databricks Unified Analytics-Plattform
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.
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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.
“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
“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
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.
“Our pipeline has gone from over 24 hours to refresh to less then 4 hours using Databricks.”
Josh McNutt, Showtime
“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