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
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:
Recentrer les systèmes de soins sur les patients grâce aux 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.
Suscitez l'engagement des consommateurs à chaque interaction
Exploitez tout le potentiel du big data et de l'IA pour mieux connaître vos clients et leur offrir des expériences d'achat personnalisées qui les captivent sur tous les canaux de distribution
Étude de cas client
“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.