Databricks combines enterprise functionality with open source innovations, enabling large-scale data processing. Simplify and accelerate data science on big data sets. Standardise the ML lifecycle from experiment to production.
From the original creators of Apache Spark™, Delta Lake and MLflow, software that today drives the evolution of data and AI with the help of millions of developers.
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Delta Lake
Analytics that automate and optimise business outcomes
Security
Delta Lake brings data security and scalability to your existing data lakes with an open source transaction layer designed for the entire data lifecycle.
High Performance
Simple data processing on automatically scalable infrastructure. Powered by optimised Apache Spark™ for up to fifty times faster performance.
Data Science and machine learning
Cooperation and collaboration with machine learning throughout the data and process flow.
Shared Notebooks
Get quick access to explore data, find and share new insights and the chance to build models together, using any programming language and tools.
Optimised ML environments
One-click access to pre-configured ML environments for enhanced machine learning with state-of-the-art and popular ML tools.
Complete ML lifecycle
Track and share experiments, reproduce runs and manage models together from a central repository, from experiment to production.
Business analysis
More comprehensive and up-to-date data for better insights across your organisation.
Retrieve data with SQL
Run SQL queries directly against your Data lake. Data management at a significantly lower cost than traditional cloud data warehouses.
Visualize and share insights
Visualise search results quickly and easily in Dashboards, with automatic alerts for critical changes.
Broad integration of BI tools
Use your preferred BI tools, such as Tableau and Microsoft Power BI. Optimized APIs for fast performance and low latency against your Data lake.
Enterprise-level security and administration
A secure and scalable multi-cloud platform with millions of users.
Platform security
Give all your users proper access with a comprehensive audit trail. Use your existing cloud security policies and identity management systems to create compatible, private and isolated workspaces.
360° administration
Complete availability of collaboration sites for all projects simultaneously. Easily manage user access, control data usage and analyse activity while maintaining control and security.
Scalable
Use fully configured data environments and APIs to move quickly from initiative to development and production. Once in production, data teams can use autoscaling on demand. This to optimize performance and reduce the operating time of data pipelines and ML models in production.
Multi-cloud Management
Securely integrate one platform with multiple cloud solutions so your data teams can do data analysis and machine learning without users having to learn cloud-specific tools and processes.
Comcast’s journey to building a large-scale agile data and AI platform
In this conversation, Jim Forsythe and Jan Neumann describe Comcast’s data and machine learning infrastructure, built on Databrick’s Unified Data Analytics Platform. Comcast uses databases to train and power the machine learning models at the heart of these products and gain deeper insight into how its users use these products.