Azure Databricks

Accelerate Insight with Databricks on Azure

Azure Databricks delivers performance, scale, and elasticity for data-driven businesses. Korcomptenz helps you harness it for analytics, ML, and GenAI—streamlining pipelines, governance, and cost. Azure Databricks integrates seamlessly with Azure Storage, Azure SQL Database, and Azure Machine Learning Studio to quickly build and deploy secure, end-to-end analytics and AI solutions.

Microsoft Azure Partner with Data & AI Expertise

As an Azure Certified Partner, we provide expert insight into why to use Azure Databricks in enterprise-class data and AI environments, maintaining optimal performance, governance, and compliance.

Data engineering

Design and operate high-performance data pipelines to process and change massive amounts of structured and unstructured data.

Machine learning

Streamline model development with collaborative notebooks, automated machine learning, and native Azure Machine Learning integration.

Business intelligence

Drive deeper insights with more powerful analytics, interactive dashboards, and effortless data visualization tools.

Driving Intelligent Outcomes with Azure Databricks

Superior Price-Performance for SQL Workloads

Proven at Enterprise Scale

Seamless, Native Azure Integration

Core Capabilities of Azure Databricks

Designed for Apache Spark-Based Big Data Analytics

Built on Apache Spark, Azure Databricks speeds up massive-scale data processing with optimized runtimes for ETL, streaming, and advanced analytics.

Collaborative Notebooks for Data Science and ML

Interactive notebooks are supported for Python, R, and SQL, with real-time collaboration, experiment tracking, and integrated ML workflows for accelerated model building.

Collaborative Notebooks for Data Science and ML

Interactive notebooks are supported for Python, R, and SQL, with real-time collaboration, experiment tracking, and integrated ML workflows for accelerated model building.

Scalability and Performance for Complex Pipelines

Auto-scaling compute and performance-optimized execution engines provide consistent performance for high-demand data pipelines, from ingestion to real-time analytics and AI.

Scalability and Performance for Complex Pipelines

Auto-scaling compute and performance-optimized execution engines provide consistent performance for high-demand data pipelines, from ingestion to real-time analytics and AI.

Secure and Compliant Enterprise-Grade Environment

Built-in identity, access control, encryption of data, and support for leading standards provide enterprise-level security for all Azure Databricks workloads.

Designed for Apache Spark-Based Big Data Analytics

Built on Apache Spark, Azure Databricks speeds up massive-scale data processing with optimized runtimes for ETL, streaming, and advanced analytics.

Collaborative Notebooks for Data Science and ML

Interactive notebooks are supported for Python, R, and SQL, with real-time collaboration, experiment tracking, and integrated ML workflows for accelerated model building.

Collaborative Notebooks for Data Science and ML

Interactive notebooks are supported for Python, R, and SQL, with real-time collaboration, experiment tracking, and integrated ML workflows for accelerated model building.

Scalability and Performance for Complex Pipelines

Auto-scaling compute and performance-optimized execution engines provide consistent performance for high-demand data pipelines, from ingestion to real-time analytics and AI.

Scalability and Performance for Complex Pipelines

Auto-scaling compute and performance-optimized execution engines provide consistent performance for high-demand data pipelines, from ingestion to real-time analytics and AI.

Secure and Compliant Enterprise-Grade Environment

Built-in identity, access control, encryption of data, and support for leading standards provide enterprise-level security for all Azure Databricks workloads.