This guide dives into the technical steps required to migrate from Amazon Redshift to Databricks. Covering everything from discovery and data evaluation to security protocols and cost estimation, it offers detailed, practical strategies for managing dependencies, optimizing queries, and planning for future scalability within Databricks’ robust ecosystem.

There is a lot of buzz around GenAI, LLMs, AI, and ML. Knowing what you should implement or not implement is tough.
In this set of 3 videos, our Technical Advisor Josue Bogran has a frank and open conversation about these subjects with Denny Lee, Principal Developer Advocate at Databricks.

Databricks SQL is easy to get started and highly performant. Don't just take our word for it. Check out the video our technical advisor Josue put out that shows how simple it is to get started with, as well as another video that he did comparing Databricks vs Snowflake query performance.

This blog introduces the strategic benefits and challenges of migrating from Amazon Redshift to Databricks. It covers Redshift’s legacy limitations, Databricks' advantages, and critical migration factors. The article provides an overview of key planning steps, including architecture considerations and phased migration strategies, setting the stage for technical execution in the upcoming part two.

Sigma offers a user-friendly BI tool ideal for building and managing dashboards. With intuitive features, seamless embedding, and live data connections, it excels in usability. However, its steep pricing and lack of Git integration may deter small businesses. SunnyData recommends Sigma for startups and enterprises seeking responsive, customizable solutions.

This blog explores the migration process of Databricks from one cloud provider (GCP) to another (Azure or AWS). It emphasizes using tools like Terraform for seamless migration, best practices for handling resources, data, and configurations, and discusses strategic reasons for switching cloud platforms.

Databricks vs. Snowflake vs. Fabric evaluates key aspects like toolsets, partner ecosystems, flexibility, ease of use, and overall business value. We break down each platform's strengths and weaknesses to guide you in choosing the best for your data strategy.

Databricks is a top choice for startups seeking an all-in-one data platform for analytics, AI, and data management. Its cloud-native, scalable, and cost-efficient architecture allows startups to begin small, grow, and avoid complex migrations as needs evolve.

In this blog, we outline the essential steps for migrating ETL workloads and EDW from Snowflake to Databricks. From data migration to report modernization, we break down five key phases for a seamless and efficient transition to Databricks.

This blog explores why companies are increasingly migrating from Snowflake to Databricks, highlighting Databricks’ integrated platform, cost-efficiency, and comprehensive data and AI capabilities. The post examines the pitfalls of Snowflake's pricing and its struggle to replicate Databricks' functionality.

This blog compares Microsoft Fabric and Databricks, focusing on pricing, features, governance, and scalability. It concludes that while Fabric suits smaller businesses, Databricks excels for medium to large enterprises due to its flexibility, innovation, and advanced data capabilities.

Migrating to Databricks offers companies unmatched benefits, including cost efficiency, scalability, and advanced AI/ML capabilities. With a unified platform and robust data governance, Databricks empowers businesses to modernize their data estates, ensuring they’re future-ready and positioned for growth.

This blog argues against the rush to adopt the latest AI technologies, emphasizing the importance of strong data engineering foundations and "Classic Analytics." It advocates for a balanced, pragmatic approach to AI adoption, ensuring long-term success over short-term gains.

Databricks AI/BI Genie leverages advanced AI models and Unity Catalog to answer business-specific queries with precision. This blog explores its potential to surpass traditional dashboards, offering a powerful tool for real-time, self-service analytics in a governed environment.

This article provides an initial analysis of Microsoft Fabric, comparing it with Databricks. It discusses why Fabric may not meet enterprise needs and explores potential integrations between Fabric and Databricks, highlighting how they can complement each other in data projects.