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Databricks Migration | FullStack Case Study
Databricks Migration
Case Study

Migration to Databricks Accelerates Data Processing and Reliability

The client, a leading real estate investment firm, partnered with FullStack to streamline data processing, enhance performance, and significantly reduce operational costs.


Improvement in reliability

<30 minute

Data processing times, down from 8+ hours


Separate data processing services consolidated


The client, a real estate investment firm, relies on data to make critical decisions daily. Before the project, the client's data infrastructure relied on three separate data services, including costly on-premises servers. The client's internal and external data users faced frequent outages and delays due to this legacy solution.

Seeking a more efficient and modern solution, the client decided to migrate to Databricks.


FullStack worked with the client's team to perform a comprehensive data migration and transformation that involved rewriting and refactoring code to enhance performance, implementing Delta Live Tables for efficient data processing and cost management, and standardizing data processing and integration using a unified framework.

Additionally, FullStack provided training sessions to help the client's team adapt to the new platform. They established DevOps automations with GitHub to improve workflows, resulting in a streamlined, modern data infrastructure.


<30 Minute Data Processing

Data processes that previously ran overnight can now run in 10-30 minutes, enabling near real-time investing data availability.

Cost Savings & Consolidation

The new solution consolidates costs from third-party licenses and on-premises servers into a single cloud-based solution.

85% Reliability Improvement

Data outage occurrences have been reduced from 1-2 per week to <1 per month, ensuring more reliable access to critical data.

Improved Data-driven Decisions

Improved data accessibility and processing enable better and faster investment decisions. The new solution pulls near-real-time data from over 50 sources, including government tax codes.

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