Petabyte-Scale Big Data Architecture for Egyptian Government
Architecting a modern, high-performance big data solution to replace a legacy system and enable analysis of petabyte-scale datasets.
The Challenge
An Egyptian government sector was struggling with the limitations of their existing SQL Big Data Cluster (BDC). It could not efficiently handle their growing datasets, which were scaling into the petabytes. They required a new architecture that could provide rapid query performance across massive volumes of data while integrating with their existing tools and workflows.
Our Solution
Our data architects designed a cutting-edge big data solution to meet their performance and scalability needs.
Dremio Query Engine:
We implemented Dremio as the core query engine, providing a high-performance, SQL-native interface over their data lake, enabling lightning-fast queries on petabyte-scale data.
Airflow Orchestration:
We used Apache Airflow to orchestrate complex data ingestion and transformation pipelines, ensuring reliable and automated data workflows.
SQL Server Integration:
The solution was seamlessly integrated with their existing SQL Server environment, allowing analysts to continue using familiar tools while benefiting from the new architecture's power.
The Impact
The new architecture empowered the government entity to analyze massive datasets with unprecedented speed and efficiency. The solution successfully handled petabytes of data, reduced query times from hours to minutes, and provided a scalable platform to support their future analytical needs, all while integrating smoothly into their existing ecosystem.
Project Overview
Key details about the engagement.
Client
Egyptian Government Sector
Services
Data Architecture, Big Data
Technologies
Dremio, Apache Airflow, SQL Server