Legacy to Cloud Migration: Moving from Exasol

Businesses continue to migrate legacy systems to the cloud, driven by the need for cost savings, faster performance and stronger security. This shift, known as legacy to cloud migration, often means swapping old-school data warehousing tools like Exasol for modern cloud platforms like Amazon Redshift. Cloud warehouses let companies ditch traditional licensing fees for a flexible pay-as-you-go payment model, work seamlessly with other cloud tools and keep their data organized and easy to manage. In short, switching to the cloud gives companies all the best cloud benefits.

Switching from outdated legacy systems like Exasol allows businesses to embrace modern technologies. In this article, we'll dive into why moving from Exasol to a cloud-native warehouse is the smarter choice.

Switching from Exasol to Amazon Redshift

Switching to Amazon Redshift empowers businesses with advanced cloud technology to streamline operations, gain a competitive edge and achieve their strategic goals more effectively. Let's break down why this shift makes sense and what benefits it brings.

Why Move from Exasol to Amazon Redshift?

With growing market demands for faster, more flexible infrastructure, businesses are looking for better options. Traditional tools like Exasol and other outdated systems (on-premise infrastructure) can't keep up with the need for scalability and performance. That's where cloud-based solutions like Amazon Redshift shine — they're super dynamic, can easily scale up as needed and work seamlessly with other cloud infrastructure. Plus, they're faster and more efficient for handling data, making this switch a no-brainer for businesses that want to stay ahead.

Moving from Exasol to Amazon Redshift, a solution from cloud provider AWS, comes with perks, and here are the top reasons why businesses are making the switch:

• Handle Big Data with Ease: Amazon Redshift's massive scalability makes it perfect for managing tons of data without slowing down.

• Save Money: Amazon Redshift is cost-effective — you only pay for what you need. You can adjust storage and computing power as you go, so you're not stuck overpaying for unused resources.

• Seamless Integration: Switching to Amazon Redshift lets companies take full advantage of other AWS cloud services, making it easier to innovate, build apps and solve problems faster.

Benefits of Migrating from Exasol to Amazon Redshift

Moving legacy applications like Exasol to Amazon Redshift is a core step in legacy system modernization, optimizing data management and analytics operations. Here's how:

1. Built-in Cloud Integration

Amazon Redshift connects effortlessly with AWS tools like S3 for storage, Kinesis for real-time data streaming and Lambda for serverless computing. It also operates in a secure Virtual Private Cloud (VPC) and employs robust security measures to keep your data safe.

With everything under one roof, Amazon Redshift simplifies workflows, makes business operations more efficient and amps up performance. Additionally, AWS access management tools provide robust security and protection.

2. Scale Without Stress

Amazon Redshift's flexibility means businesses can start small and crank things up as their needs grow. Whether your data needs suddenly spike or shrink, Amazon Redshift's resizing features make it easy to adjust capacity without breaking a sweat.

Unlike traditional data centers, Amazon Redshift provides the flexibility businesses need when moving legacy apps to support dynamic workloads without stress.

3. Less Maintenance, Fewer Headaches

Managing Exasol on a cloud setup like AWS can get complicated fast. You'd need to juggle different providers, deal with downtime during updates and be on edge about potential failures. With Amazon Redshift, migrating applications to the cloud is significantly easier. Its automated features — like backups, regular updates and security patches — lighten the load for IT teams and keep the system running smoothly without interruptions.

Running legacy applications like Exasol often requires significant upkeep. Once you migrate legacy applications to a fully managed service like Amazon Redshift, these maintenance headaches are significantly reduced.

4. Faster Queries, Better Performance

Amazon Redshift takes query performance up a notch by pre-computing and caching results for repeated queries. This means you get data faster, use less computing power and boost efficiency.

5. Smarter Data Management

Amazon Redshift works seamlessly with tools like Delta Lake, offering features like transaction tracking, versioning and strong data consistency. It's easier to keep your data organized, maintain reliability and handle big workloads.

Migration Challenges

When moving from Exasol to Amazon Redshift, there are some key differences between the two platforms that you need to consider. To begin with, data types and schemas often don't align perfectly, requiring you to clean and adjust them during the transition process.

Another thing to watch out for is SQL code — some functions in Exasol don't work in Amazon Redshift. For example, the REGEXP_SUBSTR function behaves differently in Amazon Redshift, which means you'll need to rewrite those queries with alternative logic that works.

If you're working with Lua scripting in Exasol, here's an important note: Amazon Redshift doesn't support Lua. To make your logic compatible, you'll need to rewrite any Lua-based scripts in another language, such as Python.

"The success of our Exasol to Redshift migration came from two factors: first, understanding the complexity of Lua code and its dependencies within the legacy system; and second, applying GenAI automation through migVisor to reduce the risk of failure and accelerate transformation." — Vitalii Bondarenko, Principal of Data Analytics Consulting at EPAM

Finally, transferring historical data can be a bit tricky. Amazon Redshift doesn't let you directly pull data from Exasol — it requires staging the data externally (like in S3) before you can load it. This extra step can make the process more complicated, so you'll need to stay organized and develop a detailed migration plan.

These key areas need careful attention to make sure everything works smoothly and you get the most out of your move to Amazon Redshift.

Migration Automation Approach

Automation plays a huge role in legacy application migration. It cuts down the effort, cost and risks involved, making the whole process faster and smoother. If automation handles more than 50% of the heavy lifting — such as converting SQL and UDF code, validating data and analyzing dependencies — it turns data migration from a frustrating technical problem into a game-changing business move.

The best part? Automation doesn't just speed things up. It keeps everything consistent, improves the quality of the work and frees up your team to focus on the big stuff, like optimizing systems and coming up with new ideas. By using automation, businesses can transform their data platforms quickly, avoiding headaches and saving money.

Example for GenAI Automation of Code Conversion using migVisor Code Converter

EPAM's migVisor Code Converter simplifies the process of migrating Lua-based logic from Exasol UDFs to Python, making it faster and more accurate to modernize older analytics workflows. The tool uses configurable conversion rules, metadata extraction and AI-assisted translation to automate up to 80% of the code transformation. This includes control flows, data parsing, business rules and expression handling.

It evaluates code complexity, generates modular Python UDFs that work with platforms like Amazon Redshift or Databricks, and flags portions that need manual tweaking to ensure no functionality is lost. The Code Converter fits into EPAM's larger framework for migration and validation, which includes automated linting, regression testing and logic verification. This reduces manual rewriting, improves consistency and speeds up deployment.

By replacing older scripting dependencies and shifting to scalable, cloud-ready platforms with modern programming standards, enterprises can simplify their workflows and improve flexibility.

migVisor is a collaborative framework of AI agents designed to automate and accelerate code conversion during modernization projects, such as migrating legacy software. Each agent specializes in a key step of the process — code extraction, classification, parsing and conversion, validation, review, packaging and guided manual adjustment. By working together, these agents ensure high automation coverage, consistent output quality and reduced manual effort, making migVisor a scalable and intelligent solution for modernizing legacy data platforms.

migVisor uses AI to simplify every step of migration, from pulling code to validating it. It cuts down on manual work, speeding up timelines by 3–4 times compared to old-school methods. By automating both simple and complex tasks, it reduces errors and keeps everything consistent, so teams can focus on improving systems — not redoing work.

migVisor is built on a modular agent design — small, reusable components that can be updated or replaced seamlessly without affecting the system. This architecture simplifies upgrades, enables scalability for large projects and allows quick adaptation to emerging technologies.

It supports:

• Faster Workflows: Run multiple tasks at once.

• Smooth Coordination: Keep all systems working together.

• Flexibility: Adjust to new platforms as needed.

With migVisor, companies get a future-proof system that grows with their needs.

The migVisor Code Converter runs in a virtual machine (VM) using Docker containers to keep things organized and portable. Each part of the system — like the web UI, backend logic, file storage and local PostgreSQL database — works independently, making it easy to set up in different environments. Docker ensures everything runs consistently, whether in development, testing or production and avoids any annoying dependency conflicts.

Here's what each container does:

• Web UI (via NGINX): Handles workflows and user interactions.

• Backend (Python API): Manages the logic and converts code.

• Web Tools: Includes a Web IDE (VS Code) and File Browser, so engineers can edit and validate converted files directly.

Data is stored securely in a local PostgreSQL database and a protected Data Vault, with smart LLM integration to automate tricky conversions and offer helpful suggestions.

This setup ensures migVisor is scalable, secure and highly adaptable. Engineers can work safely within isolated containers while seamlessly collaborating, making it an ideal solution for modernizing complex legacy systems with ease and efficiency.

Example for Automation of Data Reconciliation using migVisor Reconciler

migVisor Reconciler ensures that data stays accurate and consistent during the switch. Since Exasol's in-memory system with Lua is different from Amazon Redshift's cloud setup, issues like mismatched data types, schemas or logic can pop up. The Reconciler fixes this by automating tasks like schema alignment, row count checks and column-level comparisons between the two platforms. Using AI-driven mapping, it runs quick, detailed or deep data validations to ensure everything carries over smoothly and stays traceable.

What makes migVisor Reconciler stand out is that it's built right into the migration workflow. It catches inconsistencies early, saves time on manual validation and boosts confidence in the accuracy of the datasets. Designed to work at scale, it's perfect for major migrations, making sure analytics, reporting and everything downstream in Amazon Redshift runs flawlessly.

One of the biggest perks of using migVisor Reconciler is how much manual work it eliminates — cutting reconciliation costs by up to 90% compared to doing it the old-fashioned way. This means faster project timelines and more trust in the accuracy of the migrated data. It's a must-have for smooth and reliable large-scale migrations.

Retail Company Migration Case Study

Facing challenges with Exasol, a retail company decided to migrate to Amazon Redshift. This effort focused on enhancing scalability, performance and seamless cloud integration, using the innovative migVisor Suite to automate the migration process.

Challenges Faced

The company faced a set of challenges that required innovative solutions to ensure a smooth transition and optimal system efficiency:

1. Different data types and structures in Exasol versus Amazon Redshift required schema adaptations.

   Solution: Implemented migVisor Suite for automated schema conversion to minimize manual adjustments.

2. Exasol's support for SQL and Lua needed conversion to Amazon Redshift's SQL-only.

   Solution: Utilized migVisor Code Converter for automated script conversion and manual efforts for syntax adaptation.

3. Migrating in-memory database queries to Amazon Redshift sometimes delivered suboptimal performance.

   Solution: Post-migration tuning involved selecting optimal distribution keys and managing concurrency for better performance.

4. Large data transfer posed risks of downtime and bottlenecks.

   Solution: Implemented phased migrations using AWS Database Migration Service and S3 for efficient data handling.

5. Ensuring data integrity post-migration was crucial yet challenging with large datasets.

   Solution: Used migVisor Reconciler for automated reconciliation to ensure data accuracy and consistency.

6. Hidden dependencies in Exasol required careful mapping to avoid transition issues.

   Solution: Used migVisor Analytics as a dependency mapping tool and automated assessment to identify and manage data relationships.

Migration Results

Switching to Amazon Redshift shows how cloud migration can level up a business's capabilities. Here's what this retail company gained:

• Enhanced Data Management: With Amazon Redshift's scalable architecture, they transformed their data handling capabilities, effortlessly adapting to their growing needs.

• Accelerated Performance: Amazon Redshift delivered powerful data processing tools, enabling lightning-fast analytics for modern business demands.

• Seamless Integration: Redshift integrated smoothly with other AWS services, streamlining workflows and ensuring business operations run efficiently.

The move solved their scalability and integration struggles while boosting efficiency. Using EPAM's migration framework, they successfully migrated over 50,000 reporting objects and reworked complex Lua scripts — all without major hiccups.

This retail company achieved a 50% reduction in costs and enhanced data accuracy during reconciliation, all thanks to the advanced automation capabilities of the migVisor Suite.

"With migVisor, we not only automated code conversion and reconciliation. By applying an AI Agentic approach and training an LLM with the knowledge from the Exasol migration, we turned this one-time effort into reusable modernization assets. This made the Exasol-to-Redshift migration repeatable, scalable and a foundation for future modernization projects." — Vitalii Bondarenko, Principal of Data Analytics Consulting at EPAM

Cloud Migration Execution

The transition from Exasol to Amazon Redshift was facilitated through a partnership with EPAM, which focused on enhancing scalability, performance and cloud integration.

Supported by EPAM's specialized Exasol Migration and Modernization service, the retail company initiated a rigorous cloud migration strategy:

1. Initial Assessment and Strategy Formulation

EPAM worked closely with the retail company to figure out its main challenges, data management needs and goals. This phase was all about laying a solid foundation — getting the objectives super clear and making sure they matched the company's bigger business plans.

Once everything was mapped out, EPAM created a tailored cloud migration strategy, breaking it into clear steps, setting measurable success targets and prioritizing tasks on a realistic timeline.

2. Architecture Development and Technical Implementation

EPAM designed an optimal architectural framework for seamless integration within a cloud environment using Amazon Redshift to meet the retail company's immediate and future operational needs. They ran a detailed analysis of the existing Exasol setup to pinpoint any tricky areas or roadblocks.

For the migration itself, EPAM used advanced tools like the migVisor suite to automate key processes — making it easier to transfer data and transform the underlying logic. The result? A smooth transition with almost no disruptions, helping the company shift to the cloud without slowing operations.

3. Performance Optimization and System Validation

EPAM focused heavily on optimizing system performance and testing everything during and after the migration. They monitored the system constantly, ran tests on data, logic and reports and ensured everything was working perfectly. A detailed plan made the move to live operations smooth and stress-free.

4. Cutover Execution and Ongoing Support

After the migration, EPAM provided ongoing support to fix any immediate issues and tune the system for real-world use. They made sure everything aligned with the company's needs and kept improving the setup for long-term success.

EPAM used the migVisor Suite to make the migration process faster and easier:

1. Automated Pre-Migration Analysis: Conducted by migVisor Analytics, this phase involved scanning Exasol environments to identify dependencies. This information informed the design of the target architecture and enhanced the strategy.

2. Efficient Execution: With the migVisor Converter, EPAM automated the move to Amazon Redshift. This included transferring data, redirecting BI reports and setting up data replication, skipping the manual headaches.

3. Post-Migration Optimization: EPAM used migVisor Reconciler to double-check the accuracy of the migrated data. They also created a clear plan for going live to make sure everything worked seamlessly for the retail company's needs.