Extract-Transform-Load (ETL) is a crucial component of any data gathering and delivery pipeline. It helps structure huge chunks of data and simplifies work to reach the designated business objectives. For enterprises, there are differences between using the custom on-premise ETL solution or leaning toward cloud-based solutions delivered by Google Cloud, Microsoft Azure, or Amazon Web Services. When talking about the latter, the AWS-based ETL primary solution called Glue is a serverless data integration service that provides data analytics, machine learning, and application development capabilities.
If you’ve previously used the custom data integration and ETL solution, migrating to the AWS infrastructure can be a pivotal operations solution. In this article, you’ll learn about AWS ETL tools, how to make the most of migrating to Glue, crucial benefits, and components. Moreover, we will take a look at two case studies illustrating the merits of the ETL AWS migration.
Migrating to AWS Glue and making the most of it
When choosing from available AWS ETL tools, Glue stands out by a large margin. Compared to Data Pipeline, another AWS ETL instrument, Glue has extended functionality for performing ETL operations and setting up crawlers to connect the data sources. In short, Glue is a fully managed ETL service that provides all the capacities required for data integration. AWS Glue assists in optimizing mundane tasks, such as discovering, extracting, cleaning, optimizing, and organizing data in warehouses and databases.
If you’re already using AWS-powered cloud services, opting for Glue has numerous advantages compared to custom-built ETL tools. As for the migration process, AWS did a great job making it easy to start with Glue, regardless of what ETL service you were using before. As a whole, Glue makes it an excellent choice for jobs of all sizes, from small instances to large-scale data processing workloads. If you’re considering a migration of your data processing jobs to AWS Glue, here are some tips to make the most of it:
- Upon migration, make use of Glue’s automatic code generation capabilities to quickly get started with data processing in AWS;
- Check out Glue’s security functionality, including but not limited to data encryption, network isolation, and user authentication;
- Take advantage of built-in connectors to streamline the integration of the needed data sources and targets, such as Amazon’s S3, RDS, Redshift, and more;
- Consider using Glue’s scalability features to handle large data processing workloads, automating the operations depending on the requested workload.
AWS Glue infrastructure
To better understand how Glue operates, it’s necessary to review this service’s AWS ETL architecture. In short, Glue consists of:
- Data catalog, which serves as the central metadata repository;
- ETL Engine that can generate Python or Scala code;
- Flexible scheduler, which handles a variety of tasks, including job monitoring, retries, and dependency management;
- DataBrew is used to clean and normalize the source data with a smooth and usable visual interface.
These four components form the backbone of Glue’s functionality, allowing you to allocate more time for data analysis by automating data discovery, categorization, enrichment, and movement.
Benefits of migrating to AWS ETL tools
AWS ETL tools, including Glue, offer a range of benefits crucial for making informed business decisions in less time. Let’s review the principal advantages of migrating to AWS ETL services.
- Streamlined data integration. Since Glue has embedded cooperation functionality, various group members can work on data integration simultaneously. This service encompasses extraction, cleaning, normalization, combination, loading, and running ETL workloads. This AWS ETL service frees data analysts from manually creating and maintaining data pipelines, simplifying integration.
- Automation and scaling. For most ETL workloads and data integration, scaling poses a crucial challenge. In this sense, AWS Glue automates much of that effort by crawling data sources, identifying particular data formats, and suggesting frameworks for working with data. Additionally, this service can automatically generate the code to run data transformations and loading procedures. Because of such a diverse functionality, Glue enables simultaneous work across multiple data sources using SQL.
- Serverless environment. In contrast to other alternatives and custom on-premise solutions, AWS Glue ETL operates in a serverless environment. This benefit eliminates the need for infrastructure management. Because this service governs and configures resources on the cloud, you pay only for the resources you’ve been using. Serverless architectures are well-suited for ETL-specific workloads since they can be scaled up and down to match the changing data volume demands.
- Handling complex workloads. Another crucial feature of AWS ETL services is their capacity to handle complex workloads depending on specific instances and use cases involved. AWS Glue’s data processing capabilities allow parallelizing and distributing workload instances. Also, using AWS Glue ETL proves efficiency without complicated server provisioning and an excessive load of unused resources.
- Resource-efficiency. Business-wise, the decision to migrate to a serverless ETL service is best regarding the pricing. When compared to open-source solutions, including Spark, the adoption of Glue is more accessible, more automated, and cheaper. Regarding resource allocation, AWS Glue provides a unified framework for accurate work with data, allowing it to reach effectiveness within the data analytics department.
- Flexible customization. One of the largest merits of Glue is exceptional flexibility when it comes to customization. The service’s functionality includes building event-triggered pipelines, creating unified data catalogs, and evaluating structured and semi-structured data quality.
How reliable technology partnership helps businesses with AWS Glue adoption
A reliable technology partner can help businesses with Glue adoption variously. The help starts with assessment and planning, providing expertise and guidance on using AWS Glue for your particular workloads. A reliable partner can also assist during the implementation phase, helping you to get the most out of Glue and ensuring that it integrates seamlessly with your existing infrastructure.
Finally, a trusted vendor will provide ongoing support and maintenance, ensuring that your deployment remains stable and reliable. Consider reading the following case studies of the N-iX team for more information on how technology partnerships assist businesses with Glue adoption.
AWS ETL migration in action: Success story of cleverbridge
Germany-based e-commerce and subscription management solutions company cleverbridge needed the expansion of their service offering with effective data analytics reporting. The N-iX team had to design an effective data migration strategy for this task. The client needed to move its vast bulks of data from the on-premise Oracle database. Our approach was to conduct a thorough Product Discovery beforehand to ensure that the data migration and storage approach was efficient.
Regarding the technical specifications, the N-iX team used AWS Glue to design 40+ ETL workloads, which saved weeks of work. These instances were used to migrate data from the on-premise Oracle database to AWS S3. What’s more, AWS Glue’s functionality was used to process S3-transformed data on the client side. As for the databases and tables, they were stored in AWS Glue Catalog and were generated by the Glue Crawler.
Using AWS Glue, N-iX has helped cleverbridge to expand its service with a new reporting solution guaranteed by the established data governance system.
AWS Glue data delivery: Fluke case study
Fluke is a global leader in manufacturing and distributing service electronic test tools and software for measuring and condition monitoring. The client needed the design, development, and deployment of web-based systems using microservices architecture using AWS services as a backbone for the operations mentioned above. The project’s challenge was transforming Fluke products into multi-tenant applications by making them cloud-native.
As part of using AWS services as the backbone for migrating from the on-premise to SaaS, the N-iX team used AWS Glue. In particular, the team used the DynamoDB export feature to transfer table data to Amazon S3 across AWS accounts and regions. Once the data was uploaded, the N-iX team approached several Glue workflows to read and write the exported data to the target tables. This helped us save time and deliver the solution faster.
Using AWS Glue functionality, the N-iX team has helped the client to make Fluke products cloud-oriented, which was part of the project’s strategic objectives.
Why choose N-iX for ETL services migration?
- N-iX is an AWS ETL Migration Program Partner that has demonstrated excellence in AWS Glue implementations;
- The company has vast experience in delivering both AWS Glue and open-source Spark migration solutions;
- N-iX has a talent pool of 2,000+ specialists, with 200+ data experts ready to tackle any challenges in AWS Glue migration;
- The company’s data engineering portfolio includes projects for global businesses, including Discovery Limited, cleverbridge, Fluke, and Gogo;
- N-iX complies with the regulations and industry standards, including GDPR, PCI/DSS, ISO27001, ISO9001, and ISO 27001:2013.