Significantly improve the performance and reduce the cost of data lake-based analytics applications using Amazon ElastiCache for Redis — Introduction The recent post, Developing Spring Boot Applications for Querying Data Lakes on AWS using Amazon Athena, demonstrated how to develop a Cloud-native analytics application using Spring Boot. The application queried data in an Amazon S3-based data lake via an AWS Glue Data Catalog utilizing the Amazon Athena API.

Learn how to develop Cloud-native, RESTful Java services that query data in an AWS-based data lake using Amazon Athena’s API — Introduction AWS provides a collection of fully-managed services that makes building and managing secure data lakes faster and easier, including AWS Lake Formation, AWS Glue, and Amazon S3. …

Developing, testing, building, and deploying Native Quarkus-based Java microservices to Kubernetes on AWS, using GitOps — Introduction Although it may no longer be the undisputed programming language leader, according to many developer surveys, Java still ranks right up there with Go, Python, C/C++, and JavaScript. Given Java’s continued popularity, especially amongst enterprises, and the simultaneous rise of cloud-native software development, vendors have focused on creating purpose-built, modern…

Exploring common patterns for refactoring relational database models as part of a microservices architecture — Introduction There is no shortage of books, articles, tutorials, and presentations on migrating existing monolithic applications to microservices, nor designing new applications using a microservices architecture. It has been one of the most popular IT topics for the last several years. Unfortunately, monolithic architectures often have equally monolithic database models. As…

Use DataHub’s data catalog capabilities to collect, organize, enrich, and search for metadata across multiple platforms — Introduction According to Shirshanka Das, Founder of LinkedIn DataHub, Apache Gobblin, and Acryl Data, one of the simplest definitions for a data catalog can be found on the Oracle website: “Simply put, a data catalog is an organized inventory of data assets in the organization. It uses metadata to help organizations…

Comparing the features and performance of different AWS analytics services for Extract, Load, Transform (ELT) — According to Wikipedia, “Extract, load, transform (ELT) is an alternative to extract, transform, load (ETL) used with data lake implementations. In contrast to ETL, in ELT models the data is not transformed on entry to the data lake but stored in its original raw format. This enables faster loading times…

Measuring the current levels of interest and potential adoption rates of leading data lake table formats using commonly available metrics — This post examines the current levels of interest and potential adoption rates for the three popular data lake table formats: Apache Hudi™, Apache Iceberg™, and Delta Lake™. Using publicly available data, this post unbiasedly reviews analytics community involvement, project activity, commercial support, and…

What to consider when evaluating a ‘multi-region’ strategy as part of business continuity and disaster recovery planning — Introduction Increasingly, I hear the term ‘multi-region’ used within the IT community and in conversations with peers and customers, most often within the context of disaster recovery. In my experience, ‘multi-region’ is a cloud provider-agnostic phrase that can mean different things to different…

Implement an effective and repeatable strategy for documenting data analytics workflows and capturing system requirements — “Data analytics applications involve more than just analyzing data, particularly on advanced analytics projects. Much of the required work takes place upfront, in collecting, integrating, and preparing data and then developing, testing, and revising analytical models to ensure that they produce accurate results. In addition to data scientists and other…