AWS Big Data Blog

Category: Advanced (300)

Process price transparency data using AWS Glue

The Transparency in Coverage rule is a federal regulation in the United States that was finalized by the Center for Medicare and Medicaid Services (CMS) in October 2020. The rule requires health insurers to provide clear and concise information to consumers about their health plan benefits, including costs and coverage details. Under the rule, health […]

Amazon OpenSearch Service now supports 99.99% availability using Multi-AZ with Standby

Customers use Amazon OpenSearch Service for mission-critical applications and monitoring. But what happens when OpenSearch Service itself is unavailable? If your ecommerce search is down, for example, you’re losing revenue. If you’re monitoring your application with OpenSearch Service, and it becomes unavailable, your ability to detect, diagnose, and repair issues with your application is diminished. […]

How SOCAR handles large IoT data with Amazon MSK and Amazon ElastiCache for Redis

This is a guest blog post co-written with SangSu Park and JaeHong Ahn from SOCAR.  As companies continue to expand their digital footprint, the importance of real-time data processing and analysis cannot be overstated. The ability to quickly measure and draw insights from data is critical in today’s business landscape, where rapid decision-making is key. […]

Connect Kafka client applications securely to your Amazon MSK cluster from different VPCs and AWS accounts

You can now use Amazon Managed Streaming for Apache Kafka (Amazon MSK) multi-VPC private connectivity (powered by AWS PrivateLink) and cluster policy support for MSK clusters to simplify connectivity of your Kafka clients to your brokers. Amazon MSK is a fully managed service that makes it easy for you to build and run applications that […]

Use the Amazon Redshift Data API to interact with Amazon Redshift Serverless

Amazon Redshift is a fast, scalable, secure, and fully managed cloud data warehouse that makes it simple and cost-effective to analyze all your data using standard SQL and your existing ETL (extract, transform, and load), business intelligence (BI), and reporting tools. Tens of thousands of customers use Amazon Redshift to process exabytes of data per […]

Top strategies for high volume tracing with Amazon OpenSearch Ingestion

Amazon OpenSearch Ingestion is a serverless, auto-scaled, managed data collector that receives, transforms, and delivers data to Amazon OpenSearch Service domains or Amazon OpenSearch Serverless collections. OpenSearch Ingestion is powered by Data Prepper, an open-source, streaming ETL (extract, transform, and load) solution that’s part of the OpenSearch project. When you use OpenSearch Ingestion, you don’t […]

Perform upserts in a data lake using Amazon Athena and Apache Iceberg

Amazon Athena supports the MERGE command on Apache Iceberg tables, which allows you to perform inserts, updates, and deletes in your data lake at scale using familiar SQL statements that are compliant with ACID (Atomic, Consistent, Isolated, Durable). Apache Iceberg is an open table format for data lakes that manages large collections of files as […]

Working with percolators in Amazon OpenSearch Service

Amazon OpenSearch Service is a managed service that makes it easy to secure, deploy, and operate OpenSearch and legacy Elasticsearch clusters at scale in the AWS Cloud. Amazon OpenSearch Service provisions all the resources for your cluster, launches it, and automatically detects and replaces failed nodes, reducing the overhead of self-managed infrastructures. The service makes it […]

Build a transactional data lake using Apache Iceberg, AWS Glue, and cross-account data shares using AWS Lake Formation and Amazon Athena

Building a data lake on Amazon Simple Storage Service (Amazon S3) provides numerous benefits for an organization. It allows you to access diverse data sources, build business intelligence dashboards, build AI and machine learning (ML) models to provide customized customer experiences, and accelerate the curation of new datasets for consumption by adopting a modern data […]

Simplify and speed up Apache Spark applications on Amazon Redshift data with Amazon Redshift integration for Apache Spark

Customers use Amazon Redshift to run their business-critical analytics on petabytes of structured and semi-structured data. Apache Spark is a popular framework that you can use to build applications for use cases such as ETL (extract, transform, and load), interactive analytics, and machine learning (ML). Apache Spark enables you to build applications in a variety […]