AWS Big Data Blog

Category: Analytics

Introducing Apache Hudi support with AWS Glue crawlers

Apache Hudi is an open table format that brings database and data warehouse capabilities to data lakes. Apache Hudi helps data engineers manage complex challenges, such as managing continuously evolving datasets with transactions while maintaining query performance. Data engineers use Apache Hudi for streaming workloads as well as to create efficient incremental data pipelines. Hudi provides tables, transactions, efficient […]

Introducing persistent buffering for Amazon OpenSearch Ingestion

Amazon OpenSearch Ingestion is a fully managed, serverless pipeline that delivers real-time log, metric, and trace data to Amazon OpenSearch Service domains and OpenSearch Serverless collections. Customers use Amazon OpenSearch Ingestion pipelines to ingest data from a variety of data sources, both pull-based and push-based. When ingesting data from pull-based sources, such as Amazon Simple […]

Build scalable and serverless RAG workflows with a vector engine for Amazon OpenSearch Serverless and Amazon Bedrock Claude models

In pursuit of a more efficient and customer-centric support system, organizations are deploying cutting-edge generative AI applications. These applications are designed to excel in four critical areas: multi-lingual support, sentiment analysis, personally identifiable information (PII) detection, and conversational search capabilities. Customers worldwide can now engage with the applications in their preferred language, and the applications […]

Enhance monitoring and debugging for AWS Glue jobs using new job observability metrics

For any modern data-driven company, having smooth data integration pipelines is crucial. These pipelines pull data from various sources, transform it, and load it into destination systems for analytics and reporting. When running properly, it provides timely and trustworthy information. However, without vigilance, the varying data volumes, characteristics, and application behavior can cause data pipelines […]

Introducing AWS Glue serverless Spark UI for better monitoring and troubleshooting

Today, we are pleased to announce serverless Spark UI built into the AWS Glue console. You can now use Spark UI easily as it’s a built-in component of the AWS Glue console, enabling you to access it with a single click when examining the details of any given job run. There’s no infrastructure setup or teardown required. AWS Glue serverless Spark UI is a fully-managed serverless offering and generally starts up in a matter of seconds. Serverless Spark UI makes it significantly faster and easier to get jobs working in production because you have ready access to low level details for your job runs.

Use custom domain names with Amazon Redshift

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. With Amazon Redshift, you can analyze all your data to derive holistic insights about your business and your customers. Amazon Redshift now supports custom URLs or custom domain names for your data warehouse. You might want to use a custom domain name […]

Speed up queries with the cost-based optimizer in Amazon Athena

Amazon Athena is a serverless, interactive analytics service built on open source frameworks, supporting open table file formats. Athena provides a simplified, flexible way to analyze petabytes of data where it lives. You can analyze data or build applications from an Amazon Simple Storage Service (Amazon S3) data lake and 30 data sources, including on-premises […]

Architecture Diagram

Visualize Amazon DynamoDB insights in Amazon QuickSight using the Amazon Athena DynamoDB connector and AWS Glue

Amazon DynamoDB is a fully managed, serverless, key-value NoSQL database designed to run high-performance applications at any scale. DynamoDB offers built-in security, continuous backups, automated multi-Region replication, in-memory caching, and data import and export tools. The scalability and flexible data schema of DynamoDB make it well-suited for a variety of use cases. These include internet-scale […]

Implement data warehousing solution using dbt on Amazon Redshift

Amazon Redshift is a cloud data warehousing service that provides high-performance analytical processing based on a massively parallel processing (MPP) architecture. Building and maintaining data pipelines is a common challenge for all enterprises. Managing the SQL files, integrating cross-team work, incorporating all software engineering principles, and importing external utilities can be a time-consuming task that […]

Power enterprise-grade Data Vaults with Amazon Redshift – Part 1

Amazon Redshift is a popular cloud data warehouse, offering a fully managed cloud-based service that seamlessly integrates with an organization’s Amazon Simple Storage Service (Amazon S3) data lake, real-time streams, machine learning (ML) workflows, transactional workflows, and much more—all while providing up to 7.9x better price-performance than other cloud data warehouses. As with all AWS […]