<?xml version="1.0" encoding="UTF-8"?><rss version="2.0"
	xmlns:content="http://purl.org/rss/1.0/modules/content/"
	xmlns:wfw="http://wellformedweb.org/CommentAPI/"
	xmlns:dc="http://purl.org/dc/elements/1.1/"
	xmlns:atom="http://www.w3.org/2005/Atom"
	xmlns:sy="http://purl.org/rss/1.0/modules/syndication/"
	xmlns:slash="http://purl.org/rss/1.0/modules/slash/"
	>

<channel>
	<title>Amazon Athena &#8211; Noise</title>
	<atom:link href="https://noise.getoto.net/tag/amazon-athena/feed/" rel="self" type="application/rss+xml" />
	<link>https://noise.getoto.net</link>
	<description>The collective thoughts of the interwebz</description>
	<lastBuildDate>Tue, 13 Oct 2026 15:59:06 +0000</lastBuildDate>
	<language>en-US</language>
	<sy:updatePeriod>
	hourly	</sy:updatePeriod>
	<sy:updateFrequency>
	1	</sy:updateFrequency>
	<generator>https://wordpress.org/?v=7.1.3</generator>
	<item>
		<title>AWS Weekly Roundup: Prime Day 2026 by the numbers, Claude Haiku 5.5, Amazon Nova 2.5 Sonic, and more (October 13, 2026)</title>
		<link>https://noise.getoto.net/2026/10/13/aws-weekly-roundup-prime-day-2026-by-the-numbers-claude-haiku-5-5-amazon-nova-2-5-sonic-and-more-october-13-2026/</link>
		
		<dc:creator><![CDATA[Daniel Abib]]></dc:creator>
		<pubDate>Tue, 13 Oct 2026 15:59:06 +0000</pubDate>
				<category><![CDATA[Amazon Athena]]></category>
		<category><![CDATA[Amazon Aurora]]></category>
		<category><![CDATA[Amazon Bedrock]]></category>
		<category><![CDATA[Amazon GuardDuty]]></category>
		<category><![CDATA[Amazon Nova]]></category>
		<category><![CDATA[Amazon RDS]]></category>
		<category><![CDATA[Amazon Redshift]]></category>
		<category><![CDATA[Amazon Simple Storage Service (S3)]]></category>
		<category><![CDATA[announcements]]></category>
		<category><![CDATA[AWS Fault Injection Service (FIS)]]></category>
		<category><![CDATA[AWS Glue]]></category>
		<category><![CDATA[AWS Lambda]]></category>
		<category><![CDATA[AWS re:Invent]]></category>
		<category><![CDATA[news]]></category>
		<category><![CDATA[Strands Agents]]></category>
		<category><![CDATA[Week in Review]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=c9f437ea5503d740524c6fbaf5c0df84</guid>

					<description><![CDATA[Some numbers are hard to picture until you sit with them for a moment. Last week we published the Prime Day 2026 metrics, and the one that stuck with me is 2.3 quadrillion: the daily requests Amazon ElastiCache peaked at during the event. Prime Day ran back in June, so this post always lands as […]]]></description>
		
		
		
			</item>
		<item>
		<title>How Moeve standardized dbt runs across data lakes with Amazon Athena</title>
		<link>https://noise.getoto.net/2026/09/22/how-moeve-standardized-dbt-runs-across-data-lakes-with-amazon-athena/</link>
		
		<dc:creator><![CDATA[Rubén Romero Córdoba]]></dc:creator>
		<pubDate>Tue, 22 Sep 2026 15:13:31 +0000</pubDate>
				<category><![CDATA[Amazon Athena]]></category>
		<category><![CDATA[Customer Solutions]]></category>
		<category><![CDATA[Intermediate (200)]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=3b4756642752c4f45f798f12b4956cfb</guid>

					<description><![CDATA[Moeve standardized how it runs dbt across multiple data lakes by building a centralized, serverless launcher on Amazon Athena, AWS Step Functions, AWS Fargate, Amazon DynamoDB, and Amazon EventBridge, cutting new-project onboarding from days to about 15 minutes while keeping compute close to the data and orchestration loosely coupled.]]></description>
		
		
		
			</item>
		<item>
		<title>How CSIRO built scalable, cost-optimized genomic variant querying on AWS</title>
		<link>https://noise.getoto.net/2026/09/18/how-csiro-built-scalable-cost-optimized-genomic-variant-querying-on-aws/</link>
		
		<dc:creator><![CDATA[Prof. Denis Bauer]]></dc:creator>
		<pubDate>Fri, 18 Sep 2026 14:35:42 +0000</pubDate>
				<category><![CDATA[Amazon Athena]]></category>
		<category><![CDATA[Amazon DynamoDB]]></category>
		<category><![CDATA[Amazon Simple Storage Service (S3)]]></category>
		<category><![CDATA[AWS Lambda]]></category>
		<category><![CDATA[Customer Solutions]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=90b64eae5ac5e793a11e8d2281724a8c</guid>

					<description><![CDATA[Learn how researchers at CSIRO, Australia's national science agency, built Serverless Beacon (sBeacon), a scalable serverless solution for securely querying genomic variant data on AWS. sBeacon implements the GA4GH Beacon standard using Amazon S3, AWS Lambda, Amazon DynamoDB, and Amazon Athena to support production-scale clinical and research applications.]]></description>
		
		
		
			</item>
		<item>
		<title>Connect Amazon SageMaker Unified Studio to Microsoft Power BI – Part 1: IAM Identity Center (IDC)-based domains</title>
		<link>https://noise.getoto.net/2026/09/15/connect-amazon-sagemaker-unified-studio-to-microsoft-power-bi-part-1-iam-identity-center-idc-based-domains/</link>
		
		<dc:creator><![CDATA[Ramesh H Singh]]></dc:creator>
		<pubDate>Tue, 15 Sep 2026 20:55:26 +0000</pubDate>
				<category><![CDATA[Amazon Athena]]></category>
		<category><![CDATA[Amazon SageMaker Unified Studio]]></category>
		<category><![CDATA[announcements]]></category>
		<category><![CDATA[Intermediate (200)]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=6448c45ceaedb0126897b35d1b723a14</guid>

					<description><![CDATA[Connect Microsoft Power BI directly to governed data in Amazon SageMaker Unified Studio using new authentication modes in the Amazon Athena ODBC driver, with no third-party ODBC-JDBC bridge. Part 1 covers IAM Identity Center (IDC)-based domains with both DSN-based and DSN-less connection methods.]]></description>
		
		
		<enclosure url="" length="0" type="" />

			</item>
		<item>
		<title>Connect Amazon SageMaker Unified Studio to Microsoft Power BI – Part 2: IAM-based domains</title>
		<link>https://noise.getoto.net/2026/09/15/connect-amazon-sagemaker-unified-studio-to-microsoft-power-bi-part-2-iam-based-domains/</link>
		
		<dc:creator><![CDATA[Ramesh H Singh]]></dc:creator>
		<pubDate>Tue, 15 Sep 2026 20:55:16 +0000</pubDate>
				<category><![CDATA[Amazon Athena]]></category>
		<category><![CDATA[Amazon SageMaker Unified Studio]]></category>
		<category><![CDATA[announcements]]></category>
		<category><![CDATA[Intermediate (200)]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=3d3ab5545ffbc1554d7fad9b28be3709</guid>

					<description><![CDATA[Connect Microsoft Power BI directly to governed data in Amazon SageMaker Unified Studio using the Amazon Athena ODBC driver. Part 2 covers IAM-based domains with SageMakerIam authentication, including AWS IAM Identity Center administrator setup, for both DSN-based and DSN-less connection methods.]]></description>
		
		
		<enclosure url="" length="0" type="" />

			</item>
		<item>
		<title>Route Amazon Bedrock Guardrails interventions to Amazon Security Lake</title>
		<link>https://noise.getoto.net/2026/08/06/route-amazon-bedrock-guardrails-interventions-to-amazon-security-lake/</link>
		
		<dc:creator><![CDATA[Dhananjay Karanjkar]]></dc:creator>
		<pubDate>Thu, 06 Aug 2026 19:00:15 +0000</pubDate>
				<category><![CDATA[Advanced (300)]]></category>
		<category><![CDATA[Amazon Athena]]></category>
		<category><![CDATA[Amazon Bedrock]]></category>
		<category><![CDATA[Amazon Bedrock Guardrails]]></category>
		<category><![CDATA[Amazon Security Lake]]></category>
		<category><![CDATA[AWS CDK]]></category>
		<category><![CDATA[AWS Lambda]]></category>
		<category><![CDATA[OCSF]]></category>
		<category><![CDATA[Security Blog]]></category>
		<category><![CDATA[Security, Identity & Compliance]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=21022c9eb3eae313ee19216a0e11f802</guid>

					<description><![CDATA[Security teams investigating AI-related incidents need guardrail intervention data alongside their existing security telemetry. Routing Amazon Bedrock Guardrails violations to Amazon Security Lake makes this possible. With this integration, you can query guardrail events alongside identity, network, and application security data in a single layer. When a guardrail blocks a prompt injection attempt or redacts […]]]></description>
		
		
		<enclosure url="" length="0" type="" />

			</item>
		<item>
		<title>Automate creating AWS Glue Data Catalog views with AWS SDK for data mesh use case</title>
		<link>https://noise.getoto.net/2026/07/24/automate-creating-aws-glue-data-catalog-views-with-aws-sdk-for-data-mesh-use-case/</link>
		
		<dc:creator><![CDATA[Aarthi Srinivasan]]></dc:creator>
		<pubDate>Fri, 24 Jul 2026 16:05:07 +0000</pubDate>
				<category><![CDATA[Advanced (300)]]></category>
		<category><![CDATA[Amazon Athena]]></category>
		<category><![CDATA[Amazon Simple Storage Service (S3)]]></category>
		<category><![CDATA[AWS Glue]]></category>
		<category><![CDATA[AWS Lake Formation]]></category>
		<category><![CDATA[Technical How-to]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=f7c113f5ba6baed8c648bd6999f37886</guid>

					<description><![CDATA[This post shows you how to use the Catalog objects API CreateTable() to programmatically create ATHENA and SPARK dialects using cross-account IAM definer roles, and how to add the ATHENA dialect programmatically for the views that were created earlier with only SPARK dialect.]]></description>
		
		
		<enclosure url="" length="0" type="" />

			</item>
		<item>
		<title>Zero Copy access to Apache Iceberg tables in Amazon S3 from Salesforce Data 360 using the Iceberg REST endpoint from AWS Glue Data Catalog</title>
		<link>https://noise.getoto.net/2026/07/15/zero-copy-access-to-apache-iceberg-tables-in-amazon-s3-from-salesforce-data-360-using-the-iceberg-rest-endpoint-from-aws-glue-data-catalog/</link>
		
		<dc:creator><![CDATA[Avijit Goswami]]></dc:creator>
		<pubDate>Wed, 15 Jul 2026 15:51:33 +0000</pubDate>
				<category><![CDATA[Amazon Athena]]></category>
		<category><![CDATA[Amazon Simple Storage Service (S3)]]></category>
		<category><![CDATA[announcements]]></category>
		<category><![CDATA[AWS Identity and Access Management (IAM)]]></category>
		<category><![CDATA[AWS Lake Formation]]></category>
		<category><![CDATA[Expert (400)]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=40c5540aeabdafb00fd6ad79eb4fc94b</guid>

					<description><![CDATA[In this post, we demonstrate how AWS and Salesforce customers can access their enterprise data lakes on AWS from Salesforce Data 360 using zero-copy file federation.]]></description>
		
		
		<enclosure url="" length="0" type="" />

			</item>
		<item>
		<title>Multi-cloud lakehouse architecture on AWS for Agentic AI, Part 1: Architecture and best practices</title>
		<link>https://noise.getoto.net/2026/07/13/multi-cloud-lakehouse-architecture-on-aws-for-agentic-ai-part-1-architecture-and-best-practices/</link>
		
		<dc:creator><![CDATA[Sakti Mishra]]></dc:creator>
		<pubDate>Mon, 13 Jul 2026 17:02:40 +0000</pubDate>
				<category><![CDATA[Advanced (300)]]></category>
		<category><![CDATA[Amazon Athena]]></category>
		<category><![CDATA[Amazon Bedrock]]></category>
		<category><![CDATA[Amazon Bedrock AgentCore]]></category>
		<category><![CDATA[Amazon EMR]]></category>
		<category><![CDATA[Amazon Sagemaker]]></category>
		<category><![CDATA[Amazon SageMaker Lakehouse]]></category>
		<category><![CDATA[AWS Glue]]></category>
		<category><![CDATA[Customer Solutions]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=a03b3dc738f79d55acf66a71db609d95</guid>

					<description><![CDATA[This post focuses on explaining the architecture approach to build the open lakehouse architecture on AWS, unifying the metadata catalog across providers for the AI agents to access. In addition, it highlights the architecture trade-offs and best practices.]]></description>
		
		
		<enclosure url="" length="0" type="" />

			</item>
		<item>
		<title>How BigBasket uses the Iceberg based lakehouse architecture on AWS to power lightning-fast grocery delivery across India</title>
		<link>https://noise.getoto.net/2026/07/06/how-bigbasket-uses-the-iceberg-based-lakehouse-architecture-on-aws-to-power-lightning-fast-grocery-delivery-across-india/</link>
		
		<dc:creator><![CDATA[Annie Mattoo]]></dc:creator>
		<pubDate>Mon, 06 Jul 2026 16:50:17 +0000</pubDate>
				<category><![CDATA[Amazon Athena]]></category>
		<category><![CDATA[Amazon CloudWatch]]></category>
		<category><![CDATA[Amazon EMR]]></category>
		<category><![CDATA[Amazon Quick Sight]]></category>
		<category><![CDATA[Amazon Redshift]]></category>
		<category><![CDATA[Amazon Simple Storage Service (S3)]]></category>
		<category><![CDATA[AWS Glue]]></category>
		<category><![CDATA[AWS Lake Formation]]></category>
		<category><![CDATA[Customer Solutions]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=a58db9aae671ef573b0e4a36a50351a0</guid>

					<description><![CDATA[In this post, we demonstrate how BigBasket implemented the lakehouse architecture on AWS, including their architecture decisions, implementation approach, and the measurable business results you can expect from a similar modernization. Whether you’re facing scalability challenges or planning your own lakehouse implementation, this blueprint provides actionable insights you can adapt for your organization.]]></description>
		
		
		<enclosure url="" length="0" type="" />

			</item>
		<item>
		<title>Serverless analytics pipelines using the Apache Spark engine in Amazon Athena</title>
		<link>https://noise.getoto.net/2026/07/02/serverless-analytics-pipelines-using-the-apache-spark-engine-in-amazon-athena/</link>
		
		<dc:creator><![CDATA[Avichay Marciano]]></dc:creator>
		<pubDate>Thu, 02 Jul 2026 16:27:58 +0000</pubDate>
				<category><![CDATA[Advanced (300)]]></category>
		<category><![CDATA[Amazon Athena]]></category>
		<category><![CDATA[Technical How-to]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=62749fa9446cae87f4a2f941d8d3e12f</guid>

					<description><![CDATA[This post shows how developers, data engineers, and analysts can connect to a secure Spark Connect endpoint in Athena with Apache Spark. You can use your preferred tools, such as Jupyter notebooks, VS Code, or dbt with Apache Airflow, without managing cluster lifecycle or scaling.]]></description>
		
		
		<enclosure url="" length="0" type="" />

			</item>
		<item>
		<title>Deploy modern data platforms in minutes with MDAA</title>
		<link>https://noise.getoto.net/2026/07/02/deploy-modern-data-platforms-in-minutes-with-mdaa/</link>
		
		<dc:creator><![CDATA[Sudeshna Dash]]></dc:creator>
		<pubDate>Thu, 02 Jul 2026 16:26:28 +0000</pubDate>
				<category><![CDATA[Amazon Athena]]></category>
		<category><![CDATA[Amazon Bedrock]]></category>
		<category><![CDATA[Amazon CloudWatch]]></category>
		<category><![CDATA[Amazon EMR]]></category>
		<category><![CDATA[Amazon Kinesis]]></category>
		<category><![CDATA[Amazon Managed Streaming for Apache Kafka (Amazon MSK)]]></category>
		<category><![CDATA[Amazon Redshift]]></category>
		<category><![CDATA[Amazon SageMaker Lakehouse]]></category>
		<category><![CDATA[Amazon Simple Storage Service (S3)]]></category>
		<category><![CDATA[AWS CloudTrail]]></category>
		<category><![CDATA[AWS Glue]]></category>
		<category><![CDATA[AWS Key Management Service*]]></category>
		<category><![CDATA[AWS Lake Formation]]></category>
		<category><![CDATA[AWS Lambda]]></category>
		<category><![CDATA[Customer Solutions]]></category>
		<category><![CDATA[Intermediate (200)]]></category>
		<category><![CDATA[Partner solutions]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=26439facede8e2110aaf3efa4f30e0ab</guid>

					<description><![CDATA[In this post, we explore how MDAA transforms data architecture development from months of manual coding to production-ready deployment through configuration-driven infrastructure and embedded governance, examine a real customer transformation, and provide a clear implementation pathway for your own data modernization journey.]]></description>
		
		
		<enclosure url="" length="0" type="" />

			</item>
		<item>
		<title>A systematic approach to benchmarking SQL processing engines on AWS</title>
		<link>https://noise.getoto.net/2026/05/19/a-systematic-approach-to-benchmarking-sql-processing-engines-on-aws/</link>
		
		<dc:creator><![CDATA[Anubhav Awasthi]]></dc:creator>
		<pubDate>Tue, 19 May 2026 15:44:02 +0000</pubDate>
				<category><![CDATA[Advanced (300)]]></category>
		<category><![CDATA[Amazon Athena]]></category>
		<category><![CDATA[Amazon EMR]]></category>
		<category><![CDATA[Amazon Redshift]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[Technical How-to]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=28d57789025fbfeb544f7b8f8754ff23</guid>

					<description><![CDATA[Selecting the right SQL processing solution for large-scale data analytics is a critical decision for organizations. As data volumes grow exponentially, the technology landscape has evolved to offer diverse options for processing and analyzing this information efficiently. This post presents a systematic framework for evaluating and benchmarking SQL processing engines on AWS, using Apache JMeter to conduct practical performance testing at scale.]]></description>
		
		
		<enclosure url="" length="0" type="" />

			</item>
		<item>
		<title>How to use streamlined permissions for Amazon S3 Tables and Iceberg materialized views</title>
		<link>https://noise.getoto.net/2026/05/11/how-to-use-streamlined-permissions-for-amazon-s3-tables-and-iceberg-materialized-views/</link>
		
		<dc:creator><![CDATA[Srividya Parthasarathy]]></dc:creator>
		<pubDate>Mon, 11 May 2026 18:59:36 +0000</pubDate>
				<category><![CDATA[Amazon Athena]]></category>
		<category><![CDATA[Amazon EMR]]></category>
		<category><![CDATA[Amazon Redshift]]></category>
		<category><![CDATA[Amazon S3 Tables]]></category>
		<category><![CDATA[Amazon Simple Storage Service (S3)]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[AWS Big Data]]></category>
		<category><![CDATA[AWS Glue]]></category>
		<category><![CDATA[Intermediate (200)]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=c2217b5d123fedead78d8637ecae0466</guid>

					<description><![CDATA[In this post, we walk through how to set up and manage S3 Tables in the AWS Glue Data Catalog, create and query Iceberg materialized views, and configure access controls that work across your analytics stack with IAM-based authorization.]]></description>
		
		
		<enclosure url="" length="0" type="" />

			</item>
		<item>
		<title>How to use Parquet Column Indexes with Amazon Athena</title>
		<link>https://noise.getoto.net/2026/04/13/how-to-use-parquet-column-indexes-with-amazon-athena/</link>
		
		<dc:creator><![CDATA[Matt Wong]]></dc:creator>
		<pubDate>Mon, 13 Apr 2026 15:57:18 +0000</pubDate>
				<category><![CDATA[Amazon Athena]]></category>
		<category><![CDATA[Amazon SageMaker Unified Studio]]></category>
		<category><![CDATA[Analytics]]></category>
		<category><![CDATA[Intermediate (200)]]></category>
		<category><![CDATA[Technical How-to]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=ea91f8880a7f81d74b667a63b097885f</guid>

					<description><![CDATA[In this blog post, we use Athena and Amazon SageMaker Unified Studio to explore Parquet Column Indexes and demonstrate how they can improve Iceberg query performance. We explain what Parquet Column Indexes are, demonstrate their performance benefits, and show you how to use them in your applications.]]></description>
		
		
		<enclosure url="" length="0" type="" />

			</item>
		<item>
		<title>Modernize business intelligence workloads using Amazon Quick</title>
		<link>https://noise.getoto.net/2026/04/06/modernize-business-intelligence-workloads-using-amazon-quick/</link>
		
		<dc:creator><![CDATA[Satesh Sonti]]></dc:creator>
		<pubDate>Mon, 06 Apr 2026 17:56:35 +0000</pubDate>
				<category><![CDATA[Amazon Athena]]></category>
		<category><![CDATA[Amazon Quick Suite]]></category>
		<category><![CDATA[Amazon Redshift]]></category>
		<category><![CDATA[Generative BI]]></category>
		<category><![CDATA[Intermediate (200)]]></category>
		<category><![CDATA[Technical How-to]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=ae6c1e76ef2a932df8088e5695584ab0</guid>

					<description><![CDATA[In this post, we provide implementation guidance for building integrated analytics solutions that combine the generative BI features of Amazon Quick with Amazon Redshift and Amazon Athena SQL analytics capabilities.]]></description>
		
		
		<enclosure url="" length="0" type="" />

			</item>
		<item>
		<title>Building a scalable, transactional data lake using dbt, Amazon EMR, and Apache Iceberg</title>
		<link>https://noise.getoto.net/2026/03/18/building-a-scalable-transactional-data-lake-using-dbt-amazon-emr-and-apache-iceberg/</link>
		
		<dc:creator><![CDATA[Umesh Pathak]]></dc:creator>
		<pubDate>Tue, 17 Mar 2026 22:38:26 +0000</pubDate>
				<category><![CDATA[Advanced (300)]]></category>
		<category><![CDATA[Amazon Athena]]></category>
		<category><![CDATA[Amazon EMR]]></category>
		<category><![CDATA[Data Lake]]></category>
		<category><![CDATA[dbt]]></category>
		<category><![CDATA[Technical How-to]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=aaf7244988264bfa748eebd163e696e1</guid>

					<description><![CDATA[Growing data volume, variety, and velocity has made it crucial for businesses to implement architectures that efficiently manage and analyze data, while maintaining data integrity and consistency. In this post, we show you a solution that combines Apache Iceberg, Data Build Tool (dbt), and Amazon EMR to create a scalable, ACID-compliant transactional data lake. You can use this data lake to process transactions and analyze data simultaneously while maintaining data accuracy and real-time insights for better decision-making.]]></description>
		
		
		<enclosure url="" length="0" type="" />

			</item>
		<item>
		<title>Amazon Athena adds 1-minute reservations and new capacity control features</title>
		<link>https://noise.getoto.net/2026/02/12/amazon-athena-adds-1-minute-reservations-and-new-capacity-control-features/</link>
		
		<dc:creator><![CDATA[Manan Nayar]]></dc:creator>
		<pubDate>Wed, 11 Feb 2026 22:16:01 +0000</pubDate>
				<category><![CDATA[Amazon Athena]]></category>
		<category><![CDATA[announcements]]></category>
		<category><![CDATA[Intermediate (200)]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=b5d49521a1d9b8b1fcffec3609a8c05f</guid>

					<description><![CDATA[Amazon Athena is a serverless interactive query service that makes it easy to analyze data using SQL. With Athena, there’s no infrastructure to manage, you simply submit queries and get results. Capacity Reservations is a feature of Athena that addresses the need to run critical workloads by providing dedicated serverless capacity for workloads you specify. In this post, we highlight three new capabilities that make Capacity Reservations more flexible and easier to manage: reduced minimums for fine-grained capacity adjustments, an autoscaling solution for dynamic workloads, and capacity cost and performance controls.]]></description>
		
		
		<enclosure url="" length="0" type="" />

			</item>
		<item>
		<title>Using Amazon EMR DeltaStreamer to stream data to multiple Apache Hudi tables</title>
		<link>https://noise.getoto.net/2026/01/15/using-amazon-emr-deltastreamer-to-stream-data-to-multiple-apache-hudi-tables/</link>
		
		<dc:creator><![CDATA[Gautam Bhaghavatula]]></dc:creator>
		<pubDate>Thu, 15 Jan 2026 21:48:25 +0000</pubDate>
				<category><![CDATA[Advanced (300)]]></category>
		<category><![CDATA[Amazon Athena]]></category>
		<category><![CDATA[Amazon EMR]]></category>
		<category><![CDATA[Amazon Managed Streaming for Apache Kafka (Amazon MSK)]]></category>
		<category><![CDATA[Technical How-to]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=456a155ae27fb56398af08f45b68f313</guid>

					<description><![CDATA[In this post, we show you how to implement real-time data ingestion from multiple Kafka topics to Apache Hudi tables using Amazon EMR. This solution streamlines data ingestion by processing multiple Amazon Managed Streaming for Apache Kafka (Amazon MSK) topics in parallel while providing data quality and scalability through change data capture (CDC) and Apache Hudi.]]></description>
		
		
		<enclosure url="" length="0" type="" />

			</item>
		<item>
		<title>Access Snowflake Horizon Catalog data using catalog federation in the AWS Glue Data Catalog</title>
		<link>https://noise.getoto.net/2026/01/14/access-snowflake-horizon-catalog-data-using-catalog-federation-in-the-aws-glue-data-catalog/</link>
		
		<dc:creator><![CDATA[Andries Engelbrecht]]></dc:creator>
		<pubDate>Wed, 14 Jan 2026 21:00:26 +0000</pubDate>
				<category><![CDATA[Advanced (300)]]></category>
		<category><![CDATA[Amazon Athena]]></category>
		<category><![CDATA[AWS Glue]]></category>
		<category><![CDATA[AWS Lake Formation]]></category>
		<category><![CDATA[Technical How-to]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=d357581cc028ed8dd4df9778443ce7e3</guid>

					<description><![CDATA[AWS has introduced a new catalog federation feature that enables direct access to Snowflake Horizon Catalog data through AWS Glue Data Catalog. This integration allows organizations to discover and query data in Iceberg format while maintaining security through AWS Lake Formation. This post provides a step-by-step guide to establishing this integration, including configuring Snowflake Horizon Catalog, setting up authentication, creating necessary IAM roles, and implementing AWS Lake Formation permissions. Learn how to enable cross-platform analytics while maintaining robust security and governance across your data environment.]]></description>
		
		
		<enclosure url="https://d2908q01vomqb2.cloudfront.net/artifacts/DBSBlogs/BDB-5498/BDB-5498-bloghorizondemo.mp4" length="28460597" type="video/mp4" />

			</item>
	</channel>
</rss>

<!--
Performance optimized by W3 Total Cache. Learn more: https://www.boldgrid.com/w3-total-cache/?utm_source=w3tc&utm_medium=footer_comment&utm_campaign=free_plugin

Object Caching 21/232 objects using Memcached
Page Caching using Disk: Enhanced 
Lazy Loading (feed)
Database Caching using Memcached

Served from: noise.getoto.net @ 2026-10-27 20:33:02 by W3 Total Cache
-->