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	<title>Amazon Redshift &#8211; Noise</title>
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		<title>dbt and Amazon Redshift Data Sharing: Multi-cluster pipelines without moving a byte</title>
		<link>https://noise.getoto.net/2026/10/15/dbt-and-amazon-redshift-data-sharing-multi-cluster-pipelines-without-moving-a-byte/</link>
		
		<dc:creator><![CDATA[Neela Kulkarni]]></dc:creator>
		<pubDate>Thu, 15 Oct 2026 18:01:07 +0000</pubDate>
				<category><![CDATA[Advanced (300)]]></category>
		<category><![CDATA[Amazon Redshift]]></category>
		<category><![CDATA[Technical How-to]]></category>
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					<description><![CDATA[Learn how to set up Amazon Redshift Data Sharing between a producer and consumer cluster and use dbt Cloud to transform the shared data into analytics-ready models, with live, zero-copy access and no ETL between clusters.]]></description>
		
		
		
			</item>
		<item>
		<title>Resolving concurrent write conflicts for Apache Iceberg tables in Amazon Redshift</title>
		<link>https://noise.getoto.net/2026/10/13/resolving-concurrent-write-conflicts-for-apache-iceberg-tables-in-amazon-redshift/</link>
		
		<dc:creator><![CDATA[Sanjay Devireddy]]></dc:creator>
		<pubDate>Tue, 13 Oct 2026 20:16:48 +0000</pubDate>
				<category><![CDATA[Amazon Redshift]]></category>
		<category><![CDATA[announcements]]></category>
		<category><![CDATA[Foundational (100)]]></category>
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					<description><![CDATA[Amazon Redshift now automatically resolves many concurrent writes to Apache Iceberg tables that don't actually overlap, committing changes that previously failed and had to retry. Learn why these writes conflict, how the engine rebases non-overlapping ones across operation, partition, and file checks, and the throughput gains it delivers.]]></description>
		
		
		
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		<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>
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					<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>
		
		
		
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		<item>
		<title>Materialize once, query anywhere: Introducing Iceberg materialized views in Amazon Redshift</title>
		<link>https://noise.getoto.net/2026/10/06/materialize-once-query-anywhere-introducing-iceberg-materialized-views-in-amazon-redshift/</link>
		
		<dc:creator><![CDATA[Sudipta Bagchi]]></dc:creator>
		<pubDate>Mon, 05 Oct 2026 21:41:49 +0000</pubDate>
				<category><![CDATA[Advanced (300)]]></category>
		<category><![CDATA[Amazon Redshift]]></category>
		<category><![CDATA[announcements]]></category>
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					<description><![CDATA[Amazon Redshift now supports Iceberg materialized views. Compute an aggregation once in Amazon Redshift and store the result as a standard Apache Iceberg table in Amazon S3, queryable by Amazon Athena, Apache Spark, Amazon SageMaker, and AWS Glue. This post covers use cases, incremental refresh, and a step-by-step getting-started guide.]]></description>
		
		
		
			</item>
		<item>
		<title>Run an automated operational review with the Amazon Redshift MCP server</title>
		<link>https://noise.getoto.net/2026/10/05/run-an-automated-operational-review-with-the-amazon-redshift-mcp-server/</link>
		
		<dc:creator><![CDATA[Sidhanth Muralidhar]]></dc:creator>
		<pubDate>Mon, 05 Oct 2026 15:44:45 +0000</pubDate>
				<category><![CDATA[Advanced (300)]]></category>
		<category><![CDATA[Amazon Redshift]]></category>
		<category><![CDATA[Technical How-to]]></category>
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					<description><![CDATA[Amazon Redshift automates much of its own tuning, but periodic operational reviews still pay off. Learn how the review_cluster tool in the open-source Amazon Redshift MCP server runs a full cluster diagnostic from one natural-language request, evaluating 12 diagnostic areas and returning prioritized, documentation-linked recommendations in minutes.]]></description>
		
		
		
			</item>
		<item>
		<title>Getting started with Apache Iceberg write support in Amazon Redshift – Part 3</title>
		<link>https://noise.getoto.net/2026/09/28/getting-started-with-apache-iceberg-write-support-in-amazon-redshift-part-3/</link>
		
		<dc:creator><![CDATA[Raghu Kuppala]]></dc:creator>
		<pubDate>Mon, 28 Sep 2026 15:48:35 +0000</pubDate>
				<category><![CDATA[Advanced (300)]]></category>
		<category><![CDATA[Amazon Redshift]]></category>
		<category><![CDATA[Technical How-to]]></category>
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					<description><![CDATA[Amazon Redshift now supports evolving Apache Iceberg table schemas and partition layouts through ALTER statements, with no data rewrites or pipeline rebuilds. In this final post of the series, you rename, add, drop, and widen columns, evolve partitions, and create AWS Lake Formation resource links for governed cross-engine access to Amazon S3 Tables.]]></description>
		
		
		
			</item>
		<item>
		<title>How United Airlines uses Amazon Redshift and AWS Glue Data Catalog federation to query Databricks-managed data</title>
		<link>https://noise.getoto.net/2026/09/15/how-united-airlines-uses-amazon-redshift-and-aws-glue-data-catalog-federation-to-query-databricks-managed-data/</link>
		
		<dc:creator><![CDATA[Vaibhav Agrawal]]></dc:creator>
		<pubDate>Tue, 15 Sep 2026 15:59:48 +0000</pubDate>
				<category><![CDATA[Advanced (300)]]></category>
		<category><![CDATA[Amazon Redshift]]></category>
		<category><![CDATA[AWS Glue]]></category>
		<category><![CDATA[Customer Solutions]]></category>
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					<description><![CDATA[Learn how United Airlines uses AWS Glue Data Catalog federation to query Databricks Unity Catalog data directly from Amazon Redshift Serverless without duplicating data, using resource links and AWS Lake Formation for governance.]]></description>
		
		
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			</item>
		<item>
		<title>Every team is a data team — bring Amazon Redshift analytics to ChatGPT Work</title>
		<link>https://noise.getoto.net/2026/09/10/every-team-is-a-data-team-bring-amazon-redshift-analytics-to-chatgpt-work/</link>
		
		<dc:creator><![CDATA[Naresh Chainani]]></dc:creator>
		<pubDate>Thu, 10 Sep 2026 15:14:01 +0000</pubDate>
				<category><![CDATA[Amazon Redshift]]></category>
		<category><![CDATA[announcements]]></category>
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					<description><![CDATA[AWS is announcing the AWS Data Analytics plugin for the new Data agent in ChatGPT Work. Teams can ask questions in natural language, analyze governed data across their Amazon Redshift data warehouse and data lakes, and build shareable dashboards, all from a conversation in ChatGPT Work.]]></description>
		
		
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			</item>
		<item>
		<title>AWS Weekly Roundup: Claude Fable 5.1 on AWS, Amazon Linux 2027 preview, AWS Certified AI Business Strategist, and more (September 7, 2026)</title>
		<link>https://noise.getoto.net/2026/09/07/aws-weekly-roundup-claude-fable-5-1-on-aws-amazon-linux-2027-preview-aws-certified-ai-business-strategist-and-more-september-7-2026/</link>
		
		<dc:creator><![CDATA[Channy Yun (윤석찬)]]></dc:creator>
		<pubDate>Mon, 07 Sep 2026 14:24:08 +0000</pubDate>
				<category><![CDATA[Amazon Bedrock]]></category>
		<category><![CDATA[Amazon EC2]]></category>
		<category><![CDATA[Amazon Redshift]]></category>
		<category><![CDATA[AWS Lambda]]></category>
		<category><![CDATA[AWS Training and Certification]]></category>
		<category><![CDATA[news]]></category>
		<category><![CDATA[Security, Identity & Compliance]]></category>
		<category><![CDATA[Week in Review]]></category>
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					<description><![CDATA[Last week, Claude Fable 5.1 became available on AWS. According to Anthropic, Claude Fable 5.1 delivers frontier intelligence for ambitious tasks across coding, scientific research, and enterprise workflows. Claude Fable 5.1 is built for long-running, high-stakes work that runs for hours and spans many applications. It can own more of a software project on its […]]]></description>
		
		
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			</item>
		<item>
		<title>How Moovit achieved 33% cost optimization through architectural modernization</title>
		<link>https://noise.getoto.net/2026/09/03/how-moovit-achieved-33-cost-optimization-through-architectural-modernization/</link>
		
		<dc:creator><![CDATA[Saar Porat]]></dc:creator>
		<pubDate>Thu, 03 Sep 2026 16:23:46 +0000</pubDate>
				<category><![CDATA[Amazon EMR]]></category>
		<category><![CDATA[Amazon Redshift]]></category>
		<category><![CDATA[Customer Solutions]]></category>
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					<description><![CDATA[Learn how Moovit modernized its data platform with a multi-engine lakehouse architecture: offloading heavy aggregation workloads from Amazon Redshift to Amazon EMR with Spark SQL, isolating workloads with Amazon Redshift Serverless, and cutting overall data pipeline cost by 33%.]]></description>
		
		
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			</item>
		<item>
		<title>Integrate Amazon Redshift and IAM Identity Center with enhanced VPC routing</title>
		<link>https://noise.getoto.net/2026/08/31/integrate-amazon-redshift-and-iam-identity-center-with-enhanced-vpc-routing/</link>
		
		<dc:creator><![CDATA[Maneesh Sharma]]></dc:creator>
		<pubDate>Mon, 31 Aug 2026 17:22:40 +0000</pubDate>
				<category><![CDATA[Advanced (300)]]></category>
		<category><![CDATA[Amazon Redshift]]></category>
		<category><![CDATA[announcements]]></category>
		<category><![CDATA[AWS IAM Identity Center]]></category>
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					<description><![CDATA[Amazon Redshift now supports AWS IAM Identity Center authentication on clusters and workgroups that use enhanced VPC routing. Create two interface VPC endpoints to give your users single sign-on with their corporate credentials while keeping all authentication traffic on the AWS private network.]]></description>
		
		
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			</item>
		<item>
		<title>Razor Group’s journey to a modern data lakehouse on AWS</title>
		<link>https://noise.getoto.net/2026/08/28/razor-groups-journey-to-a-modern-data-lakehouse-on-aws/</link>
		
		<dc:creator><![CDATA[Yaswanth Kothainti]]></dc:creator>
		<pubDate>Fri, 28 Aug 2026 16:25:02 +0000</pubDate>
				<category><![CDATA[Amazon Redshift]]></category>
		<category><![CDATA[Amazon S3 Tables]]></category>
		<category><![CDATA[Customer Solutions]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=fd6bb64614cc18c57b11726c62a85269</guid>

					<description><![CDATA[Razor Group, one of Europe's leading ecommerce aggregators managing 250+ brands, migrated from always-on Amazon Redshift clusters to an open lakehouse on Apache Iceberg, Amazon S3 Tables, and Apache Spark. Learn the architectural decisions, the five-phase migration, and the results: 65% faster P95 queries and a 63% infrastructure cost reduction.]]></description>
		
		
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			</item>
		<item>
		<title>Long-term system tables retention in Amazon Redshift with Amazon S3 Tables</title>
		<link>https://noise.getoto.net/2026/08/20/long-term-system-tables-retention-in-amazon-redshift-with-amazon-s3-tables/</link>
		
		<dc:creator><![CDATA[Nidhi Nayak]]></dc:creator>
		<pubDate>Thu, 20 Aug 2026 19:20:20 +0000</pubDate>
				<category><![CDATA[Amazon Redshift]]></category>
		<category><![CDATA[Amazon S3 Tables]]></category>
		<category><![CDATA[announcements]]></category>
		<category><![CDATA[Intermediate (200)]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=38d2fbc2b59366045a96e5a481c6cd47</guid>

					<description><![CDATA[Amazon Redshift system table integration with Amazon S3 Tables automatically delivers your system table logs to Amazon S3 Tables in Apache Iceberg format. You can retain this data well beyond the 7-day limit for compliance, auditing, and cross-warehouse observability, without custom ETL pipelines or cluster resource consumption.]]></description>
		
		
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			</item>
		<item>
		<title>Amazon Redshift multi-Region disaster recovery</title>
		<link>https://noise.getoto.net/2026/08/03/amazon-redshift-multi-region-disaster-recovery/</link>
		
		<dc:creator><![CDATA[Werner Gunter]]></dc:creator>
		<pubDate>Mon, 03 Aug 2026 16:22:56 +0000</pubDate>
				<category><![CDATA[Advanced (300)]]></category>
		<category><![CDATA[Amazon Redshift]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=bb30d18492d37c877714e2ae99dbe01d</guid>

					<description><![CDATA[In this post, we walk through the core concepts of cross-Region disaster recovery, introduce a framework for assessing your requirements, and then dive deep into three primary DR strategies for Amazon Redshift: Active-Passive, Active-Active, and a Hybrid approach. For each strategy, we cover architecture, trade-offs, implementation guidance, and cost considerations so you can make an informed decision for your workload.]]></description>
		
		
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			</item>
		<item>
		<title>Upgrade Amazon Redshift DC2 clusters to the new Amazon Redshift RG</title>
		<link>https://noise.getoto.net/2026/08/03/upgrade-amazon-redshift-dc2-clusters-to-the-new-amazon-redshift-rg/</link>
		
		<dc:creator><![CDATA[Ricardo Serafim]]></dc:creator>
		<pubDate>Mon, 03 Aug 2026 16:09:37 +0000</pubDate>
				<category><![CDATA[Advanced (300)]]></category>
		<category><![CDATA[Amazon Redshift]]></category>
		<category><![CDATA[Technical How-to]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=92b255d3f9e24675d2a2921663d1b7fc</guid>

					<description><![CDATA[Upgrading your Amazon Redshift DC2 clusters to AWS Graviton-based RG instances unlocks managed storage, data sharing, zero-ETL, and an integrated data lake engine. This post covers the new features, node-mapping guidance for sizing, the available upgrade methods, and how to validate your target configuration with Amazon Redshift Test Drive.]]></description>
		
		
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		<item>
		<title>Govern Amazon Redshift Data Warehouses Data Across Accounts using Amazon SageMaker Unified Studio</title>
		<link>https://noise.getoto.net/2026/07/20/govern-amazon-redshift-data-warehouses-data-across-accounts-using-amazon-sagemaker-unified-studio/</link>
		
		<dc:creator><![CDATA[Bandana Das]]></dc:creator>
		<pubDate>Mon, 20 Jul 2026 16:48:33 +0000</pubDate>
				<category><![CDATA[Advanced (300)]]></category>
		<category><![CDATA[Amazon Redshift]]></category>
		<category><![CDATA[Amazon SageMaker Unified Studio]]></category>
		<category><![CDATA[Technical How-to]]></category>
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					<description><![CDATA[In this post, we show you how to use Amazon SageMaker Unified Studio to implement cross-account data sharing in Amazon Redshift using data mesh principles. We demonstrate how to build a scalable data mesh architecture that supports secure, auditable data sharing across AWS accounts while reducing operational burden.]]></description>
		
		
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		<item>
		<title>Patch perfect: Automating Amazon Redshift patch testing</title>
		<link>https://noise.getoto.net/2026/07/14/patch-perfect-automating-amazon-redshift-patch-testing/</link>
		
		<dc:creator><![CDATA[Eva Donaldson]]></dc:creator>
		<pubDate>Tue, 14 Jul 2026 16:37:11 +0000</pubDate>
				<category><![CDATA[Advanced (300)]]></category>
		<category><![CDATA[Amazon Elastic Container Service]]></category>
		<category><![CDATA[Amazon EventBridge]]></category>
		<category><![CDATA[Amazon Redshift]]></category>
		<category><![CDATA[Amazon Simple Notification Service (SNS)]]></category>
		<category><![CDATA[Amazon Simple Storage Service (S3)]]></category>
		<category><![CDATA[AWS Lambda]]></category>
		<category><![CDATA[Technical How-to]]></category>
		<guid isPermaLink="false">http://noise.getoto.net/?guid=8421d167704be7b5e1fe6657f68cc0a0</guid>

					<description><![CDATA[In this post, we demonstrate an automated test suite that validates your Amazon Redshift cluster automatically after any patch, reboot, or modification. It uses standard drivers against real workload patterns to provide a verified gate between a patch landing and that patch reaching production.]]></description>
		
		
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		<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>
		
		
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		<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>
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					<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>
		
		
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		<item>
		<title>Amazon Redshift RG: Faster and lower cost, Graviton-powered</title>
		<link>https://noise.getoto.net/2026/07/02/amazon-redshift-rg-faster-and-lower-cost-graviton-powered/</link>
		
		<dc:creator><![CDATA[Stefan Gromoll]]></dc:creator>
		<pubDate>Thu, 02 Jul 2026 16:21:06 +0000</pubDate>
				<category><![CDATA[Amazon Redshift]]></category>
		<category><![CDATA[announcements]]></category>
		<category><![CDATA[Intermediate (200)]]></category>
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					<description><![CDATA[In this post, we describe the innovations that make RG instances so much faster. We also share benchmark results showing that RG delivers up to 4.2x better price-performance than other leading data warehouses.]]></description>
		
		
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