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aws.amazon.com /1 month ago

Unleashing Agentic AI Analytics on Amazon SageMaker with Amazon Athena and Amazon Quick

This post demonstrates how agentic AI assistant from Amazon Quick transform data analytics into a self-service capability by using Amazon Simple Storage Service (Amazon S3) as a st...

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aws.amazon.com /3 weeks ago

From data lake to AI-ready analytics: Introducing new data source with S3 Tables in Amazon Quick

Amazon Quick introduces Amazon S3 Tables (Apache Iceberg tables) as a new data source. With this feature, customers can directly query and visualize Apache Iceberg tables stored in...

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aws.amazon.com /1 month ago

Get to insights faster using Notebooks in Amazon SageMaker Unified Studio

In this post, we demonstrate how Notebooks in Amazon SageMaker Unified Studio help you get to insights faster by simplifying infrastructure configuration. You'll see how to analyze...

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cloud.google.com /1 month ago

The future of data lakehouse: Open and interoperable for the agentic era

Traditional lakehouses were engineered for the era of reporting, not the high-velocity, multimodal demands of AI agents. To bridge this gap, architecture must evolve into an AI-nat...

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aws.amazon.com /1 week ago

How Amazon is moving to integrate catalogs to improve data discovery with Amazon SageMaker

Enterprises face challenges when teams create data assets outside of central data catalogs. It adds overhead for discovery, and limits collaboration. Amazon’s Business Data Technol...

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aws.amazon.com /1 month ago

Analyzing your data catalog: Query SageMaker Catalog metadata with SQL

In this post, we demonstrate how to use the metadata export capability in Amazon SageMaker Catalog and perform analytics such as historical changes, monitor asset growth and track...

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aws.amazon.com /2 weeks ago

Fine-tune LLM with Databricks Unity Catalog and Amazon SageMaker AI

In this post, we demonstrate how to build a secure, complete LLM fine-tuning workflow that integrates Unity Catalog with Amazon SageMaker AI using Amazon EMR Serverless for preproc...

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aws.amazon.com /1 month ago

End-to-end lineage with DVC and Amazon SageMaker AI MLflow apps

In this post, we show how to combine DVC (Data Version Control), Amazon SageMaker AI, and Amazon SageMaker AI MLflow Apps to build end-to-end ML model lineage. We walk through two...

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aws.amazon.com /1 day ago

Comprehensive observability for Amazon SageMaker AI LLM inference: From GPU utilization to LLM quality

This post demonstrates a comprehensive observability solution using Amazon Managed Grafana dashboards that provides a holistic view of both quality and quantity for LLMs served on...

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aws.amazon.com /1 month ago

Stream live data from Amazon Keyspaces to S3 vector for real time AI applications

In this post, you learn how to build a real-time AI movie recommendation system by streaming live data changes from Amazon Keyspaces to Amazon S3 vector storage. The post shows how...

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aws.amazon.com /3 weeks ago

Streamlining generative AI development with MLflow v3.10 on Amazon SageMaker AI

Today, we’re excited to announce that Amazon SageMaker AI MLflow Apps now support MLflow version 3.10, bringing enhanced capabilities for generative AI development and streamlined...

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cloud.google.com /1 month ago

Openness without compromises for your Apache Iceberg lakehouse

Today, at the Apache Iceberg Summit in San Francisco, we are announcing the preview of read and write interoperability between BigQuery and Iceberg-compatible engines, including Tr...

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aws.amazon.com /1 week ago

Accelerate ML feature pipelines with new capabilities in Amazon SageMaker Feature Store

Today, we’re announcing three new capabilities available in SageMaker Python SDK v3.8.0. In this post, we walk through each capability with code examples you can use to get started...

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databricks.com /3 days ago

Announcing Lakebase Change Data Feed (CDF)

Moving data from your operational database has traditionally meant setting up and...

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aws.amazon.com /1 week ago

Meet Amazon Redshift RG – AWS Graviton-based instances with an integrated data lake query engine delivering up to 2.4x b...

On May 12, 2026, we announced the general availability of Amazon Redshift RG instances, powered by AWS Graviton processors. RG instances are up to 2.2x as fast for data warehouse w...

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databricks.com /3 days ago

How the lakebase architecture stays resilient to cloud failures

In the last year, agents have strained the limits of cloud infrastructure with new...

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aws.amazon.com /1 week ago

Build real-time voice applications with Amazon SageMaker AI and vLLM

Voice agents, live captioning, contact center analytics, and accessibility tools all depend on real-time speech-to-text, where your application streams audio in and receives transc...

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aws.amazon.com /4 days ago

Build an enterprise observability solution for Amazon Quick

When hundreds to thousands of users are onboarded to an enterprise AI platform, business leaders and platform owners need visibility into who is using the platform, whether users a...

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aws.amazon.com /2 weeks ago

Improve DynamoDB analytics with AWS Glue zero-ETL schema and partition controls

In this post, you learn how to replicate Amazon DynamoDB data to Apache Iceberg tables in Amazon S3 through a zero-ETL integration. We walk through the challenges that the DynamoDB...

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dzone.com /1 week ago

Architecting Petabyte-Scale Hyperspectral Pipelines on AWS

The Data Challenge Every industry has its version of the same data engineering problem: massive, complex payloads generated at the edge — far from the cloud, often on unreliable ne...

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dipayan-x-das.medium.com /1 week ago

When to Keep AI in Snowflake, and When to Extend to AWS: A 2026 Decision Framework

A practitioner’s view on Snowflake Cortex AI + Snowpark Container Services versus SageMaker, Bedrock, and Bedrock AgentCore — grounded in…Continue reading on Medium »

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aws.amazon.com /1 month ago

Building unified data pipelines with Apache Iceberg and Apache Flink

In this post, you build a unified pipeline using Apache Iceberg and Amazon Managed Service for Apache Flink that replaces the dual-pipeline approach. This walkthrough is for interm...

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aws.amazon.com /2 weeks ago

Optimize Amazon S3 Tables queries with Amazon Redshift

This is the third post in our S3 Tables and Amazon Redshift series. The first post covered getting started with querying Apache Iceberg tables, and the second post walked through e...

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databricks.com /3 days ago

Introducing Always-On pricing: automatic savings for Databricks Lakebase

Most managed operational databases force you into a corner: choose "Serverless" for...

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