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dev.to /2 weeks ago

Building a Modern Data Lakehouse on AWS: S3, Iceberg, Glue, Athena, and Lake Formation

The data lakehouse has become the default architecture for analytics on AWS in 2026. It combines the best of both worlds: the low-cost, schema-flexible storage of a data lake (S3)...

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aws.amazon.com /1 month ago

Multi-cloud lakehouse architecture on AWS for Agentic AI, Part 1: Architecture and best practices

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 acces...

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cloud.google.com /1 month ago

The borderless Lakehouse: Bring AWS, Databricks and Snowflake data to your AI agents

Today’s data lakehouse is no longer mere data repository, but increasingly a system of action, actively executing tasks via always-on, autonomous AI agents. Rather than waiting for...

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aws.amazon.com /3 weeks ago

Unlocking real-time analytics: Streaming Aurora DSQL changes into Apache Iceberg

Stream Amazon Aurora DSQL change data capture (CDC) events into Apache Iceberg tables on Amazon S3 with Amazon Data Firehose, then query them using Amazon Athena. This post walks t...

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aws.amazon.com /6 days ago

Building medallion architecture with Iceberg materialized views in Amazon SageMaker

With Apache Iceberg materialized views in Amazon SageMaker, you can build a Bronze, Silver, and Gold medallion architecture as three SQL statements. This declarative approach folds...

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aws.amazon.com /1 month ago

Scaling fine-grained access control for enterprise lakehouse using SageMaker Unified Studio and AWS Lake Formation

As enterprise lakehouses grow to thousands of tables across business domains and regions, fine-grained access control becomes a governance bottleneck. This post shows how to combin...

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aws.amazon.com /1 week ago

Razor Group’s journey to a modern data lakehouse on AWS

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...

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forrester.com /1 month ago

Takeaways From The Forrester Waveâ„¢: Data Lakehouses, Q3 2026

The enterprise data lakehouse is evolving. Once designed primarily to consolidate data for analytics, today’s lakehouse has become the operational foundation for agentic AI, delive...

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aws.amazon.com /2 weeks ago

Build a no-code ML workflow with Snowflake, Amazon SageMaker Canvas and Amazon Quick – Part 3: Visualizing insights with...

In Part 3 of this no-code ML series, you bring fraud detection predictions to life. Import your Amazon SageMaker Canvas predictions into Amazon Quick Sight, build interactive dashb...

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databricks.com /1 week ago

Building for the AI Era: Lakebase, Streaming, and Lakehouse Innovations at VLDB 2026

We are headed to VLDB 2026 to share multiple innovations that power the Databricks platform...

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aws.amazon.com /6 days ago

Build a dynamic streaming data lake with Apache Iceberg and Apache Flink

Learn how to build a dynamic streaming data lake on Amazon Managed Service for Apache Flink that adapts to new event types and schema changes without stopping the pipeline, using A...

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databricks.com /1 week ago

Object Storage + WAL: Lakebase Postgres for the agentic era

Agents that interact with a traditional OLTP database often create bottlenecks at the storage layer. New deployments...

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snowflake.com /1 month ago

Apache Iceberg Lakehouse: Snowflake & Google Cloud

Discover how Snowflake and Google Cloud use Apache Iceberg to build an open, AI-ready lakehouse. Achieve data interoperability without vendor lock-in.

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aws.amazon.com /2 weeks ago

Build a no-code ML workflow with Snowflake, Amazon SageMaker Canvas and Amazon Quick – Part 1: Setting up your Snowflake...

Healthcare, retail, and life sciences teams store large volumes of operational data in Snowflake, but turning it into predictions is hard. In Part 1 of this series, you set up your...

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databricks.com /1 month ago

Foundational context: Cross-industry & function-specific accelerators for Lakebase

Databricks Lakebase is a fully managed, serverless Postgres database built for the...

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aws.amazon.com /2 weeks ago

Build a no-code ML workflow with Snowflake, Amazon SageMaker Canvas and Amazon Quick – Part 2: Data preparation and mode...

In Part 2 of this no-code ML series, you connect Amazon SageMaker Canvas to Snowflake, prepare and join transaction data with Data Wrangler visual transformations, and train an XGB...

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aws.amazon.com /2 weeks ago

AWS and DuckLabs: Building the future of analytics together

Today we are announcing that Amazon has signed a definitive agreement to acquire DuckLabs, the Amsterdam-based company behind the open-source analytical database DuckDB. We expect...

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aws.amazon.com /6 days ago

Query Amazon S3 Tables from Amazon EMR Trino using the Iceberg REST endpoint

Learn how to query Amazon S3 Tables from Trino on Amazon EMR using the Apache Iceberg REST catalog endpoint. This post shows how to deploy the integration with AWS CloudFormation,...

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aws.amazon.com /22 hours ago

Govern models with MLflow and Amazon SageMaker AI Model Registry sync: Part 1

Managed MLflow on Amazon SageMaker AI now syncs richer model metadata (training metrics, evaluation results, inference specs, and lineage) into the SageMaker AI Model Registry, wit...

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aws.amazon.com /2 weeks ago

Enable cross-cloud analytics with Amazon S3 Tables and Google BigQuery, Part 2: access control with Lake Formation

In Part 2 of this series, connect Google BigQuery to Amazon S3 Tables using AWS Lake Formation credential vending. Lake Formation manages fine-grained permissions and issues short-...

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aws.amazon.com /1 week ago

Deliver real-time data to streaming tables for Apache Iceberg with Amazon Kinesis Data Streams

Amazon Kinesis Data Streams now supports streaming tables, a fully managed capability that continuously delivers your streaming data as queryable Apache Iceberg tables on Amazon S3...

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aws.amazon.com /3 weeks ago

How Jumio built a real-time feature store on AWS

Learn how Jumio built a centralized, real-time feature store on AWS with Amazon SageMaker Feature Store, Amazon Managed Service for Apache Flink, and Amazon Kinesis Data Streams. T...

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aws.amazon.com /1 week ago

Deepgram deepens Amazon SageMaker AI observability with Enhanced Metrics

Self-hosted speech AI carries an observability trade-off: the numbers that drive capacity planning and cost management stay locked inside the vendor container. Deepgram closes that...

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aws.amazon.com /1 week ago

Build with geospatial and variant types in Iceberg v3 on AWS Glue 6.0

AWS Glue 6.0 with Apache Spark 4.1 adds support for Apache Iceberg v3: native geospatial types, nanosecond-precision timestamps, the VARIANT type, and DEFAULT column values. This p...

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