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Use Apache Iceberg in your data lake with Amazon S3, AWS Glue, and Snowflake

AWS Big Data

They understand that a one-size-fits-all approach no longer works, and recognize the value in adopting scalable, flexible tools and open data formats to support interoperability in a modern data architecture to accelerate the delivery of new solutions. Snowflake can query across Iceberg and Snowflake table formats.

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Exploring real-time streaming for generative AI Applications

AWS Big Data

Furthermore, data events are filtered, enriched, and transformed to a consumable format using a stream processor. The result is made available to the application by querying the latest snapshot. For more information, refer to Notions of Time: Event Time and Processing Time. For more information, refer to Dynamic Tables.

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Architectural patterns for real-time analytics using Amazon Kinesis Data Streams, part 1

AWS Big Data

Kinesis Data Streams has native integrations with other AWS services such as AWS Glue and Amazon EventBridge to build real-time streaming applications on AWS. Refer to Amazon Kinesis Data Streams integrations for additional details. To access your data from Timestream, you need to install the Timestream plugin for Grafana.

Analytics 111
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Load data incrementally from transactional data lakes to data warehouses

AWS Big Data

Data lakes and data warehouses are two of the most important data storage and management technologies in a modern data architecture. Data lakes store all of an organization’s data, regardless of its format or structure. Delta Lake doesn’t have a specific concept for incremental queries.

Data Lake 111
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Build a multi-Region and highly resilient modern data architecture using AWS Glue and AWS Lake Formation

AWS Big Data

This means that if data is moved from a bucket in the source Region to another bucket in the target Region, the data access permissions need to be reapplied in the target Region. AWS Glue Data Catalog The AWS Glue Data Catalog is a central repository of metadata about data stored in your data lake.

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Migrate Microsoft Azure Synapse Analytics to Amazon Redshift using AWS SCT

AWS Big Data

Amazon Redshift is a fast, fully managed, petabyte-scale data warehouse that provides the flexibility to use provisioned or serverless compute for your analytical workloads. The decoupled compute and storage architecture of Amazon Redshift enables you to build highly scalable, resilient, and cost-effective workloads.

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Simplify operational data processing in data lakes using AWS Glue and Apache Hudi

AWS Big Data

The Analytics specialty practice of AWS Professional Services (AWS ProServe) helps customers across the globe with modern data architecture implementations on the AWS Cloud. The company wanted the ability to continue processing operational data in the secondary Region in the rare event of primary Region failure.