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

AWS Big Data

licensed, 100% open-source data table format that helps simplify data processing on large datasets stored in data lakes. Data engineers use Apache Iceberg because it’s fast, efficient, and reliable at any scale and keeps records of how datasets change over time.

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Use Apache Iceberg in a data lake to support incremental data processing

AWS Big Data

Iceberg has become very popular for its support for ACID transactions in data lakes and features like schema and partition evolution, time travel, and rollback. In early 2022, AWS announced general availability of Athena ACID transactions, powered by Apache Iceberg. and later supports the Apache Iceberg framework for data lakes.

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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.

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Backtesting index rebalancing arbitrage with Amazon EMR and Apache Iceberg

AWS Big Data

Terminology Let’s first discuss some of the terminology used in this post: Research data lake on Amazon S3 – A data lake is a large, centralized repository that allows you to manage all your structured and unstructured data at any scale. This is where the tagging feature in Apache Iceberg comes in handy.

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Perform upserts in a data lake using Amazon Athena and Apache Iceberg

AWS Big Data

Amazon Athena supports the MERGE command on Apache Iceberg tables, which allows you to perform inserts, updates, and deletes in your data lake at scale using familiar SQL statements that are compliant with ACID (Atomic, Consistent, Isolated, Durable).

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Choosing an open table format for your transactional data lake on AWS

AWS Big Data

A modern data architecture enables companies to ingest virtually any type of data through automated pipelines into a data lake, which provides highly durable and cost-effective object storage at petabyte or exabyte scale.

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Introducing native support for Apache Hudi, Delta Lake, and Apache Iceberg on AWS Glue for Apache Spark, Part 2: AWS Glue Studio Visual Editor

AWS Big Data

In the first post of this series , we described how AWS Glue for Apache Spark works with Apache Hudi, Linux Foundation Delta Lake, and Apache Iceberg datasets tables using the native support of those data lake formats. For S3 URL , enter s3://noaa-ghcn-pds/csv/by_year/2022.csv. The data source is configured.