AWS Big Data

JULY 20, 2023

With data becoming the driving force behind many industries today, having a modern data architecture is pivotal for organizations to be successful. In this post, we describe Orca’s journey building a transactional data lake using Amazon Simple Storage Service (Amazon S3), Apache Iceberg, and AWS Analytics.

Data Lake 93

Data Lake Analytics Snapshot Data Quality 93

AWS Big Data

APRIL 27, 2023

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). The first task performs an initial copy of the full data into an S3 folder.

Data Lake 80

Data Lake Snapshot Optimization Data Transformation 80

AWS Big Data

JANUARY 27, 2023

Verify all table metadata is stored in the AWS Glue Data Catalog. Consume data with Athena or Amazon EMR Trino for business analysis. Update and delete source records in Amazon RDS for MySQL and validate the reflection of the data lake tables. the Flink table API/SQL can integrate with the AWS Glue Data Catalog.

Data Lake 66

Data Lake Metadata Business Analysis Data-driven 66

AWS Big Data

FEBRUARY 18, 2025

To optimize their security operations, organizations are adopting modern approaches that combine real-time monitoring with scalable data analytics. They are using data lake architectures and Apache Iceberg to efficiently process large volumes of security data while minimizing operational overhead.

Snapshot 76

Snapshot Optimization Data Lake Metadata 76

AWS Big Data

NOVEMBER 6, 2024

Second, because traditional data warehousing approaches are unable to keep up with the volume, velocity, and variety of data, engineering teams are building data lakes and adopting open data formats such as Parquet and Apache Iceberg to store their data.

Metadata 108

Metadata Data Lake Management Internet of Things 108