Remove Data Lake Remove Data Processing Remove Management Remove Metadata
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Migrate an existing data lake to a transactional data lake using Apache Iceberg

AWS Big Data

A data lake is a centralized repository that you can use to store all your structured and unstructured data at any scale. You can store your data as-is, without having to first structure the data and then run different types of analytics for better business insights.

Data Lake 105
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Build a serverless transactional data lake with Apache Iceberg, Amazon EMR Serverless, and Amazon Athena

AWS Big Data

Since the deluge of big data over a decade ago, many organizations have learned to build applications to process and analyze petabytes of data. Data lakes have served as a central repository to store structured and unstructured data at any scale and in various formats.

Data Lake 105
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Modernize your ETL platform with AWS Glue Studio: A case study from BMS

AWS Big Data

In addition to using native managed AWS services that BMS didn’t need to worry about upgrading, BMS was looking to offer an ETL service to non-technical business users that could visually compose data transformation workflows and seamlessly run them on the AWS Glue Apache Spark-based serverless data integration engine.

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Petabyte-scale log analytics with Amazon S3, Amazon OpenSearch Service, and Amazon OpenSearch Ingestion

AWS Big Data

Organizations often need to manage a high volume of data that is growing at an extraordinary rate. At the same time, they need to optimize operational costs to unlock the value of this data for timely insights and do so with a consistent performance. We think of this concept as inside-out data movement.

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Introducing AWS Glue crawler and create table support for Apache Iceberg format

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. Iceberg captures metadata information on the state of datasets as they evolve and change over time. For more details, refer to Creating Apache Iceberg tables.

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Query your Apache Hive metastore with AWS Lake Formation permissions

AWS Big Data

The Hive metastore is a repository of metadata about the SQL tables, such as database names, table names, schema, serialization and deserialization information, data location, and partition details of each table. Apache Hive, Apache Spark, Presto, and Trino can all use a Hive Metastore to retrieve metadata to run queries.

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Configure cross-Region table access with the AWS Glue Catalog and AWS Lake Formation

AWS Big Data

Today’s modern data lakes span multiple accounts, AWS Regions, and lines of business in organizations. It’s important that their data solution gives them the ability to share and access data securely and safely across Regions. A resource link is a Data Catalog object that is a link to a database or table.