AWS prescriptive-guidance documentation change
Summary
Updated image path, added bold formatting to AWS service names, minor text adjustments, and changed 'following section' to 'next section'.
Security assessment
The changes are purely cosmetic and structural: image path update, formatting enhancements (bolding service names), and minor wording adjustments. No security vulnerabilities, fixes, or new security features are mentioned. Existing security references (e.g., S3 security/compliance, Lake Formation access controls) remain unchanged.
Diff
diff --git a/prescriptive-guidance/latest/apache-iceberg-on-aws/data-lakes.md b/prescriptive-guidance/latest/apache-iceberg-on-aws/data-lakes.md index c88efcda6..9ea68e8b9 100644 --- a//prescriptive-guidance/latest/apache-iceberg-on-aws/data-lakes.md +++ b//prescriptive-guidance/latest/apache-iceberg-on-aws/data-lakes.md @@ -73 +73 @@ Apache Iceberg is supported by AWS services such as [Amazon EMR](https://aws.ama - + @@ -77 +77 @@ The following AWS services provide native Iceberg integrations. There are additi - * [Amazon S3](https://docs.aws.amazon.com/AmazonS3/latest/userguide/Welcome.html) is the best place to build data lakes because of its durability, availability, scalability, security, compliance, and audit capabilities. Iceberg was designed and built to interact with Amazon S3 seamlessly, and provides support for many Amazon S3 features as listed in the [Iceberg documentation](https://iceberg.apache.org/docs/latest/aws/#s3-fileio). In addition, [Amazon S3 Tables](https://docs.aws.amazon.com/AmazonS3/latest/userguide/s3-tables.html) deliver the first cloud object store with built-in Iceberg support and streamline storing tabular data at scale. With S3 Tables support for Iceberg, you can easily query your tabular data by using popular AWS and third-party query engines. + * [**Amazon S3**](https://docs.aws.amazon.com/AmazonS3/latest/userguide/Welcome.html) is the best place to build data lakes because of its durability, availability, scalability, security, compliance, and audit capabilities. Iceberg was designed and built to interact with Amazon S3 seamlessly, and provides support for many Amazon S3 features as listed in the [Iceberg documentation](https://iceberg.apache.org/docs/latest/aws/#s3-fileio). In addition, [Amazon S3 Tables](https://docs.aws.amazon.com/AmazonS3/latest/userguide/s3-tables.html) deliver the first cloud object store with built-in Iceberg support and streamline storing tabular data at scale. With S3 Tables support for Iceberg, you can easily query your tabular data by using popular AWS and third-party query engines. @@ -79 +79 @@ The following AWS services provide native Iceberg integrations. There are additi - * [The next generation of SageMaker](https://aws.amazon.com/sagemaker/) is built on an open lakehouse architecture that unifies data access across Amazon S3 data lakes, Amazon Redshift data warehouses, and third-party and federated data sources. These capabilities help you build powerful analytics and AI/ML applications on a single copy of data. The lakehouse is fully compatible with Iceberg, so you have the flexibility to access and query data in place by using the Iceberg REST API. + * [**The next generation of SageMaker**](https://aws.amazon.com/sagemaker/)**** is built on an open lakehouse architecture that unifies data access across Amazon S3 data lakes, Amazon Redshift data warehouses, and third-party and federated data sources. These capabilities help you build powerful analytics and AI/ML applications on a single copy of data. The lakehouse is fully compatible with Iceberg, so you have the flexibility to access and query data in place by using the Iceberg REST API. @@ -81 +81 @@ The following AWS services provide native Iceberg integrations. There are additi - * [Amazon EMR](https://docs.aws.amazon.com/emr/) is a big data solution for petabyte-scale data processing, interactive analytics, and machine learning by using open source frameworks such as Apache Spark, Flink, Trino, and Hive. Amazon EMR can run on customized Amazon Elastic Compute Cloud (Amazon EC2) clusters, Amazon Elastic Kubernetes Service (Amazon EKS), AWS Outposts, or Amazon EMR Serverless. + * [**Amazon EMR**](https://docs.aws.amazon.com/emr/) is a big data solution for petabyte-scale data processing, interactive analytics, and machine learning by using open source frameworks such as Apache Spark, Flink, Trino, and Hive. Amazon EMR can run on customized Amazon Elastic Compute Cloud (Amazon EC2) clusters, Amazon Elastic Kubernetes Service (Amazon EKS), AWS Outposts, or Amazon EMR Serverless. @@ -83 +83 @@ The following AWS services provide native Iceberg integrations. There are additi - * [Amazon Athena](https://docs.aws.amazon.com/athena/latest/ug/what-is.html) is a serverless, interactive analytics service that's built on open source frameworks. It supports open-table and file formats and provides a simplified, flexible way to analyze petabytes of data where it lives. Athena provides native support for read, time travel, write, and DDL queries for Iceberg and uses the AWS Glue Data Catalog for the Iceberg metastore. + * [**Amazon Athena**](https://docs.aws.amazon.com/athena/latest/ug/what-is.html) is a serverless, interactive analytics service that's built on open source frameworks. It supports open-table and file formats and provides a simplified, flexible way to analyze petabytes of data where it lives. Athena provides native support for read, time travel, write, and DDL queries for Iceberg and uses the AWS Glue Data Catalog for the Iceberg metastore. @@ -85 +85 @@ The following AWS services provide native Iceberg integrations. There are additi - * [Amazon Redshift](https://docs.aws.amazon.com/redshift/) is a petabyte-scale cloud data warehouse that supports both cluster-based and serverless deployment options. Amazon Redshift Spectrum can query external tables that are registered with the AWS Glue Data Catalog and stored on Amazon S3. Redshift Spectrum also provides support for the Iceberg storage format. + * [**Amazon Redshift**](https://docs.aws.amazon.com/redshift/) is a petabyte-scale cloud data warehouse that supports both cluster-based and serverless deployment options. Amazon Redshift Spectrum can query external tables that are registered with the AWS Glue Data Catalog and stored on Amazon S3. Redshift Spectrum also provides support for the Iceberg storage format. @@ -87 +87 @@ The following AWS services provide native Iceberg integrations. There are additi - * [AWS Glue](https://docs.aws.amazon.com/glue/latest/dg/what-is-glue.html) is a serverless data integration service that makes it easier to discover, prepare, move, and integrate data from multiple sources for analytics, machine learning (ML), and application development. It is fully integrated with Iceberg. Specifically, you can perform read and write operations on Iceberg tables by using AWS Glue jobs, manage tables through the [AWS Glue Data Catalog](https://docs.aws.amazon.com/glue/latest/dg/start-data-catalog.html) (Hive metastore-compatible), discover and register tables automatically by using AWS Glue crawlers, and evaluate data quality in Iceberg tables through the AWS Glue Data Quality feature. The AWS Glue Data Catalog also supports collecting column statistics, calculating and updating the number of distinct values (NDVs) for each column in Iceberg tables, and automatic table optimizations (compaction, snapshot retention, orphan file deletion). AWS Glue also supports zero-ETL integrations from a list of AWS services and third-party applications into Iceberg tables. + * [**AWS Glue**](https://docs.aws.amazon.com/glue/latest/dg/what-is-glue.html) is a serverless data integration service that makes it easier to discover, prepare, move, and integrate data from multiple sources for analytics, machine learning (ML), and application development. It is fully integrated with Iceberg. Specifically, you can perform read and write operations on Iceberg tables by using AWS Glue jobs, manage tables through the [AWS Glue Data Catalog](https://docs.aws.amazon.com/glue/latest/dg/start-data-catalog.html) (Hive metastore-compatible), discover and register tables automatically by using AWS Glue crawlers, and evaluate data quality in Iceberg tables through the AWS Glue Data Quality feature. The AWS Glue Data Catalog also supports collecting column statistics, calculating and updating the number of distinct values (NDVs) for each column in Iceberg tables, and automatic table optimizations (compaction, snapshot retention, orphan file deletion). AWS Glue also supports zero-ETL integrations from a list of AWS services and third-party applications into Iceberg tables. @@ -89 +89 @@ The following AWS services provide native Iceberg integrations. There are additi - * [Amazon Data Firehose](https://docs.aws.amazon.com/firehose/latest/dev/what-is-this-service.html) is a fully managed service for delivering real-time streaming data to destinations such as Amazon S3, Amazon Redshift, Amazon OpenSearch Service, Amazon OpenSearch Serverless, Splunk, Apache Iceberg tables, and any custom HTTP or HTTP endpoints owned by supported third-party service providers, including Datadog, Dynatrace, LogicMonitor, MongoDB, New Relic, Coralogix, and Elastic. With Firehose, you don't need to write applications or manage resources. You configure your data producers to send data to Firehose, and it automatically delivers the data to the destination that you specified. You can also configure Firehose to transform your data before delivering it. + * [**Amazon Data Firehose**](https://docs.aws.amazon.com/firehose/latest/dev/what-is-this-service.html) is a fully managed service for delivering real-time streaming data to destinations such as Amazon S3, Amazon Redshift, Amazon OpenSearch Service, Amazon OpenSearch Serverless, Splunk, Apache Iceberg tables, and any custom HTTP or HTTP endpoints owned by supported third-party service providers, including Datadog, Dynatrace, LogicMonitor, MongoDB, New Relic, Coralogix, and Elastic. With Firehose, you don't need to write applications or manage resources. You configure your data producers to send data to Firehose, and it automatically delivers the data to the destination that you specified. You can also configure Firehose to transform your data before delivering it. @@ -91 +91 @@ The following AWS services provide native Iceberg integrations. There are additi - * [Amazon Managed Service for Apache Flink](https://docs.aws.amazon.com/managed-flink/latest/java/what-is.html) is a fully managed Amazon service that lets you use an Apache Flink application to process streaming data. It supports both reading from and writing to Iceberg tables, and enables real-time data processing and analytics. + * [**Amazon Managed Service for Apache Flink**](https://docs.aws.amazon.com/managed-flink/latest/java/what-is.html) is a fully managed Amazon service that lets you use an Apache Flink application to process streaming data. It supports both reading from and writing to Iceberg tables, and enables real-time data processing and analytics. @@ -93 +93 @@ The following AWS services provide native Iceberg integrations. There are additi - * [Amazon SageMaker AI](https://docs.aws.amazon.com/sagemaker/latest/dg/whatis.html) supports the storage of feature sets in Amazon SageMaker AI Feature Store by using Iceberg format. + * [**Amazon SageMaker AI**](https://docs.aws.amazon.com/sagemaker/latest/dg/whatis.html)**** supports the storage of feature sets in Amazon SageMaker AI Feature Store by using Iceberg format. @@ -95 +95 @@ The following AWS services provide native Iceberg integrations. There are additi - * [AWS Lake Formation](https://docs.aws.amazon.com/lake-formation/latest/dg/what-is-lake-formation.html) provides coarse and fine-grained access control permissions to access data, including Iceberg tables consumed by Athena or Amazon Redshift. To learn more about permissions support for Iceberg tables, see the [Lake Formation documentation](https://docs.aws.amazon.com/lake-formation/latest/dg/working-with-services.html). + * [**AWS Lake Formation**](https://docs.aws.amazon.com/lake-formation/latest/dg/what-is-lake-formation.html) provides coarse and fine-grained access control permissions to access data, including Iceberg tables consumed by Athena or Amazon Redshift. To learn more about permissions support for Iceberg tables, see the [Lake Formation documentation](https://docs.aws.amazon.com/lake-formation/latest/dg/working-with-services.html). @@ -100 +100 @@ The following AWS services provide native Iceberg integrations. There are additi -AWS has a wide range of services that support Iceberg, but covering all these services is beyond the scope of this guide. The following sections cover Spark (batch and structured streaming) on Amazon EMR and AWS Glue, as well as Athena SQL. The [following section](./getting-started.html) provides a quick look at Iceberg support in Athena SQL. +AWS has a wide range of services that support Iceberg, but covering all these services is beyond the scope of this guide. The following sections cover Spark (batch and structured streaming) on Amazon EMR and AWS Glue, as well as Athena SQL. The [next section](./getting-started.html) provides a quick look at Iceberg support in Athena SQL.