Remove Data Processing Remove Metadata Remove Reference Remove Snapshot
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Modernize a legacy real-time analytics application with Amazon Managed Service for Apache Flink

AWS Big Data

Frequent materialized view refreshes on top of constantly changing base tables due to streamed data can lead to snapshot isolation errors. The second streaming data source constitutes metadata information about the call center organization and agents that gets refreshed throughout the day. We use two datasets in this post.

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Power enterprise-grade Data Vaults with Amazon Redshift – Part 2

AWS Big Data

Data Vault overview For a brief review of the core Data Vault premise and concepts, refer to the first post in this series. For more information, refer to Amazon Redshift database encryption. Chargeback metadata Amazon Redshift provides different pricing models to cater to different customer needs. model in Amazon Redshift.

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Build a data lake with Apache Flink on Amazon EMR

AWS Big Data

The AWS Glue Data Catalog provides a uniform repository where disparate systems can store and find metadata to keep track of data in data silos. With unified metadata, both data processing and data consuming applications can access the tables using the same metadata. For metadata read/write, Flink has the catalog interface.

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

AWS Big Data

Iceberg captures metadata information on the state of datasets as they evolve and change over time. AWS Glue crawlers will extract schema information and update the location of Iceberg metadata and schema updates in the Data Catalog. For more details, refer to Creating Apache Iceberg tables. Choose Create.

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Build incremental data pipelines to load transactional data changes using AWS DMS, Delta 2.0, and Amazon EMR Serverless

AWS Big Data

Although this post uses an Aurora PostgreSQL database hosted on AWS as the data source, the solution can be extended to ingest data from any of the AWS DMS supported databases hosted on your data centers. Let’s refer to this S3 bucket as the raw layer. Refer to Submitting EMR Serverless jobs from Airflow for additional details.

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Why Replicating HBase Data Using Replication Manager is the Best Choice

Cloudera

The service provides simple, easy-to-use, and feature-rich data movement capability to deliver data and metadata where it is needed, and has secure data backup and disaster recovery functionality. In this method, you prepare the data for migration, and then set up the replication plugin to use a snapshot to migrate your data.