Remove Consulting Remove Data Lake Remove Snapshot
article thumbnail

Achieve data resilience using Amazon OpenSearch Service disaster recovery with snapshot and restore

AWS Big Data

This post focuses on introducing an active-passive approach using a snapshot and restore strategy. Snapshot and restore in OpenSearch Service The snapshot and restore strategy in OpenSearch Service involves creating point-in-time backups, known as snapshots , of your OpenSearch domain.

Snapshot 105
article thumbnail

Building end-to-end data lineage for one-time and complex queries using Amazon Athena, Amazon Redshift, Amazon Neptune and dbt

AWS Big Data

In the context of comprehensive data governance, Amazon DataZone offers organization-wide data lineage visualization using Amazon Web Services (AWS) services, while dbt provides project-level lineage through model analysis and supports cross-project integration between data lakes and warehouses.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

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.

Data Lake 129
article thumbnail

Simplify operational data processing in data lakes using AWS Glue and Apache Hudi

AWS Big Data

A modern data architecture is an evolutionary architecture pattern designed to integrate a data lake, data warehouse, and purpose-built stores with a unified governance model. The company wanted the ability to continue processing operational data in the secondary Region in the rare event of primary Region failure.

Data Lake 109
article thumbnail

Implement disaster recovery with Amazon Redshift

AWS Big Data

With built-in features such as automated snapshots and cross-Region replication, you can enhance your disaster resilience with Amazon Redshift. Amazon Redshift supports two kinds of snapshots: automatic and manual, which can be used to recover data. Snapshots are point-in-time backups of the Redshift data warehouse.

article thumbnail

Exploring real-time streaming for generative AI Applications

AWS Big Data

Furthermore, data events are filtered, enriched, and transformed to a consumable format using a stream processor. The result is made available to the application by querying the latest snapshot. For more details, refer to Create a low-latency source-to-data lake pipeline using Amazon MSK Connect, Apache Flink, and Apache Hudi.

Data Lake 112
article thumbnail

Five actionable steps to GDPR compliance (Right to be forgotten) with Amazon Redshift

AWS Big Data

Tagging Consider tagging your Amazon Redshift resources to quickly identify which clusters and snapshots contain the PII data, the owners, the data retention policy, and so on. Redshift resources, such as namespaces, workgroups, snapshots, and clusters can be tagged. Tags provide metadata about resources at a glance.