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From Hive Tables to Iceberg Tables: Hassle-Free

Cloudera

Depending on the size and usage patterns of the data, several different strategies could be pursued to achieve a successful migration. In this blog, I will describe a few strategies one could undertake for various use cases. You want to let your clients or jobs continue writing the data to the table.

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Use Apache Iceberg in a data lake to support incremental data processing

AWS Big Data

Whenever there is an update to the Iceberg table, a new snapshot of the table is created, and the metadata pointer points to the current table metadata file. At the top of the hierarchy is the metadata file, which stores information about the table’s schema, partition information, and snapshots. all_reviews ): data and metadata.

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Synchronize your Salesforce and Snowflake data to speed up your time to insight with Amazon AppFlow

AWS Big Data

To achieve this, they combine their CRM data with a wealth of information already available in their data warehouse, enterprise systems, or other software as a service (SaaS) applications. One widely used approach is getting the CRM data into your data warehouse and keeping it up to date through frequent data synchronization.

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Enable Multi-AZ deployments for your Amazon Redshift data warehouse

AWS Big Data

Amazon Redshift is a fully managed, petabyte scale cloud data warehouse that enables you to analyze large datasets using standard SQL. Data warehouse workloads are increasingly being used with mission-critical analytics applications that require the highest levels of resilience and availability.

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Migrate Microsoft Azure Synapse Analytics to Amazon Redshift using AWS SCT

AWS Big Data

Amazon Redshift is a fast, fully managed, petabyte-scale data warehouse that provides the flexibility to use provisioned or serverless compute for your analytical workloads. You can get faster insights without spending valuable time managing your data warehouse. Fault tolerance is built in. Choose Create workgroup.

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How OLX Group migrated to Amazon Redshift RA3 for simpler, faster, and more cost-effective analytics

AWS Big Data

We live in a data-producing world, and as companies want to become data driven, there is the need to analyze more and more data. These analyses are often done using data warehouses. Status quo before migration Here at OLX Group, Amazon Redshift has been our choice for data warehouse for over 5 years.

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Enrich your customer data with geospatial insights using Amazon Redshift, AWS Data Exchange, and Amazon QuickSight

AWS Big Data

Load generic address data to Amazon Redshift Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. Redshift Serverless makes it straightforward to run analytics workloads of any size without having to manage data warehouse infrastructure.