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Upstream

The Big Data Blog

Improving Redshift Spectrum's Performance & Costs

May 14, 2020 5:58:23 PM / by Roy Hegdish posted in Database, Data Lake, Data Architecture, Amazon Athena, Streaming Data, ETL, SQL, AWS S3, Apache Parquet, AWS Redshift

 

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Streaming Machine Learning with Upsolver and AWS SageMaker

May 14, 2020 1:38:55 PM / by Roy Hegdish posted in Database, Data Lake, Data Architecture, Amazon Athena, Streaming Data, ETL, SQL, AWS S3, Apache Parquet, AWS Redshift

 

In a previous article, we covered one of the main challenges in machine learning: the need to set up, maintain and orchestrate two separate ETL flows - one for offline processing and creating the training dataset, and one for real-time serving and inference.

 

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What is Apache Parquet and why you should use it

May 6, 2020 2:05:19 PM / by Roy Hegdish posted in Database, Data Lake, Data Architecture, Amazon Athena, Streaming Data, ETL, SQL, AWS S3, Apache Parquet, AWS Redshift

 

 

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Comparing Amazon Athena vs Traditional Databases

May 3, 2020 11:40:05 AM / by Roy Hegdish posted in Database, Data Lake, Data Architecture, Amazon Athena, Streaming Data, ETL, SQL, AWS S3, AWS Redshift

 

 

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How to Work with Streaming Data in AWS Redshift

Apr 16, 2020 11:19:55 AM / by Roy Hegdish posted in Data Lake, Data Architecture, Amazon Athena, Streaming Data, ETL, SQL, AWS S3, AWS Redshift

 

Amazon Redshift remains one of the most popular cloud data warehouses, and is still constantly being updated with new features and capabilities. Over 10,000 companies worldwide use Redshift as part of their AWS deployments (according to a recent press release).

 

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