• Architecting a Modern Data Lake with Dipti Borkar from Ahana

  • 2021/11/09
  • 再生時間： 40 分
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Architecting a Modern Data Lake with Dipti Borkar from Ahana

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  • In this episode of Building The Backend we hear from Dipti Borkar cofounder @ Ahana  a managed service for Presto on AWS, where we talk all about the data lake, how it should be structured and where the industry is going.
     
    Below are top 3 value bombs: 

    1. Presto is an open source distributed SQL query engine originally created by Facebook, mainly used to run SQL queries on data lakes but can be connected to relational data stores as well. Ahana is a managed Presto service on AWS with 3x price/performance. 
    2. When optimizing your data lake, it’s normally best to store the data in Parquet or ORC format vs JSON or CSV as they are columnar formats that can have indexes built in. 
    3. Data Lake Houses are continuing to gain popularity by bringing the benefits of your data lake and data warehouse together with the help of tools like  Databricks DeltaLake and Apache HUDI.
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あらすじ・解説

In this episode of Building The Backend we hear from Dipti Borkar cofounder @ Ahana  a managed service for Presto on AWS, where we talk all about the data lake, how it should be structured and where the industry is going.
 
Below are top 3 value bombs: 

  1. Presto is an open source distributed SQL query engine originally created by Facebook, mainly used to run SQL queries on data lakes but can be connected to relational data stores as well. Ahana is a managed Presto service on AWS with 3x price/performance. 
  2. When optimizing your data lake, it’s normally best to store the data in Parquet or ORC format vs JSON or CSV as they are columnar formats that can have indexes built in. 
  3. Data Lake Houses are continuing to gain popularity by bringing the benefits of your data lake and data warehouse together with the help of tools like  Databricks DeltaLake and Apache HUDI.
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