Amazon Athena & Tableau – Serverless Interactive Query Service and Business Intelligence (BI)

Amazon Athena is used to easily analyze data using standard SQL in S3. It can process both structured and semi-structured data in different file formats such as CSV, JSON, Parquet, and ORC. It can be used to generate reports in connection with BI tools. It has a very high query performance even for huge datasets and complex queries.

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Amazon Athena & Tableau – Serverless Interactive Query Service and Business Intelligence (BI)

Apache Drill vs Amazon Athena – A Comparison on Data Partitioning

Big data exploration in almost all fields has led to the development of multiple big data technologies for accessing, exploring, and reporting huge volume of data. Amazon Athena, a serverless, interactive query service, is used to easily analyze big data using standard SQL in Amazon S3. Apache Drill, a schema-free, low-latency SQL query engine, enables self-service data exploration on big data. Let us compare data partitioning in Apache Drill & AWS Athena and the distinct features of both.

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Apache Drill vs Amazon Athena – A Comparison on Data Partitioning

Data Analysis Using Apache Hive and Apache Pig

Apache Hive, an open-source data warehouse system, is used with Apache Pig for loading and transforming unstructured, structured, or semi-structured data for data analysis and getting better business insights. Pig, a standard ETL scripting language, is used to export and import data into Apache Hive and to process large number of datasets.

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Data Analysis Using Apache Hive and Apache Pig

Amazon Athena & Tableau – Serverless Interactive Query Service and Business Intelligence (BI)

Amazon Athena is used to easily analyze data using standard SQL in S3. It can process both structured and semi-structured data in different file formats such as CSV, JSON, Parquet, and ORC. It can be used to generate reports in connection with BI tools. It has a very high query performance even for huge datasets and complex queries.

read more

Amazon Athena & Tableau – Serverless Interactive Query Service and Business Intelligence (BI)

Amazon Athena & Tableau – Serverless Interactive Query Service and Business Intelligence (BI)

Amazon Athena & Tableau – Serverless Interactive Query Service and Business Intelligence (BI)

Amazon Athena is used to easily analyze data using standard SQL in S3. It can process both structured and semi-structured data in different file formats such as CSV, JSON, Parquet, and ORC. It can be used to generate reports in connection with BI tools. It has a very high query performance even for huge datasets and complex queries.

Apache Drill vs Amazon Athena – A Comparison on Data Partitioning

Big data exploration in almost all fields has led to the development of multiple big data technologies for accessing, exploring, and reporting huge volume of data. Amazon Athena, a serverless, interactive query service, is used to easily analyze big data using standard SQL in Amazon S3. Apache Drill, a schema-free, low-latency SQL query engine, enables self-service data exploration on big data. Let us compare data partitioning in Apache Drill & AWS Athena and the distinct features of both.

read more

Apache Drill vs Amazon Athena – A Comparison on Data Partitioning

Apache Drill vs Amazon Athena – A Comparison on Data Partitioning

Apache Drill vs Amazon Athena – A Comparison on Data Partitioning

Big data exploration in almost all fields has led to the development of multiple big data technologies for accessing, exploring, and reporting huge volume of data. Amazon Athena, a serverless, interactive query service, is used to easily analyze big data using standard SQL in Amazon S3. Apache Drill, a schema-free, low-latency SQL query engine, enables self-service data exploration on big data. Let us compare data partitioning in Apache Drill & AWS Athena and the distinct features of both.

Data Analysis Using Apache Hive and Apache Pig

Apache Hive, an open-source data warehouse system, is used with Apache Pig for loading and transforming unstructured, structured, or semi-structured data for data analysis and getting better business insights. Pig, a standard ETL scripting language, is used to export and import data into Apache Hive and to process large number of datasets.

read more

Data Analysis Using Apache Hive and Apache Pig