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  1. Stackups
  2. Application & Data
  3. Databases
  4. Big Data Tools
  5. Amazon Athena vs Azure HDInsight

Amazon Athena vs Azure HDInsight

OverviewDecisionsComparisonAlternatives

Overview

Amazon Athena
Amazon Athena
Stacks521
Followers840
Votes49
Azure HDInsight
Azure HDInsight
Stacks29
Followers138
Votes0

Amazon Athena vs Azure HDInsight: What are the differences?

What is Amazon Athena? Query S3 Using SQL. Amazon Athena is an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL. Athena is serverless, so there is no infrastructure to manage, and you pay only for the queries that you run.

What is Azure HDInsight? A cloud-based service from Microsoft for big data analytics. It is a cloud-based service from Microsoft for big data analytics that helps organizations process large amounts of streaming or historical data.

Amazon Athena and Azure HDInsight belong to "Big Data Tools" category of the tech stack.

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Advice on Amazon Athena, Azure HDInsight

Pavithra
Pavithra

Mar 12, 2020

Needs adviceonAmazon S3Amazon S3Amazon AthenaAmazon AthenaAmazon RedshiftAmazon Redshift

Hi all,

Currently, we need to ingest the data from Amazon S3 to DB either Amazon Athena or Amazon Redshift. But the problem with the data is, it is in .PSV (pipe separated values) format and the size is also above 200 GB. The query performance of the timeout in Athena/Redshift is not up to the mark, too slow while compared to Google BigQuery. How would I optimize the performance and query result time? Can anyone please help me out?

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Detailed Comparison

Amazon Athena
Amazon Athena
Azure HDInsight
Azure HDInsight

Amazon Athena is an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL. Athena is serverless, so there is no infrastructure to manage, and you pay only for the queries that you run.

It is a cloud-based service from Microsoft for big data analytics that helps organizations process large amounts of streaming or historical data.

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Fully managed; Full-spectrum; Open-source analytics service in the cloud for enterprises
Statistics
Stacks
521
Stacks
29
Followers
840
Followers
138
Votes
49
Votes
0
Pros & Cons
Pros
  • 16
    Use SQL to analyze CSV files
  • 8
    Glue crawlers gives easy Data catalogue
  • 7
    Cheap
  • 6
    Query all my data without running servers 24x7
  • 4
    No data base servers yay
No community feedback yet
Integrations
Amazon S3
Amazon S3
Presto
Presto
IntelliJ IDEA
IntelliJ IDEA
Apache Spark
Apache Spark
Kafka
Kafka
Visual Studio Code
Visual Studio Code
Hadoop
Hadoop
Apache Storm
Apache Storm
HBase
HBase
Apache Hive
Apache Hive
Azure Data Factory
Azure Data Factory
Azure Active Directory
Azure Active Directory

What are some alternatives to Amazon Athena, Azure HDInsight?

Google BigQuery

Google BigQuery

Run super-fast, SQL-like queries against terabytes of data in seconds, using the processing power of Google's infrastructure. Load data with ease. Bulk load your data using Google Cloud Storage or stream it in. Easy access. Access BigQuery by using a browser tool, a command-line tool, or by making calls to the BigQuery REST API with client libraries such as Java, PHP or Python.

Apache Spark

Apache Spark

Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.

Amazon Redshift

Amazon Redshift

It is optimized for data sets ranging from a few hundred gigabytes to a petabyte or more and costs less than $1,000 per terabyte per year, a tenth the cost of most traditional data warehousing solutions.

Qubole

Qubole

Qubole is a cloud based service that makes big data easy for analysts and data engineers.

Presto

Presto

Distributed SQL Query Engine for Big Data

Amazon EMR

Amazon EMR

It is used in a variety of applications, including log analysis, data warehousing, machine learning, financial analysis, scientific simulation, and bioinformatics.

Apache Flink

Apache Flink

Apache Flink is an open source system for fast and versatile data analytics in clusters. Flink supports batch and streaming analytics, in one system. Analytical programs can be written in concise and elegant APIs in Java and Scala.

lakeFS

lakeFS

It is an open-source data version control system for data lakes. It provides a “Git for data” platform enabling you to implement best practices from software engineering on your data lake, including branching and merging, CI/CD, and production-like dev/test environments.

Druid

Druid

Druid is a distributed, column-oriented, real-time analytics data store that is commonly used to power exploratory dashboards in multi-tenant environments. Druid excels as a data warehousing solution for fast aggregate queries on petabyte sized data sets. Druid supports a variety of flexible filters, exact calculations, approximate algorithms, and other useful calculations.

Altiscale

Altiscale

we run Apache Hadoop for you. We not only deploy Hadoop, we monitor, manage, fix, and update it for you. Then we take it a step further: We monitor your jobs, notify you when something’s wrong with them, and can help with tuning.

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