Alation vs Amazon Athena

Overview

Amazon Athena

Stacks519

Followers840

Votes49

Alation

Stacks14

Followers26

Votes0

Alation vs Amazon Athena: What are the differences?

Introduction

In this comparison, we will highlight the key differences between Alation and Amazon Athena for better understanding of their capabilities.

Data Sources Supported: Alation primarily focuses on cataloging and organizing various data sources within an organization, providing a comprehensive view for data analysts and data stewards. On the other hand, Amazon Athena is a query service that allows you to analyze data stored in Amazon S3 using standard SQL queries.
Deployment Model: Alation is typically deployed on-premises or in a private cloud environment, providing more control over data governance and security policies. In contrast, Amazon Athena is a fully managed service provided by AWS, eliminating the need for infrastructure management.
Usage of Metadata: Alation excels in metadata management, offering features such as data lineage, impact analysis, and data quality insights to improve data governance and decision-making processes. Amazon Athena, while offering some metadata capabilities, primarily focuses on query processing and analysis of data in Amazon S3.
Integration with Other Tools: Alation is designed to integrate seamlessly with various data analytics tools, data visualization platforms, and data preparation tools, facilitating a unified data ecosystem for users. Amazon Athena is commonly used in conjunction with other AWS services like Amazon Redshift, Amazon EMR, and AWS Glue for broader data processing and analytics needs.
Cost Structure: Alation's pricing model is based on the number of users, data sources, and specific features required, offering flexibility for organizations of different sizes. Amazon Athena follows a pay-per-query pricing structure, where you only pay for the queries you run, making it cost-effective for sporadic or unpredictable query workloads.
Data Processing Capabilities: Alation focuses more on data cataloging and collaboration, offering a central repository for users to discover, understand, and trust data assets. Amazon Athena, being a serverless query service, is optimized for ad-hoc querying and processing large datasets efficiently on Amazon S3.

In Summary, Alation emphasizes data cataloging and metadata management with on-premises deployment options, while Amazon Athena is a fully managed query service optimized for analyzing data stored in Amazon S3 with a pay-per-query pricing model.

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Advice on Amazon Athena, Alation

Pavithra

Mar 12, 2020

Needs adviceon

Amazon S3

Amazon Athena

Amazon 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	Alation
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.	The leader in collaborative data cataloging, it empowers analysts & information stewards to search, query & collaborate for fast and accurate insights.
-	Data Catalog; Automatically indexes your data by source; Automatically gathers knowledge about your data
Statistics
Stacks 519	Stacks 14
Followers 840	Followers 26
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 Presto	No integrations available

What are some alternatives to Amazon Athena, Alation?

Segment

Segment is a single hub for customer data. Collect your data in one place, then send it to more than 100 third-party tools, internal systems, or Amazon Redshift with the flip of a switch.

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.

Presto

Distributed SQL Query Engine for Big Data

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

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 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.

Apache Kylin

Apache Kylin™ is an open source Distributed Analytics Engine designed to provide SQL interface and multi-dimensional analysis (OLAP) on Hadoop/Spark supporting extremely large datasets, originally contributed from eBay Inc.

Splunk

It provides the leading platform for Operational Intelligence. Customers use it to search, monitor, analyze and visualize machine data.

Apache Impala

Impala is a modern, open source, MPP SQL query engine for Apache Hadoop. Impala is shipped by Cloudera, MapR, and Amazon. With Impala, you can query data, whether stored in HDFS or Apache HBase – including SELECT, JOIN, and aggregate functions – in real time.

Vertica

It provides a best-in-class, unified analytics platform that will forever be independent from underlying infrastructure.

Related Comparisons

Alation vs Amazon Athena: What are the differences?

Introduction

In this comparison, we will highlight the key differences between Alation and Amazon Athena for better understanding of their capabilities.

Data Sources Supported: Alation primarily focuses on cataloging and organizing various data sources within an organization, providing a comprehensive view for data analysts and data stewards. On the other hand, Amazon Athena is a query service that allows you to analyze data stored in Amazon S3 using standard SQL queries.
Deployment Model: Alation is typically deployed on-premises or in a private cloud environment, providing more control over data governance and security policies. In contrast, Amazon Athena is a fully managed service provided by AWS, eliminating the need for infrastructure management.
Usage of Metadata: Alation excels in metadata management, offering features such as data lineage, impact analysis, and data quality insights to improve data governance and decision-making processes. Amazon Athena, while offering some metadata capabilities, primarily focuses on query processing and analysis of data in Amazon S3.
Integration with Other Tools: Alation is designed to integrate seamlessly with various data analytics tools, data visualization platforms, and data preparation tools, facilitating a unified data ecosystem for users. Amazon Athena is commonly used in conjunction with other AWS services like Amazon Redshift, Amazon EMR, and AWS Glue for broader data processing and analytics needs.
Cost Structure: Alation's pricing model is based on the number of users, data sources, and specific features required, offering flexibility for organizations of different sizes. Amazon Athena follows a pay-per-query pricing structure, where you only pay for the queries you run, making it cost-effective for sporadic or unpredictable query workloads.
Data Processing Capabilities: Alation focuses more on data cataloging and collaboration, offering a central repository for users to discover, understand, and trust data assets. Amazon Athena, being a serverless query service, is optimized for ad-hoc querying and processing large datasets efficiently on Amazon S3.

Alation vs Amazon Athena

Overview

Alation vs Amazon Athena: What are the differences?