AWS Big Data Blog

Category: Amazon Athena

How Imperva uses Amazon Athena for machine learning botnets detection

This is a guest post by Ori Nakar, Principal Engineer at Imperva. In their own words, “Imperva is a large cyber security company and an AWS Partner Network (APN) Advanced Technology Partner, who protects web applications and data assets. Imperva protects over 6,200 enterprises worldwide and many of them use Imperva Web Application Firewall (WAF) […]

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New features from Apache Hudi available in Amazon EMR

Apache Hudi is an open-source data management framework used to simplify incremental data processing and data pipeline development by providing record-level insert, update and delete capabilities. This record-level capability is helpful if you’re building your data lakes on Amazon S3 or HDFS. You can use it to comply with data privacy regulations and simplify data […]

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Effective data lakes using AWS Lake Formation, Part 1: Getting started with governed tables

Thousands of customers are building their data lakes on Amazon Simple Storage Service (Amazon S3). You can use AWS Lake Formation to build your data lakes easily—in a matter of days as opposed to months. However, there are still some difficult challenges to address with your data lakes: Supporting streaming updates and deletes in your data […]

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Example Corp program managers can now monitor slack engagement using their QuickSight Dashboard

Create a custom data connector to Slack’s Member Analytics API in Amazon QuickSight with Amazon Athena Federated Query

Amazon QuickSight recently added support for Amazon Athena Federated Query, which allows you to query data in place from various data sources. With this capability, QuickSight can extend support to query additional data sources like Amazon CloudWatch Logs, Amazon DynamoDB, and Amazon DocumentDB (with Mongo DB compatibility) via their existing Amazon Athena data source. You […]

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The following diagram shows the flow of our solution.

Integrating Datadog data with AWS using Amazon AppFlow for intelligent monitoring

Infrastructure and operation teams are often challenged with getting a full view into their IT environments to do monitoring and troubleshooting. New monitoring technologies are needed to provide an integrated view of all components of an IT infrastructure and application system. Datadog provides intelligent application and service monitoring by bringing together data from servers, databases, […]

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The following diagram shows the solution architecture for the Vertica custom connector when deployed to AWS.

Querying a Vertica data source in Amazon Athena using the Athena Federated Query SDK

The ability to query data and perform ad hoc analysis across multiple platforms and data stores with a single tool brings immense value to the big data analytical arena. As organizations build out data lakes with increasing volumes of data, there is a growing need to combine that data with large amounts of data in […]

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In the following tree diagram, we’ve outlined what the bucket path may look like as logs are delivered to your S3 bucket

Automating AWS service logs table creation and querying them with Amazon Athena

I was working with a customer who was just getting started using AWS, and they wanted to understand how to query their AWS service logs that were being delivered to Amazon Simple Storage Service (Amazon S3). I introduced them to Amazon Athena, a serverless, interactive query service that allows you to easily analyze data in […]

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The following diagram shows the architecture EMX uses.

How EMX reduced data pipeline costs by 85% with Amazon Athena

This is a guest blog post by Gary Bouton and Louis Ashner from EMX. In their own words, “ENGINE Media Exchange (EMX) is a leading marketing technology company, leveraging a patented, end-to-end tech stack purpose-built to meet the demands of today’s digital marketplace. The company creates both open- and closed-loop solutions designed to unify advertisers, […]

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Detecting anomalous values by invoking the Amazon Athena machine learning inference function

Amazon Athena has released a new feature that allows you to easily invoke machine learning (ML) models for inference directly from your SQL queries. Inference is the stage in which a trained model is used to infer and predict the testing samples and comprises a similar forward pass as training to predict the values. Unlike […]

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