Category: Amazon Data Firehose

February 9, 2024: Amazon Kinesis Data Firehose has been renamed to Amazon Data Firehose. Read the AWS What’s New post to learn more. August 30, 2023: Amazon Kinesis Data Analytics has been renamed to Amazon Managed Service for Apache Flink. Read the announcement in the AWS News Blog and learn more. Businesses across the world […]

August 30, 2023: Amazon Kinesis Data Analytics has been renamed to Amazon Managed Service for Apache Flink. Read the announcement in the AWS News Blog and learn more. February 9, 2024: Amazon Kinesis Data Firehose has been renamed to Amazon Data Firehose. Read the AWS What’s New post to learn more. When we look at […]

February 9, 2024: Amazon Kinesis Data Firehose has been renamed to Amazon Data Firehose. Read the AWS What’s New post to learn more. Toyota Motor Corporation (TMC), a global automotive manufacturer, has made “connected cars” a core priority as part of its broader transformation from an auto company to a mobility company. In recent years, […]

With the release of Kinesis Data Firehose HTTP endpoint delivery, you can now stream your data through Amazon Kinesis or directly push data to Kinesis Data Firehose and configure it to deliver data to MongoDB Atlas. You can also configure Kinesis Data Firehose to transform the data before delivering it to its destination. You don’t have to write applications and manage resources to read data and push to MongoDB. It’s all managed by AWS, making it easier to estimate costs for your data based on your data volume. In this post, we discuss how to integrate Kinesis Data Firehose and MongoDB Cloud and demonstrate how to stream data from your source to MongoDB Atlas.

This post shows how to implement Vega visualizations included in Kibana, which is part of Amazon Elasticsearch Service (Amazon ES), using a real-world clickstream data sample. Vega visualizations are an integrated scripting mechanism of Kibana to perform on-the-fly computations on raw data to generate D3.js visualizations. For this post, we use a fully automated setup using AWS CloudFormation to show how to build a customized histogram for a web analytics use case. This example implements an ad hoc map-reduce like aggregation of the underlying data for a histogram.

February 9, 2024: Amazon Kinesis Data Firehose has been renamed to Amazon Data Firehose. Read the AWS What’s New post to learn more. New Relic can now ingest data directly from Amazon Kinesis Data Firehose, expanding the insights New Relic can give you into your cloud stacks so you can deliver more perfect software. Kinesis […]

February 9, 2024: Amazon Kinesis Data Firehose has been renamed to Amazon Data Firehose. Read the AWS What’s New post to learn more. Amazon Kinesis Data Firehose now provides an easy-to-configure and straightforward process for streaming data to a third-party service for analysis, including logs from AWS services. Due to the varying formats and high […]

February 9, 2024: Amazon Kinesis Data Firehose has been renamed to Amazon Data Firehose. Read the AWS What’s New post to learn more. The value of data is time sensitive. Streaming data services can help you move data quickly from data sources to new destinations for downstream processing. For example, Amazon Data Firehose can reliably […]

We parse through millions of scooter and user events generated daily (over 300 events per second) to extract actionable insight. We selected AWS Glue to perform this task. Our primary ETL job reads the newly added raw event data from Amazon S3, processes it using Apache Spark, and writes the results to our Amazon Redshift data warehouse. AWS Glue plays a critical role in our ability to scale on demand. After careful evaluation and testing, we concluded that AWS Glue ETL jobs meet all our needs and free us from procuring and managing infrastructure.