Amazon Kinesis Firehose VS Google BigQuery
Compare Amazon Kinesis Firehose VS Google BigQuery and see what are their differences
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Amazon Kinesis Firehose
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Amazon Kinesis Firehose Google BigQueryBased on our record, Google BigQuery should be more popular than Amazon Kinesis Firehose. It has been mentiond 35 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
First, you may not know the Kinesis Data Firehose service. Here's the AWS definition: Amazon Kinesis Data Firehose is an Extract, Transform, and Load (ETL) service that captures, transforms, and reliably delivers streaming data to data lakes, data stores, and analytics services. (https://aws.amazon.com/kinesis/data-firehose/). - Source: dev.to / about 1 year ago
As you can see in the diagram, we are feeding all events from Event Bus via a catch-all rule into Kinesis Data Firehose. Firehose is a fully managed service that streams into specific destinations like Data Warehouses or Data Lakes. Unlike it's bigger brother of using Kinesis Data Streams directly, there are no setting up of shards and it's mostly configuration free. We are only defining a buffer interval which is... - Source: dev.to / over 1 year ago
When using EventBridge I always log all events to an S3 bucket for auditing, analytics and debugging purposes. A super easy method to do this is to create a Kinesis Data Firehose stream and create a rule that captures all events that points to the Firehose stream. The Firehose stream can then flush the events on S3 in an interval/size of choice based on configuration. - Source: dev.to / over 1 year ago
Have you looked at Kinesis Firehose? It was pretty much build for this use case although you will still need to see if you can define a partitioning scheme probably in combination with an S3 Select query to meet your query requirements. https://aws.amazon.com/kinesis/data-firehose/?nc=sn&loc=0. - Source: Hacker News / almost 2 years ago
Is continuous backup important ? e.g. If the stuff fails for one day and you lose that day's upload is that ok? Do you want it to push updates more frequently than once a day? If you want to continuously push updates then Kinesis Firehose might be worth looking into. Source: over 2 years ago
Using the Galaxy UI, knowledge workers can systematically review the best results from all configured services including Apache Solr, ChatGPT, Elastic, OpenSearch, PostgreSQL, Google BigQuery, plus generic HTTP/GET/POST with configurations for premium services like Google's Programmable Search Engine, Miro and Northern Light Research. - Source: dev.to / 8 months ago
Data Transformations: This phase involves modifying and integrating tables to generate new tables optimized for analytical use. Consider this example: you want to understand the purchasing behavior of customers aged between 20-30 in your online shop. This means you'll need to join product, customer, and transaction data to create a unified table for analytics. These data preparation tasks (e.g., joining... - Source: dev.to / 8 months ago
Introduction In today's data-driven world, transforming raw data into valuable insights is crucial. This process, however, often involves complex tasks that demand efficiency, scalability, and reliability. Enter dbt Cloud—a powerful tool that simplifies data transformations on Google BigQuery. In this article, we'll take you through a step-by-step guide on how to run BigQuery transformations using dbt Cloud.... - Source: dev.to / 9 months ago
You'll want to evaluate what BigQuery has to offer and see if it makes sense for you to move over. Source: 10 months ago
Watch the introductory videos on BigQuery on the Google Cloud Platform website (https://cloud.google.com/bigquery). Source: 11 months ago
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