Based on our record, Apache Airflow should be more popular than Amazon Redshift. It has been mentiond 65 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.
They differ from conventional analytic databases like Snowflake, Redshift, BigQuery, and Oracle in several ways. Conventional databases are batch-oriented, loading data in defined windows like hourly, daily, weekly, and so on. While loading data, conventional databases lock the tables, making the newly loaded data unavailable until the batch load is fully completed. Streaming databases continuously receive new... - Source: dev.to / 3 months ago
Data warehousing is the process of storing and analyzing large volumes of data for business intelligence and analytics purposes. AWS offers a fully managed data warehousing service called Amazon Redshift that can handle petabyte-scale data warehouses with ease. - Source: dev.to / 7 months ago
The topics of databases and data warehouses are central to the modern data landscape, and Amazon's offeringsDynamoDB and Redshiftare standout products in their respective categories. Here's a detailed comparison:. - Source: dev.to / 8 months ago
Amazon Redshift is a powerful, scalable data warehousing service within the AWS ecosystem. It excels in handling large datasets with its columnar storage, parallel query execution, and features like Redshift Spectrum and RA3 instances. Redshift’s clustered architecture, robust security, and integration with AWS services make it a go-to choice for businesses needing efficient and secure data management solutions. - Source: dev.to / 11 months ago
Amazon Redshift (analytics) Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. With Amazon Redshift, you can analyze your data using your existing business intelligence tools. Https://aws.amazon.com/redshift/. - Source: dev.to / over 1 year ago
For the third, examples here might be analytics plugins in specialized databases like Clickhouse, data-transformations in places like your ETL pipeline using Airflow or Fivetran, or special integrations in your authentication workflow with Auth0 hooks and rules. - Source: dev.to / 3 months ago
Apache Airflow is an open-source platform to programmatically author, schedule, and monitor workflows. The platform features a web-based user interface and a command-line interface for managing and triggering workflows. Source: 6 months ago
Airflow is the most widely used and well-known tool for orchestrating data workflows. It allows for efficient pipeline construction, scheduling, and monitoring. - Source: dev.to / 6 months ago
AIRFLOW This is more of a library in my opinion, but Airflow has become an essential tool for scheduling in my work. All our ML training pipelines are ordered and scheduled with Airflow and it works seamlessly. The dashboard provided is also fantastic! Source: 7 months ago
I agree there are many options in this space. Two others to consider: - https://airflow.apache.org/ - https://github.com/spotify/luigi There are also many Kubernetes based options out there. For the specific use case you specified, you might even consider a plain old Makefile and incrond if you expect these all to run on a single host and be triggered by a new file... - Source: Hacker News / 8 months ago
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