The Data Management UI for the AWS Data Stack
This is an illustrated introduction to Depoxy's first set of features that are already implemented. If you want to know more about all the planned features, read our other article: Introducing Depoxy.
Data pipeline management is a complex and time-consuming task for data engineers and analysts. Traditional tools are difficult to use, hard to integrate with other systems, and lack the features and functionality needed to optimize data pipelines effectively and easily.
That is the reason we created Depoxy. It addresses these challenges by providing a user-friendly interface and powerful data visualization capabilities. With Depoxy, it is simple to manage, monitor, and optimize your data pipelines, making your work more efficient and effective.
One aspect of working with data pipelines that run SQL queries is that debugging them and running ad-hoc analytics queries on them is time-consuming. With Depoxy, you can get all the relevant context and the error message on the same screen, helping you fix the underlying problem faster.
Even if you're not an experienced SQL developer, you can easily navigate the tool and run your queries with confidence. The clean and intuitive layout of the interface makes it easy to understand the results of your queries, and the built-in error message functionality helps ensure that you can troubleshoot any issues.
One of the key benefits of using Depoxy for your ETL needs is its ability to help you easily manage and organize your ETL jobs. With its intuitive interface, you can quickly search, filter, and sort through your ETL jobs to find the one you are looking for. This makes it simple to keep track of all your ETL jobs, no matter how many you have or how complex they may be.
Additionally, Depoxy offers powerful visualization and reporting capabilities, so you can quickly see the status and performance of your ETL jobs at a glance. This makes it easier to identify potential problems or bottlenecks in your ETL pipelines and take action to resolve them.
Here is the screen showing the jobs in your infra that fail most often:
And here is the one showing the slowest queries:
These are the two charts that I use for identifying what to improve the next time when I have a chance to work on improvements.
When we started Depox, one of the pain points for us and our customers was finding tables in the data infrastructure easily. This is exactly the reason why we created the following screen:
From here, it is super easy to go to the table that you are looking for. The search box uses the client-side data to find the table you are searching for.
Depoxy is a data pipeline management tool that provides a user-friendly interface and powerful data visualization capabilities. With Depoxy, it is simple to manage, monitor, and optimize your data pipelines, making your work more efficient and effective. It offers features such as a screen for easily finding and navigating to tables, a screen for managing and organizing ETL jobs, and also visualization and reporting capabilities for quickly identifying potential problems or bottlenecks in your pipelines.
We just got started, and these are the first features we think are the most useful for our customers. Looking forward to hearing your opinion either on HN or via email (email@example.com).
Thanks for your attention.