Metaplane
Telmai
Truth{set}
Segment
Iteratively
Percival
Masthead Data
Segment Protocols
Astronomer
Kestra.io
Apache Airflow
Dagster
n8n.io
Prefect.io
Make.com
Segment
Data teams are often the last to know about data quality issues, finding out only when downstream data consumers complain about broken dashboards. Metaplane solves this problem by continuously monitoring the entire data stack, alerting teams when something goes wrong, and providing context about what caused the issue.
Metaplane is the only data observability tool that is free to try and can be setup in under 10 minutes. After connecting your warehouse, our test engine automatically adds thousands of tests for row counts, freshness, and statistical properties, all without writing a single line of code.
Using your query history, transformation tool and BI tools, Metaplane can construct lineage across your entire data stack. When an issue is spotted, Metaplane will send you an alert to Slack or email and provide context about what may have caused the issue as well as what could be impacted.
Metaplane AstronomerBased on our record, Astronomer should be more popular than Metaplane. It has been mentiond 4 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.
After evaluating few solutions in the market: We were in the market to hunt for a solution which will cost under 10k (yearly) considering the cost of opensource will be similar considering DE resource and maintenance cost etc 1. MonteCarlo - Super duper expensive - Unable to hosting in Google Cloud 2. BigEye - Good features 3. Metaplane - Overall good package but when compared to catalog and other features it... Source: about 1 year ago
A quick tip for airflow if you don't have a local install (and I heartily recommend a local install - astronomer.io has an easy to set up container). Source: over 1 year ago
Julian LaNeve is an engineer and data scientist who currently works at Astronomer.io as a Product Manager. In his free time, he enjoys playing poker, chess and winning data science competitions. - Source: dev.to / over 1 year ago
Then load up docker, don't need to be a docker expert, just install docker desktop on windows or use linux. Go to astronomer.io and look at how to run airflow (cron++) in docker. Get that working. If you don't know python but do program in some language, you should be able to get up to speed on the basics pretty quickly. If you know python, it will be a breeze. Source: over 2 years ago
Hello guys, I am currently looking for the right orchestration to build a data pipeline composed of long running tasks (python scripts) among which some run in parallel. Although I was firstly hesitating between Apache Airflow and AWS Step functions, it appeared setting Airflow for production might be too complicated without using a way too expensive service meant for that intent( aws managed worflows or... Source: about 3 years ago
Telmai - Monitor your customer data quality in real-time
Kestra.io - Infinitely scalable, event-driven, language-agnostic orchestration and scheduling platform to manage millions of workflows declaratively in code.
Truth{set} - Measuring the quality of consumer data
Apache Airflow - Airflow is a platform to programmaticaly author, schedule and monitor data pipelines.
Segment - We make customer data simple.
Dagster - The cloud-native open source orchestrator for the whole development lifecycle, with integrated lineage and observability, a declarative programming model, and best-in-class testability.
