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.
Based on our record, Dagster should be more popular than Metaplane. It has been mentiond 3 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
Instead of the custom orchestrator I used, a proper orchestration tool should replace it like Apache Airflow, Dagster, ..., etc. - Source: dev.to / 11 days ago
Level 1 of MLOps is when you've put each lifecycle stage and their intefaces in an automated pipeline. The pipeline could be a python or bash script, or it could be a directed acyclic graph run by some orchestration framework like Airflow, dagster or one of the cloud-provider offerings. AI- or data-specific platforms like MLflow, ClearML and dvc also feature pipeline capabilities. - Source: dev.to / about 2 months ago
I would recommend the following: - https://www.mage.ai/ - https://dagster.io/ - https://www.prefect.io/ - https://metaflow.org/ - https://zenml.io/home. Source: about 1 year ago
Telmai - Monitor your customer data quality in real-time
Apache Airflow - Airflow is a platform to programmaticaly author, schedule and monitor data pipelines.
Truth{set} - Measuring the quality of consumer data
Kestra.io - Infinitely scalable, event-driven, language-agnostic orchestration and scheduling platform to manage millions of workflows declaratively in code.
Segment - We make customer data simple.
Prefect.io - Prefect offers modern workflow orchestration tools for building, observing & reacting to data pipelines efficiently.