Metaplane
Telmai
Truth{set}
Segment
Iteratively
Percival
Masthead Data
Segment Protocols
Apache Airflow
Microsoft Power Automate
ifttt
Make.com
Pipefy
Pushwoosh
Kissflow
Process Street
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 Apache AirflowBased on our record, Apache Airflow seems to be a lot more popular than Metaplane. While we know about 68 links to Apache Airflow, we've tracked only 1 mention of Metaplane. 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
An integral part of an ML project is data acquisition and data transformation into the required format. This involves creating ETL (extract, transform, load) pipelines and running them periodically. Airflow is an open source platform that helps engineers create and manage complex data pipelines. Furthermore, the support for Python programming language makes it easy for ML teams to adopt Airflow. - Source: dev.to / 22 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
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 / 4 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: 8 months ago
Telmai - Monitor your customer data quality in real-time
Microsoft Power Automate - Microsoft Power Automate is an automation platform that integrates DPA, RPA, and process mining. It lets you automate your organization at scale using low-code and AI.
Truth{set} - Measuring the quality of consumer data
ifttt - IFTTT puts the internet to work for you. Create simple connections between the products you use every day.
Segment - We make customer data simple.
Make.com - Tool for workflow automation (Former Integromat)
