Metaplane has been great to work with. The team at Metaplane is stellar, and the product fills a huge gap in the monitoring ecosystem. It has become a critical part of our daily workflow and provides a ton of value.

Metaplane is exactly what we were missing, which is an automated way to monitor the content of data in the data warehouse. I love that we receive alerts as soon as the data in a table gets outside the expected band of values-- whether that means that data is not as fresh as expected, a max or min value is too high or too low, the cardinality of a field has changed, or a table row count has shot up or down. With Metaplane, the data team is able to proactively respond to issues with data before business users notice them (instead of finding out about the issues when business users inform us).

There are very few things that I don't love about Metaplane. We do tend to get a lot of alerts if something happens over the weekend and it is not critical enough to respond to right away, so sometimes there is a lot of redundant alerting built up by Monday morning. However, the Metaplane team is constantly working to improve the tool and add new features, and I know this is something they are working to address!

Metaplane is very easy to connect to your database and integrates with other tools like dbt, looker. It helps us stay ahead of data issues that we otherwise wouldn't detect (for instance: the pipeline runs correctly, but you are missing half the data) and speeds up the investigation when an issue is raised. The support team is always ready to help and every new release brings a great feature.

The ease of use and set up of anomaly detection. It would take a long time to build what metaplane can do in a few clicks. The alerts we get are accurate and have been from the very beginning - if the logic changes, it's very easy to reset the predictions. Metaplane also provides insights into table usage/queries - which is helpful to investigate long running queries, performance issues, most used tables, etc.

I would love to see a better user management in the software.

Very good so far, good for business detection. Good customer support and extremely helpful when taking the suggestion of client regarding features, improvement seriously.

This is great tool introducing AI monitor instead of hard monitor. Then, it would have suggestions instead of binary option like before.

Some feature is missing as well as room for integrate to many more services as other guys in market.

Metaplane leverages AI to predict when something might potentially go wrong. We have improved our data quality and monitoring of all our database objects and jobs and generally enhanced the proactiveness of our analysts and data engineers in spotting problems.

Custom Queries: Metaplane empowers the user to create custom queries in SQL for monitoring our data models.

Hard to tell now because metaplane has been constantly improving the software based on past feedback and now difficult to name something i dislike

For us Metaplane solves: 1) Monitoring ETL pipelines for failures or abnormal data 2) Monitoring modeled data for abnormalities before it gets to a business user 3) A simple and effective way to surface data issues via Slack or the UI. The benefit of using Metaplane is that we avoid failures and mistakes that are costly in terms of our data team's reputation and in terms of clients who are using their data to generate additional revenue and where the cost of inaccurate or missing data is high.

Metaplane is hands down the easiest and most useful data observability tool on the market. We use it to monitor failures and anomalies across all of our clients' data stacks. Most monitoring tools are difficult to set up and can’t differentiate between critical and non-critical failures, which results in notification fatigue. Metaplane is the opposite. Metaplane is quick to configure both from the start and on an ongoing basis. It automatically differentiates between critical and non critical failures, making it an extremely actionable data observability tool. With Metaplane we are able to easily and accurately test our own ETL pipelines and the outputs of our data models and catch errors before business users even know anything is wrong. This helps maintain our reputation as a data engineering org and also saves our clients a ton of time and money, especially when we catch errors related to data integrations that power revenue-generating flows or advertising data where the cost of mistakes is high. 
Metaplane is now a default part of our data stack whenever we add a new client.

We’re really satisfied customers and love the tool.

Metaplane has been great to work with. It has allowed the data engineers and analytics engineers to see issues with tables (based on expected table growth or set limits) and investigate/fix/announce before any end users know there is an issue with warehouse data. Before Metaplane, end users would find issues with data and there was a trust gap unless a data analyst or analytics engineer pulled raw data and verified it. The added lineage allows us to know exactly what is impacted in our business intelligence tool and helps analytics engineers plan out next sets in data modeling.

Metaplane has helped us build trust with end users and improved alerting to data engineers and analytics engineers. It is such a simple plug-in solution compared to the hours/weeks/months it would have taken an engineer to build a fraction of what Metaplane does alerting-wise. Metaplane's lineage functionality is super useful when building out new solutions or needing to alert specific end users about changes coming to their data sources. Metplane has saved my team and me so much time and has helped us grow so much trust with end users.

no reporting around query performance, it is being worked on and if/when Metaplane can get query performance reporting it will be another game changing feature for us and aloow us to tackle slow running queries

Metaplane not only helps our team with data quality monitoring (test failures, alerts, etc) but also with determining cruft in our data model. Receiving alerts about data issues on upstream models is a huge improvement as it helps us triage and solve issues before they reach downstream data users. Metaplane UI is easy to navigate and the Slack integration is key - once you set up your tests, you don't need to spend a lot of time in the app. Additionally, since we don't currently have a failproof process for discussing schema changes within the data and engineering org, Metaplane is crucial in informing us of schema updates that may have a large impact on our downstream models. Metaplane helps us determine user errors when related to data and what models are the most and least used.

I wish Metaplane had a connection with Hightouch (alongside their Looker & other downstream connections) to help with lineage. However, they are actively working on this so I'm excited to utilize it once available! Additionally, aggregated data or metadata would be nice so we could better access data performance over time. Lastly, lineage on production database schema changes lineage would be amazing (not sure if that's possible though...)

Metaplane allows us to have confidence that we'll know when something breaks or negatively impacts our data warehouse or the systems and workflows that depend on it. It also helps us know what impact planned changes in the data warehouse will have, and even helps us plan them in the first place through the combination of their lineage and usage reporting features. Additionally, their schema change monitoring enables us to be alerted to upstream changes that we may not have been informed about Their customer service is also amazing

The ease with which Metaplane is implemented is amazing. Within minutes, one can go from no monitoring on their data warehouse to thorough coverage

Metaplane is still ironing out some elements of the user interface, but they seem to be making extremely rapid (and well directed) progress

Metaplane is a great software, and the people at Metaplane have been wonderful partners in our implementation and ongoing optimization and adoption.

The best part of Metaplane is its ML algorithm for understanding the shape and trends of existing data. This feature saves tremendous time in setting up meaningful alerts and notifications. For example, instead of you trying to manually figure out what the right daily record count is supposed be, Metaplane's algorithm automatically learns what the right count should be.In my experience, this algorithm is right 99% of the time, and on the rare occasions where adjustments need to be made, corrective feedback can be easily given to the algorithm with a few clicks in the UI.

Metaplane is a fast-growing company, and sometimes newly released features are a bit rough around the edges. For example, in one of the alerts I received, the name of the failed data quality test came through as an internal ID of some sort, instead of a human-understandable name of the affected table.Despite annoyance from these blips, they’ve also proven responsive Metaplane is to customer feedback. When I reported the problem with the alert notifications, the issue was fixed almost immediately by the team!

I love how easy it was to set up and just basically point it at our BigQuery and get up and running very easily with our more important datasets and tables. I find it's so easy and takes the pain out of things that we are actually testing a lot lot more and their slack integration is so great it makes it easy to maintain or just disable alerts you might not care about anymore etc.

There can be a little bit of a learning curve to the concepts and approaches and how to get the best out of it. Also ideally i'd love to have all my tests as code in some way so as to avoid lots of clicking around on the UI. So i'd love something like a terraform approach but for our metaplane account, which is something i know they are working on.

Metaplane helps us as a data team understand many different aspects of our warehouse including data freshness, model lineage, and usage of our data sources. It sits silently processing while alerting us of issues before our business stakeholders surface them, helping our team save credibility.

Metaplane helps us in a few key aspects: - understand when there may be a bottleneck with our ETL tools by providing predictive models for not only expected load times but also total records being loaded - visualize data lineage from raw source data to dimensional modeling to bi tools, helping better understand business impacts of modeling changes - surface long-running and expensive queries to allow us to fine-tune usage to provide a better experience for our end users while minimizing cost - provide tracking of new and updated schema inside our warehouse

Metaplane is growing out of its infancy and may not have all of the features an enterprise product may need. Although they are very open to feedback and are very willing to implement features based on customer feedback.

Metaplane helps us identify data issues sooner. We used to only find out we had data issues when users alerted us that reports looked odd or were broken. Sometimes this was days after the actual incident occurred. With Metaplane we usually fix data errors before our stakeholders notice them and before they influence decisions.

Metaplane makes it very easy to be identified when there are issues with your data environment. It uses AI to learn what patterns are typical for your data so that it can notify you of discrepancies without you having to set thresholds for every test.

When you first start using the tool you may get a lot of false alarms as it learns your data and you learn how to fine-tune the controls so that it only alerts you about priority issues.