Easy to use UI, reliable scheduling and great support from the Anomalo team. Review collected by and hosted on G2.com.

It's somewhat limited in what datasources checks are supported on. Review collected by and hosted on G2.com.

Straightforward and quick to implement.

Transparent pricing.

High ROI - the two tiers of monitoring give me a lot of bang for my buck.

The main chunk of IP - their ML-based monitoring Review collected by and hosted on G2.com.

It's very easy to create noise in your monitoring channels Review collected by and hosted on G2.com.

The major factor I loved about the tool is the simplicity of using it. The interface is super easy to use. The tool could be customised as per the usability of it and as per a user. Review collected by and hosted on G2.com.

The tool's option to connect to different teams is a significant drawback. The device cannot control the scanned data, helping decide the table's credibility. Hope it gets resolved. Review collected by and hosted on G2.com.

Slack alerts visualization

Built in checks Review collected by and hosted on G2.com.

Admin page is very not user friendly

Many bugs

Tables are not immediately updated in the system

Team does not respond to feature requests or bug reports

UI is bad Review collected by and hosted on G2.com.

It's easy to set up new tables with automatic checks and for stakeholders to dive into the data. Review collected by and hosted on G2.com.

Some of the automated outlier detection models don't work very well. For example, predicting bounds outside of possible value ranges. Review collected by and hosted on G2.com.

Nice platform with useful features that gives a lot of anomaly detection flexibility Review collected by and hosted on G2.com.

sometimes there are to much features, would be nice to have a guided question to set test rules and validations Review collected by and hosted on G2.com.

- Anomalo provides a solution that we can easily integrate with our data stores (Snowflake, Databricks Delta) and immediately start to configure data quality checks for all the tables that we care about.

- Anomalo in general is very easy to use, yet it is also comprehensive. It allows us to configure almost any key metrics and validation rules in SQL based on what we need to monitor for data quality. It provides integration with Okta, Slack, PagerDuty which are the tech stacks that we use in Opendoor, therefore onboarding Anomalo is quite a smooth experience.

- In addition to the UI, Anomalo also provides a Python SDK which enables a ton of flexibility to integrate Anomalo into building data pipelines and triggering data quality checks on the fly.

- Anomalo's team has been quite responsive to our questions and requests. We have regular office hours to meet with Anomalo's team to discuss questions and so far it has been very helpful every time. Review collected by and hosted on G2.com.

- The way that Anomalo presents the metric results can potentially be improved. One significant inconvenient issue that we observed, is that if there is a table has a lot of "segments", then any metrics graph based on segment is pretty hard to digest because the segments and their metric values are not sorted based on segment names. The segment names are also not searchable because the metric graph is an image.

- Anomalo UI user experience can be further improved. Sometimes these use cases can be hard to find out unless Anomalo's team really understands how the customer is using the solution.

For example, there is currently not a great way to view the history of a single check. The best thing to do is to go to the URL /dashboard/check_runs/<run_id>/runs?sort=-started_at but notice that there is a "<run_id>" in the URL instead of a "<check_id>". This means that the history is showing all the runs for a particular check up to the run_id specified in the URL, and therefore there is not a stable URL to see the history.

- Anomalo doesn't have a solution for data lineage visualization yet. While this is not super critical in my company (other than sometimes we need to know if deleting a table could cause any downstream impact), it can be an important functionality that is needed for other companies. Some companies in the data observability area provides lineage such as Monte Carlo. Review collected by and hosted on G2.com.

Automated anomaly detection makes my life as a data engineering professional way easier, especially managing high-visibility datasets where important failures are not just a matter of the ETL failing, but of the contents of the table changing meaningfully. It's super easy to set up good alerts that detect all kinds of undesired changes or issues in the data. The UI is very intuitive and clear. The reporting/analysis tools are excellent. The triage system is simple but effective. Review collected by and hosted on G2.com.

A lot of features outside of the core anomaly detection piece are under-developed and make the tool less useful than it could/will be. Ideally you could send alerts to more than one slack channel or destinations outside of Slack using just the UI. The API is clumsy (ex. it's very difficult to update just one parameter in the config for a table with an existing config) and not fully documented. Datadog integration is a dealbreaker for some teams. Review collected by and hosted on G2.com.

Anomalo has helped Faire's data organization maintain high-quality data models and pipelines that are key to effective operation. Anomalo diagnoses data quality issues efficiently, providing well-designed automatic alerts integrated into Slack with data visualizations that highlight critical trends and potential errors that require attention. Catching errors that may have otherwise gone unnoticed for days if not weeks has been a major benefit of setting up alerts on tables in our data warehouse. Our cross-functional analytics, product, and engineering partners appreciate and engage with Anomalo's intuitive alerts, which have sparked discussions that have led to better outcomes and resolutions for the data team, our customers, and the larger business. Review collected by and hosted on G2.com.

There are some customization options we would like to have in Anomalo to fine-tune their product to our organization's use cases that are not available just yet, including integration into our engineering DB and additional team-based functionalities. However, the Anomalo team has been supportive and engaged in actioning many of our previous feature requests into fully fledged features, or suggested adaptations that have worked quite well for our organization. Review collected by and hosted on G2.com.

We were able to detect data issues quickly using Anomalo and get the alerts quickly so that we could fix them quickly and move on.

We are using this tool to detect infra issues in data pipelines, data quality issues and even monitoring business KPIs - this is how much we trust this tool! Review collected by and hosted on G2.com.

- Some aspects are not part of the original GUI, so you need to access the Django app to manage them.

- The rollout of new features that impact the env without being able to mark it as a feature flag before it impacts the environment (although the Anomalos team was really there to help and discuss this issue and to find solutions). Review collected by and hosted on G2.com.