Compare Anomalo and Great Expectations 
- Users report that Anomalo excels in real-time analytics with a score of 9.4, highlighting its ability to provide immediate insights into data quality issues, while Great Expectations, although strong, scores slightly lower at 8.8 in data quality monitoring.
- Reviewers mention that Anomalo's anomaly identification feature is particularly robust, scoring 9.3, which users appreciate for its effectiveness in detecting data irregularities, whereas Great Expectations scores 8.3, indicating it may not be as comprehensive in this area.
- G2 users note that Great Expectations shines in its integration capabilities, scoring 8.6, making it easier to connect with various data sources, while Anomalo's integration score of 7.1 suggests it may have limitations in this aspect.
- Users on G2 highlight that Anomalo offers a single pane view feature with a score of 8.0, which provides a consolidated view of data quality metrics, whereas Great Expectations scores higher at 8.9, indicating a more user-friendly interface for monitoring data quality.
- Reviewers mention that Anomalo's ease of setup is rated at 9.4, making it a favorable choice for teams looking to implement quickly, while Great Expectations, with a score of 9.2, is also easy to set up but may require slightly more time for configuration.
- Users say that Anomalo's quality of support is rated at 9.0, with many reviewers praising the responsiveness and helpfulness of the support team, while Great Expectations, with a score of 8.5, is still considered good but may not match the level of support provided by Anomalo.
- Automated data monitoring
- Simple installation
- Visualizations for reporting and explainability
- 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...
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
Ease of Use and the features that are provided on the platform to handle different challenges associated with data quality.
Not everything is that bad at all to be using the tool except a few processing issues. Git processing and git tagging is rather slow and a tedious process. The dashboard needs a revamp.
- 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...
Ease of Use and the features that are provided on the platform to handle different challenges associated with data quality.
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
Not everything is that bad at all to be using the tool except a few processing issues. Git processing and git tagging is rather slow and a tedious process. The dashboard needs a revamp.
