What is Panoply?
Panoply helps business users sync, store, and access all of their data, without complicated code. Drive insights fast by building a single source of truth for all your reporting needs.
Who Uses Panoply?
Data analysts, engineers, architects & scientists responsible for availability/usability of disparate data. Business users and strategists who need to generate insights
Where can Panoply be deployed?
- Yes, has free trial
- No free version
Panoply does not have a free version but does offer a free trial. Panoply paid version starts at US$499.00/month.
Panoply videos and images
Features of Panoply
- Customer Database
- Data Analysis Tools
- Data Blending
- Data Capture and Transfer
- Data Cleansing
- Data Connectors
- Data Discovery
- Data Integration
- Data Migration
- Data Quality Control
- Data Security
- Data Storage Management
- ETL - Extract Transfer Load
- Match & Merge
- Metadata Management
- Third Party Integrations
Alternatives to Panoply
Reviews of Panoply
Panoply gets the job done!
Comments: The support team behind Panoply is very helpful. We've used the on-site chat function to get immediate help. We've also submitted questions through traditional routes like email. All of which were answered quickly.
The speed to solution is a big win for us. We were able to get a full data pipeline up in running in less than half a day. That's with various data sources and incremental refresh. The UI is easy to use.
There aren't really any cons. The platform is in its infancy and I can tell that the team is listening to user feedback and already making updates.
Reasons for Choosing Panoply: Snowflake was too costly and still required in-depth coding and platform knowledge to quickly spin up a data pipeline.
Switched From: Snowflake
Reasons for Switching to Panoply: The price was perfect and the features met our needs.
Excellent starting option for data warehousing
Comments: Was the foundation of my last company's BI pipeline and served us very well. Now they are going through a painful migration from the old Redshift servers to BigQuery and the cost has tripled. Before I left I was undergoing a migration to BigQuery natively and skipping Panoply as it began to add complexity for us rather than take it away.
Very simple to set up and manage. Still all the core functionality you need in a warehouse
The built in data connectors could be buggy. Particularly Google Analytics with multiple accounts. Integrating with Google Data Studio was also frustrating as we couldn't find a way to share dashboards within our workspace.
Reasons for Switching to Panoply: much more simple to set up and manage. Reliable monthly cost was easier to get buy in from management
Customer service is great until you cancel
Comments: Decent product, overpriced for it's function, the support team and customer service team need to get their act together.
We used Panoply to ingest DynamoDB data and send it to the analytics platform for intellegence. The software worked and functioned fine, our we had a simple use case, but it never failed us.
The pricing was really steep for our simple use case and didn't bring the value that the price tag suggests. Ultimately we found a service that is 40% the cost that suites our needs. When I went to cancel there is no unsubscribe button, I had to hunt for a cancellation email address. After going back and forth with the director of customer service, I finally got it cancelled. However, they threw a 30-day notice clause at us causing us to pay an extra 50 days for a product we are not using. Really bad form in my opinion.
2 years ago
Hi Matt, Thank you for your review. We value feedback from all of our customers. I am glad that you had a good experience with our platform and that our platform allowed you to get some insights. I am sorry about your experience with the cancellation process. While we are disappointed when one of our customers leaves, we aim to make the process as simple as possible by following the terms of the signed contract. One of the terms is our requirement to provide 30 days' notice before the next renewal date. We state this in our terms and conditions but apologize for any misunderstanding, and we will work to make that part of the agreement clearer. We wish you all the best and hope that we can work together in the future.
Helped me immensely with analyzing netcdf data files
Comments: I am working with Geographical data that has latitudes, longitudes and a variable I am trying to analyze. This is a great tool to have for such data structure.
I was introduced to Panoply by a colleague. I was trying to analyze a bunch of climate variables that were in netcdf format. Before I could write a code in Matlab to analyze the data, I needed to know the data structure. For this I have used a combination of F77 and Matlab in the past. However, I wanted to exclude Fortran and have a more convenient way of knowing the basic data structure. Matlab was more powerful with the actual analysis but not with the pre processing. This is where Panoply came in handy. All I had to do was upload the netcdf data file directly into panoply and boom. It gave me the basic structure that includes the number of data points, latitudes and longitudes of the data points and other essential details I needed.
I did not come across any problem in particular for the 2+ years I have used Panoply. Sometimes, It did take a little long to load it if the netcdf file I was working with was a large file but it was not a big deal. Panoply actually was immensely helpful in knowing the data structure of the variable type for which I followed a much more complex procedure in the past before I used Panoply.
Panoply is a great product that helps in WH management as well as optimization.
Query optimization is great and all behind the scenes. Views automatic materialization is great and enable me to create very complicated views without considering runtime. support representatives are very responsive and usually very helpful. In general, very flexible company that always to get better and answers it's clients needs
Web platform can be built better Materialization processes have some problem sometimes (downtime) and are not visible properly on the platform