Altair Monarch (formerly Datawatch Monarch, acquired by Altair in December, 2018) works with both relational and multi-structured data including support for a wide range of formats including PDF, XML, HTML, text, spool and ASCII files. The product can access data from invoices, sales reports, balance sheets, customer lists, inventory, logs and more. According to the vendor, the system is easy to use, allowing users to quickly select any data source and automatically convert it into…
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dbt
Score 9.0 out of 10
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dbt is an SQL development environment, developed by Fishtown Analytics, now known as dbt Labs. The vendor states that with dbt, analysts take ownership of the entire analytics engineering workflow, from writing data transformation code to deployment and documentation. dbt Core is distributed under the Apache 2.0 license, and paid Teams and Enterprise editions are available.
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Pricing
Altair Monarch
dbt
Editions & Modules
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Pricing Offerings
Altair Monarch
dbt
Free Trial
Yes
Yes
Free/Freemium Version
Yes
Yes
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
Optional
No setup fee
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Community Pulse
Altair Monarch
dbt
Features
Altair Monarch
dbt
Data Transformations
Comparison of Data Transformations features of Product A and Product B
Altair Monarch
-
Ratings
dbt
9.5
Ratings
15% above category average
Simple transformations
00 Ratings
10.00 Ratings
Complex transformations
00 Ratings
9.00 Ratings
Data Modeling
Comparison of Data Modeling features of Product A and Product B
* Individual seat licenses are very expensive, which is one reason we are moving to CMOD/RMS. But RMS has less functionality than standalone Monarch (now known as "Modeler"). I would like to know what improvements we can expect in RMS, I would also ask, what is the future of the standalone version? * In the past there has been a dearth of user discussion and support in the online community, although this seems to be improving with the new "Datawatch Commmunity" (http://community.datawatch.com).
dbt (Data Build Tool) is best suited for doing the data transformation. dbt is just a transformation tool and it is not suitable for building a data pipeline which requires extraction of data and loading. dbt is well suited for SQL based transformation logic and it is less appropriate when transformation logic requires python.
Setting up visualizations with time series data requires a good understanding of how the software works. I would like it to be more intuitive. Having said that, time series data is inherently complicated and I don't see any obvious ways to make it simpler. But I'm not a software designer myself; they could put more resources into the user experience.
Their video training is really helpful and they have a big library of videos, but the videos get out of date as they come out with new versions. I can imagine that it's difficult to keep all the videos updated, but it would be great if the videos were always using the latest major version of the product.
They need more visualizations. They have a pretty big collection now but it seems like there is often some other way to present and visually analyze data that would be a better/tighter fit with requirements than the visualizations available in the standard product. I understand it is possible to add more visualizations - custom visualizations - but that's beyond my expertise.
Slow load times of the dbt cloud environment (they're working on it via a new UI though)
More out-of-the-box solutions for managing procedures, functions, etc would be nice to have, but honestly, it's pretty easy to figure out how to adapt dbt macros
Datawatch recently repositioned Data Pump and essentially priced us out of the market. The initial investment was very inexpensive, but the yearly maintenance contract was viewed as being a little pricey. The only value of the contract was that it included software upgrades. The Professional Services portion of the contract that was meant to provide support was not viewed as being very effective or beneficial.
dbt is very easy to use. Basically if you can write SQL, you will be able to use dbt to get what you need done. Of course more advanced users with more technical skills can do more things.
Datawatch is very good value of money compared to QlikView; QlikView is really more of a BI tool and has a lot of functions that I didn't need. Datawatch is very strong in the real-time area where Tableau, Panorama, and Qlik don't do very well. If you need to set up a visual monitoring dashboard, Datawatch is the best product I've seen for that. if you want to do a lot of in depth statistical analysis of large databases, Tableau is probably a good option.
Matillion is graphical versus dbt, which is SQL code-based (that, of course, is a matter of personal preference and not an objective advantage). The integrated testing, documentation generation, lineage, etc., were additional criteria that led us to choose dbt.