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Datapipe Cloud Analytics for AWS OverviewUNIXBusinessApplication

What is Datapipe Cloud Analytics for AWS?

Datapipe's cloud analytics solution for AWS environments is an innovative data-mining and intelligence tool that can govern and analyze 100% of your AWS usage across the enterprise.

This intelligence powers you in optimizing your architecture and organization, save costs, run more efficiently, and enhance your security.

Datapipe Cloud Analytics for AWS Customers

Citrix, CloudPassage, mongoDB, Datastax

Datapipe Cloud Analytics for AWS Video

Datapipe Cloud Analytics for AWS Reviews

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Director of IT Customer Service with 5,001-10,000 employees
Real User
Top 5Leaderboard
Stable, straightforward to set up and does have good integration with various useful tools
Pros and Cons
  • "The initial setup is pretty straightforward."
  • "I'd like to see it coordinated or integrated with more of a data catalog."

What is our primary use case?

We're using it to actually build data extractions, to end transformations from different healthcare data sources into a consolidated analytics warehouse.

It's not exactly a data lake, however, in our market, there are dozens of different sources for healthcare data. The analytics we do require a heterogeneous collection of that with the data catalog MOX, et cetera. We're using an ETL for healthcare data as part of the general case.

What is most valuable?

I like that it's integrated. 

I also like that it works well with SageMaker. The nice thing about AWS is it actually works well in combination with some of their other tools like QuickSight and SageMaker. I've found that those workflows to be fairly seamless and easy to coordinate across their products.

The initial setup is pretty straightforward.

The solution is stable.

What needs improvement?

The on-demand pipeline execution is something that we've had some challenges with for on-demand scheduling, however, we have some fairly complex use cases there. That said, we have had some problems getting that to work across a wide variety of use cases. Therefore, depending on the latency and the on-demand nature of it, they could do some improvement there. 

QuickSight is evolving pretty quickly. While I liked it, it integrates with it, it would help if they did more coordinated releases so that those features in their other products are improved and that those are available too.

I'd like to see it coordinated or integrated with more of a data catalog. While there are some features there, the data governance and data cataloging, they touch on that, however, that's an important area of growth. It's becoming more and more important. That's why I would like to see more sophisticated and more complete data cataloging and data governance in that product. I know they're working on that. And of course, sometimes you have to go to half a dozen different AWS products before you get the thing you want. That said, I would like to see more data cataloging, more governance.

For how long have I used the solution?

I've used the solution for two years. 

What do I think about the stability of the solution?

Compared to what we were doing with Talend, I'd have to rate it as pretty stable. It's faster. For both speed and stability, I'd give it a good score there.

What do I think about the scalability of the solution?

I have found it to be scalable. Of course, it is all relative. We have not yet implemented our multi-tenant solutions, which would take it from a couple of terabytes to probably near the petabyte area. That's next April. We're not releasing that for another nine months.

So far, it's proven scalable, as most of the AWS stuff is.

We're in the process of expanding our team. So far, we have five people in-house and two consultants. I've got a couple of teams in India as well. There are probably 15 to 20 people total working on that.

How are customer service and technical support?

I actually would rate technical support as extremely good. Between Amazon and Snowflake, I was quite impressed with the level of service and responsiveness. I thought we'd be a small fish in a big pond. After all, we're not a massive company or something like that, however, we've had excellent support from AWS.

Which solution did I use previously and why did I switch?

We use some stuff from Talend. We started with their open-source stuff and that was slow. We experimented with their commercial option and we actually liked it, however, it was still slow. It was dated and it was less cloud-based than we wanted. They haven't quite upgraded that, especially on their open-source version. 

We explored TIBCO Spotfire, however, it had less ETL functionality than it did data analytics. We looked closely at Looker, yet, once again, they were less of an ETL data pipeline. I did like DB Stitch and Fivetran. If all of you needed was ETL, either of these products would work quite nicely. Still, you couldn't manage real complex pipelines and in a scalable fashion with us.

How was the initial setup?

The initial setup was actually straightforward. However,  we did cheat and have an expert do that.

In terms of deployment and maintenance, it was problematic. We had one guy at first, and it became clear that we were really overloading him. We backed him up now. It's just a two-person setup. I do have some India resources that are available for performance and implementation. I have two half-time resources that get involved, and that lets us do a 24/7 support role. However, I've only got a couple of people working on the whole rollout. That likely will expand.

What about the implementation team?

We did have assistance with the implementation. We had an expert help us out. Jeff:
They were a third party. It's someone that works with us on some other consulting. They had worked with us a couple of times before. We thought we'd bring them in and kind of let him take point and coach as they went. It was pretty seamless.

What was our ROI?

We haven't really seen an ROI. We're doing more with that product, however, probably not saving money. We are just able to do more at a scale that's better. For us, the ROI is hard to quantify.

What's my experience with pricing, setup cost, and licensing?

We bill our clients based on the services that they consume. There are some internal charges for development in our staging and development areas, however, most of what we're doing is we mark up and bill to our clients. That cost varies by month, however, we're spending, $80,000 to $100,000 a year on internal services. However, there are several times that that gets consumed by the clients that we help. We basically manage for them and broker on their behalf.

What other advice do I have?

We do have a business relationship with Amazon. We are partners. We have relations with both Amazon and Google. We used to have one with Azure, with Microsoft, as well. Technically we still do, however, we find we're not using that as much. In any case, we have a partnership with Amazon, especially in the healthcare arena.

The solution is a recent version. It was probably updated in the last six months, and we've upgraded to that.

Our clients tend to rely on us to provide the resources. So, typically what we started out with is implementation and deployment, and support. They end up looking to us to doing additional data flows or analytics, et cetera.

I would advise those considering the solution to hire someone who's handled the implementation before. It's ideal if that person is non-AWS. They will help you. However, it's best to find a consultant that can coach and mentor a team that's done it all at least two or three times before. That's one of the reasons our implementation went more smoothly than I expected, as we brought in some resources that had actually done it before. 

I'd rate the solution at an eight out of ten.

Disclosure: My company has a business relationship with this vendor other than being a customer: Partner
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