Try our new research platform with insights from 80,000+ expert users

Datapipe Cloud Analytics for AWS vs Oracle Big Data Cloud Service comparison

Sponsored
 

Comparison Buyer's Guide

Executive Summary

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Categories and Ranking

IBM Turbonomic
Sponsored
Ranking in Cloud Analytics
1st
Average Rating
8.8
Reviews Sentiment
7.4
Number of Reviews
205
Ranking in other categories
Cloud Migration (5th), Cloud Management (4th), Virtualization Management Tools (2nd), IT Financial Management (1st), IT Operations Analytics (4th), Cloud Cost Management (1st), AIOps (5th)
Datapipe Cloud Analytics fo...
Ranking in Cloud Analytics
9th
Average Rating
8.0
Reviews Sentiment
7.8
Number of Reviews
1
Ranking in other categories
No ranking in other categories
Oracle Big Data Cloud Service
Ranking in Cloud Analytics
5th
Average Rating
7.6
Reviews Sentiment
6.0
Number of Reviews
2
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of February 2025, in the Cloud Analytics category, the mindshare of IBM Turbonomic is 36.8%, down from 43.2% compared to the previous year. The mindshare of Datapipe Cloud Analytics for AWS is 0.9%, up from 0.4% compared to the previous year. The mindshare of Oracle Big Data Cloud Service is 2.8%, up from 1.7% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Cloud Analytics
 

Featured Reviews

Keldric Emery - PeerSpot reviewer
Saves time and costs while reducing performance degradation
It's been a very good solution. The reporting has been very, very valuable as, with a very large environment, it's very hard to get your hands on the environment. Turbonomic does that work for you and really shows you where some of the cost savings can be done. It also helps you with the reporting side. Me being able to see that this machine hasn't been used for a very long time, or seeing that a machine is overused and that it might need more RAM or CPU, et cetera, helps me understand my infrastructure. The cost savings are drastic in the cloud feature in Azure and in AWS. In some of those other areas, I'm able to see what we're using, what we're not using, and how we can change to better fit what we have. It gives us the ability for applications and teams to see the hardware and how it's being used versus how they've been told it's being used. The reporting really helps with that. It shows which application is really using how many resources or the least amount of resources. Some of the gaps between an infrastructure person like myself and an application are filled. It allows us to come to terms by seeing the raw data. This aspect is very important. In the past, it was me saying "I don't think that this application is using that many resources" or "I think this needs more resources." I now have concrete evidence as well as reporting and some different analytics that I can show. It gives me the evidence that I would need to show my application owners proof of what I'm talking about. In terms of the downtime, meantime, and resolution that Turbonomic has been able to show in reports, it has given me an idea of things before things happen. That is important as I would really like to see a machine that needs resources, and get resources to it before we have a problem where we have contention and aspects of that nature. It's been helpful in that regard. Turbonomic has helped us understand where performance risks exist. Turbonomic looks at my environment and at the servers and even at the different hosts and how they're handling traffic and the number of machines that are on them. I can analyze it and it can show me which server or which host needs resources, CPU, or RAM. Even in Azure, in the cloud, I'm able to see which resources are not being used to full capacity and understand where I could scale down some in order to save cost. It is very, very helpful in assessing performance risk by navigating underlying causes and actions. The reason why it's helpful is because if there's a machine that's overrunning the CPU, I can run reports every week to get an idea of machines that would need CPU, RAM, or additional resources. Those resources could be added by Turbonomic - not so much by me - on a scheduled basis. I personally don't have to do it. It actually gives me a little bit of my life back. It helps me to get resources added without me physically having to touch each and every resource myself. Turbonomic has helped to reduce performance degradation in the same way as it's able to see the resources and see what it needs and add them before a problem occurs. It follows the trends. It sees the trends of what's happening and it's able to add or take away those resources. For example, we discuss when we need to do certain disaster recovery tests. Over the years, Turbo will be able to see, for example, around this time of year that certain people ramp up certain resources in an environment, and then it will add the resources as required. Another time of year, it will realize these resources are not being used as much, and it takes those resources away. In this way, it saves money and time while letting us know where we are. We've saved a great deal of time using this product when I consider how I'd have to multiply myself and people like me who would have to add resources to devices or take resources away. We've saved hundreds of hours. Most of the time those hours would have to be after hours as well, which are more valuable to me as that's my personal time. Those saved hours are across months, not years. I would consider the number of resources that Turbonomic is adding and taking away and the placement (if I had to do it all myself) would end up being hundreds of hours monthly that would be added without the help of Turbonomic. It helps us to meet SLAs mainly due to the fact that we're able to keep the servers going and to keep the servers in an environment, to keep them to where (if we need to add resources) we can add them at any given time. It will keep our SLAs where they need to be. If we were to have downtime due to the fact that we had to add resources or take resources away and it was an emergency, then that would prevent us from meeting our SLAs. We also use it to monitor Azure and to monitor our machines in terms of the resources that are out there and the cost involved. In a lot of cases, it does a better job of giving us cost information than Azure itself does. We're able to see the cost per machine. We're able to see the unattached volume and storage that we are paying for. It gives us a great level of insight. Turbonomic gives us the time to be able to focus on innovation and ongoing modernization. Some of the tasks that it does are tasks that I would not necessarily have to do. It's very helpful in that I know that the resources are there where they need to be and it gives me an idea of what changes need to be made or what suggestions it's making. Even if I don't take them, I'm able to get a good idea of some best practices through Turbonomic. One of the ways that Turbonomic does to help bring new resources to market is that we are now able to see the resources (or at least monitor the resources) before they get out to the general public within our environment. We saw immediate value from the product in the test environment. We set it up in a small test environment and we started with just placement and we could tell that the placement was being handled more efficiently than what VMware was doing. There was value for us in placement alone. Then, after we left the placement, we began to look at the resources and there were resources. We immediately began to see a change in the environment. It has made the application and performance better, mainly due to the fact that we are able to give resources and take resources away based on what the need is. Our expenses, definitely, have been in a better place based on the savings that we've been able to make in the cloud and on-prem. Turbonomic has been very helpful in that regard. We've been able to see the savings easily based on the reports in Turbonomic. That, and just seeing the machines that are not being used to capacity allows us to set everything up so it runs a bit more efficiently.
JC
Stable, straightforward to set up and does have good integration with various useful tools
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.
reviewer813444 - PeerSpot reviewer
Easy to set up with good data integration and data virtualization
We developed the solution based on Hadoop, but using Hadoop as a relationship database, it's hard to maintain and recruit developers. There needs to be better integrations with other solutions and there need to be more tools (including virtualization tools) and utilities between this solution and Hadoop. For example, Oracle has a product called Big Data SQL and it built a bridge between Hadoop and Oracle's database to make things easier for developers. The solution needs to be more stable.

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Pros

"Turbonomic can show us if we're not using some of our storage volumes efficiently in AWS. For example, if we've over-provisioned one of our virtual machines to have dedicated IOPs that it doesn't need, Turbonomic will detect that and tell us."
"Using this product helps us to reduce performance risk because it shows us where resources are needed but not yet allocated."
"I like the analytics that help us optimize compatibility. Whereas Azure Advisor tells us what we have to do, Turbonomic has automation which actually does those things. That means we don't have to be present to get them done and simplifies our IT engineers' jobs."
"Turbonomic has helped optimize cloud operations and reduced our cloud costs significantly. Overall, we are at about 40 percent savings, and we spend about three million a year just in Azure. It reduces the size of the VMs, putting them into the right template for usage. People don't realize that you don't have to future-proof a virtual machine in Azure. You just need to build it for today. As the business or service grows, you can scale up or out. About 90 percent of all the costs that we've reduced has been from sizing machines appropriately."
"We have seen a 30% performance improvement overall."
"Rightsizing is valuable. Its recommendations are pretty good."
"The proactive monitoring of all our open enrollment applications has improved our organization. We have used it to size applications that we are moving to the cloud. Therefore, when we move them out there, we have them appropriately sized. We use it for reporting to current application owners, showing them where they are wasting money. There are easy things to find for an application, e.g., they decommissioned the server, but they never took care of the storage. Without a tool like this, that storage would just sit there forever, with us getting billed for it."
"The solution has a good optimization feature."
"The initial setup is pretty straightforward."
"The solution's most valuable aspects are its data integration and data virtualization."
"The solution's most valuable aspect is the fact that it is open source."
 

Cons

"The GUI and policy creation have room for improvement. There should be a better view of some of the numbers that are provided and easier to access. And policy creation should have it easier to identify groups."
"The deployment process is a little tricky. It wasn't hard for me because I have pretty in-depth knowledge of Kubernetes, and their software runs on Kubernetes. To deploy it or upgrade it, you have to be able to follow steps and use the Kubernetes command line, or you'll need someone to come in and do it for you."
"Turbonomic doesn't do storage placement how I would prefer. We use multiple shared storage volumes on VMware, so I don't have one big disk. I have lots of disks that I can place VMs on, and that consumes IOPS from the disk subsystem. We were getting recommendations to provision a new volume."
"Remove the need for special in-house knowledge and development."
"Since the introduction of a HTML 5 based interface, our main - but minor - criticism of a less than intuitive operation managers' GUI would be the area of improvement."
"The old interface was not the clearest UI in some areas, and could be quite intimidating when first using the tool."
"It would be good for Turbonomic, on their side, to integrate with other companies like AppDynamics or SolarWinds or other monitoring softwares. I feel that the actual monitoring of applications, mixed in with their abilities, would help. That would be the case wherever Turbonomic lacks the ability to monitor an application or in cases where applications are so customized that it's not going to be able to handle them. There is monitoring that you can do with scripting that you may not be able to do with Turbonomic."
"The reporting needs to be improved. It's important for us to know and be able to look back on what happened and why certain decisions were made, and we want to use a custom report for this."
"I'd like to see it coordinated or integrated with more of a data catalog."
"We've had some issues with stability."
"The solution needs to improve the functionality of the auto-deduplication."
 

Pricing and Cost Advice

"It was an annual buy-in. You basically purchase it based on your host type stuff. The buy-in was about 20K, and the annual maintenance is about $3,000 a year."
"The pricing and licensing are fair. We purchase based on benchmark pricing, which we have been able to get. There are no surprise charges nor hidden fees."
"IBM Turbonomic is an investment that we believe will deliver positive returns."
"Contact the Turbonomic sales team, explain your needs and what you're looking to monitor. They will get a pre-sales SE on the phone and together work up a very accurate quote."
"The product is fairly priced right now. Given its capabilities, it is excellently priced. We think that the product will become self-funding because we will be able to maximize our resources, which will help us from a capacity perspective. That should save us money in the long run."
"The pricing is in line with the other solutions that we have. It's not a bargain software, nor is it overly expensive."
"You should understand the cost of your physical servers and how much time and money you are spending year over year on expanding your virtual farm."
"I know there have been some issues with the billing, when the numbers were first proposed, as to how much we would save. There was a huge miscommunication on our part. Turbonomic was led to believe that we could optimize our AWS footprint, because we didn't know we couldn't. So, we were promised savings of $750,000. Then, when we came to implement Turbonomic, the developers in AWS said, "Absolutely not. You're not putting that in our environment. We can't scale down anything because they coded it." Our AWS environment is a legacy environment. It has all these old applications, where all the developers who have made it are no longer with the company. Those applications generate a ton of money for us. So, if one breaks, we are really in trouble and they didn't want to have to deal with an environment that was changing and couldn't be supported. That number went from $750,000 to about $450,000. However, that wasn't Turbonomic's fault."
Information not available
Information not available
report
Use our free recommendation engine to learn which Cloud Analytics solutions are best for your needs.
838,713 professionals have used our research since 2012.
 

Top Industries

By visitors reading reviews
Financial Services Firm
15%
Computer Software Company
13%
Manufacturing Company
10%
Insurance Company
7%
No data available
No data available
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
No data available
 

Questions from the Community

What is your experience regarding pricing and costs for Turbonomic?
It offers different scenarios. It provides more capabilities than many other tools available. Typically, its price is...
What needs improvement with Turbonomic?
The implementation could be enhanced.
What is your primary use case for Turbonomic?
We use IBM Turbonomic to automate our cloud operations, including monitoring, consolidating dashboards, and reporting...
Ask a question
Earn 20 points
Ask a question
Earn 20 points
 

Comparisons

No data available
No data available
 

Also Known As

Turbonomic, VMTurbo Operations Manager
No data available
No data available
 

Interactive Demo

Demo not available
Demo not available
 

Overview

 

Sample Customers

IBM, J.B. Hunt, BBC, The Capita Group, SulAmérica, Rabobank, PROS, ThinkON, O.C. Tanner Co.
Citrix, CloudPassage, mongoDB, Datastax
GE Digital, Wiggle, RecVue
Find out what your peers are saying about IBM, Densify, Spot by NetApp and others in Cloud Analytics. Updated: February 2025.
838,713 professionals have used our research since 2012.