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Andrew McLaren
Principal Consultant at DXC
Consultant
Top 5
Self-patching means I generally don't need a DBA; detailed analytics make it very capable
Pros and Cons
  • "Self-patching and runs machine-learning across its logs all the time"
  • "Ease of connectivity could be improved."

What is our primary use case?

Oracle Autonomous is a self-repairing version or cloud-based version of the Oracle Database. I typically use the new Data Warehouse capacity so I'll use it if I'm building anything connected to finance, HR, plus any of the standard business products. We also use it for other Oracle products if they're cloud-based; such as with ACM and all their other ERP tools, where the data resides on ADW. We're a consultancy so we partner with Oracle as well as other companies. I'm the principal consultant of the company. 

What is most valuable?

I like the fact that the solution is self-patching, that it's running machine-learning generally across its logs all the time in order to identify any issues and to self-repair. It means that I don't really need a DBA for the most part. I can do everything myself.

The product is also smart enough that it doesn't need me to set indexes because it's in the memory log so I don't have to specify them, it will actually learn and build the ones that are necessary.

I'm reasonably happy with what they're packaging. Because they've got the cloud offering, there's a lot of things that aren't part of ADW, yet interact with ADW. Purely as a database, it does what it needs to do. And then I've got the detailed analytics and machine learning, so I'm happy with that. It's a capable product. 

What needs improvement?

Ease of interconnectivity could be improved by which I mean setting up the VPN access and the like from on-premises to cloud. If that was a little easier, it would certainly make my life easier.

For how long have I used the solution?

I've been using Oracle databases since 2011 and Oracle Autonomous for the last two and a half years. 

What do I think about the stability of the solution?

This is a stable solution, I haven't had any issues. 

What do I think about the scalability of the solution?

This is an easy solution to scale, it's just a matter of changing parameters, and it will restart itself, although in the latest update the restart might not be required anymore. 

How are customer service and technical support?

I've had contact with technical support many times. Normally I fill out a service request and they have a set of processes that they run. And even if you understand those and give them all of the information they require before they ask for it, I find they're still likely to delay the process to give themselves time. They will move the bug fix or the investigation up to a higher level of technical skill if required.

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

Other solutions I use are the standard on-premise Oracle Database and Microsoft SQL. Obviously we do a lot of web development, but I use MySQL for that. The product I use at any one time depends on the client. As a consultant, I work with whatever technology is required, but typically it's on an Oracle setup.

How was the initial setup?

The initial setup is extremely simple. If you know in advance what you intend to set up, it takes less than five minutes before you're actually running or creating tables and placing data. It's very quick. We do the setup ourselves, specify capacity, username, password and then it should be up and running in a matter of minutes. 

It doesn't require any maintenance on our part, that's all controlled by Oracle. The patching is done automatically, typically with zero outage and there's no performance tuning really, because it does the majority of it itself. Internally, we'd have a couple of hundred people dealing with the product at any one time. 

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

Licensing costs are typically arranged by Oracle CPU. You pay for the access and then you can scale. If you have a fairly intensive database activity, you'd scale up by CPU, and you're paying by the CPU and the uptime. So there's a marginal uptime cost. If your operations are only running 12 hours a day, you can put your database offline after that and reduce costs. If you had multiple databases supporting the same environment, let's say a development, a test, and a production, you could just turn off the development and the test when you're not fixing anything or developing, and that would reduce your costs. There is also a free version of ADW that can be accessed if you create a cloud account. I think it allows for 20MB of space that is free. 

What other advice do I have?

It's worth looking at what Oracle has available because their ETL tool, for example, which is called ODI, Oracle Data Integration, is free if the target of the platform is Oracle ADW. So you can build an entire ETL or ODI process on a very capable tool and not have to pay for that tool if the target is an ADW database.

I would rate this solution a nine out of 10. 

Which deployment model are you using for this solution?

Private Cloud

If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?

Other
Disclosure: My company has a business relationship with this vendor other than being a customer: Partner
Mauricio Ruiz Falcón
Senior Information Management Architect at Raken
Real User
Top 20
I like how quickly the solution can be implemented
Pros and Cons
  • "The features that I have found most valuable are the ease of use, the rapidness, how quickly the solution can be implemented, and of course that it's been very easy to move from the on-premise world to the Cloud world because Snowflake is based on SQL also."
  • "It would benefit from an administration that allows you to be aware of your credit consumption once you have the service so that you may be sure how many credits you are consuming when you use the platform and to make sure that you are making the most efficient use of these resources. In other words, to improve their interface so that you may monitor the consumption of your credits on Cloud."

What is our primary use case?

We are a consulting company so our primary use depends on the niche that we are providing the services to and on which of the different versions they have. I think we are mainly using Snowflake Enterprise.

In general, it is being used for integrating information. Snowflake is a database platform, it gives information to support analytic needs, such as advanced data analytics like machine learning. In some of those cases it is also used for descriptive analytics, for instance BI.

How has it helped my organization?

One of example of how Snowflake has improved a client's organization is the democratization, it makes information available to more of the users.

What is most valuable?

The features that I have found most valuable are the ease of use, the rapidness, how quickly the solution can be implemented, and of course that it's been very easy to move from the on-premise world to the Cloud world because Snowflake is based on SQL also.

What needs improvement?

I think that the area of improvement with Snowflake is to improve the administration. It would benefit from an administration that allows you to be aware of your credit consumption once you have the service so that you may be sure how many credits you are consuming when you use the platform and to make sure that you are making the most efficient use of these resources. In other words, to improve their interface so that you may monitor the consumption of your credits on Cloud.

I also heard from a company we work for that it could be more user-friendly because it provides some tools but they are not user-friendly.

Additionally, it would be very helpful if Snowflake integrated machine learning and some other advanced analytics features within their language or product capabilities. Right now, they do it through some other company where you have to buy these capabilities from other vendors. There are some customers that don't have complex needs for machine learning or advanced analytics so they don't have to buy it from another vendor but can use it from the product itself if they have it.

For how long have I used the solution?

The whole company has been using Snowflake for about three years.

What do I think about the stability of the solution?

In terms of stability, so far it is very stable.

What do I think about the scalability of the solution?

Snowflake is very scalable. Our client companies where we implement Snowflake are medium to large sized. These companies have offices in different parts of the world, not just some regions, but companies with office users in different parts of the world. We are dealing with international companies. Their tendency is to increase the use of the Snowflake platform. It would serve all the analytical needs in these companies.

How are customer service and technical support?

I have not directly experienced the technical support. It's not part of my job to be involved on those kind of issues, but we constantly receive information as a partner from them and we are very in good touch with them and with the people we are working with, meaning the representatives that are within the Latin American market, which is where I work. They are very open and very fast with communication.

How was the initial setup?

The initial setup is easy. Full deployment takes a few weeks. The initial deployment for the first initiatives might take weeks. It's not complex, really. You may have it loaded after a full day and already providing results or interacting, but there are some other companies that have to be implemented to extract and consume the information from the database. But it's very easy.

Which other solutions did I evaluate?

There have been a couple of other solutions that we've been participating in the evaluation process of and some others that have been included in the decision process, including Redshift from AWS and also Azure Synapse from Microsoft.

For instance, AWS Redshift looked like it was easier to implement and to be adopted by the technical users, the programmers and database programmers. So far it has been far easier to adapt this technology. I'm not saying that AWS is a better technology. It's very complex, but at least what I've seen is that for them, it looks like it's been easier to use the first time.

We liked that Snowflake is able to be used as a multi-Cloud service - it can be used in AWS Cloud, Azure Cloud, or Google Cloud. Whereas AWS, or even Synapse, can only be used in their corresponding networks.

What other advice do I have?

I would definitely recommend Snowflake.

On a scale of one to ten, I would give Snowflake an eight.

I give it an eight out of 10 due to its room for improvement in the user interface for the monitoring of the credit consumption and that the user experience is not friendly. And also because the machine learning is lacking some advanced analytic features.

Which deployment model are you using for this solution?

Private Cloud
Disclosure: My company has a business relationship with this vendor other than being a customer: partner
Lead Security Architect at a comms service provider with 1,001-5,000 employees
Real User
Top 5
Good security, excellent online resources and easy to set up
Pros and Cons
  • "The solution has many features that are applicable to events such as audits."
  • "The solution could make improvements around orchestration and doing some automation stuff on AWS front automation. It would be useful if we could use automation to build images and use hardened images which are CIS compliant."

What is our primary use case?

We primarily use the solution as a cloud data warehouse.

What is most valuable?

The security of the solution is pretty good.

The solution has many features that are applicable to events such as audits.

The solution offers a lot of documentation online that users can use to help with troubleshooting or learning the systems. We rely on these materials when we need support.

What needs improvement?

The solution could make improvements around orchestration and doing some automation stuff on AWS front automation. It would be useful if we could use automation to build images and use hardened images which are CIS compliant. 

For AWS, currently, we are facing the challenge when previewing. On AWS, we have set up a scanner instance with a Nexus scanner. For some reason, the scanner instance has been set up on AWS so that if it's in one region or maybe if it is deployed on one subnet, the other subnet is not reachable within the same region. The scanner is not reachable to the different subnets. For example, if there is a subnet A where the scanner is deployed, and if we want to scan the subnet B within the same region, the scanner is not reachable due to the fact that it's in Subnet A. That's a problem we are currently facing and trying to troubleshoot that.

For how long have I used the solution?

I've been using the solution for about three years at this point.

What do I think about the stability of the solution?

The solution is very stable. We haven't experienced issues such as bugs or glitches. AWS if very good, performance-wise. It doesn't crash or freeze.

What do I think about the scalability of the solution?

I don't really have any insights into scaling the solution. It's not my area of expertise. I haven't attempted to scale yet, so I can't speak to its capabilities.

We have different project teams using the solution across the organization curently.

How are customer service and technical support?

We've never dealt with technical support just yet. If there is a need, we might reach out. However, I can't speak to their level of service as we've never used them yet.

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

Each team in our organization has the option to work with whatever solution they like. Others might use Azure, for example. We, right now, use AWS which we find to be more agile and scalable.

Whichever solution a team chooses wold be based on their own unique requirements.

How was the initial setup?

I wouldn't describe the initial setup as complex. It's pretty straightforward.

For deployment, you basically just download it and start working. It's easy.

We didn't really have a deployment strategy in place. We are at the start of all of this automation stuff. Right now, different project teams are using the cloud. It's new for them as well. We are trying to see how best we can try to get these images, hardened images, deployed in an automated fashion.

There is a dedicated team that handles maintenance on the product. Every product team is responsible for their own setup plan (subscription), and they maintain it. Maintenence might be five or ten people per 1,000 users. It depends on the team size. Eveyone is scattered all across the globe. It's pretty difficult to say which team is handling maintenance and how many are responsible for it as different teams are independantly using the solution. 

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

I'm not privvy to licesning information. I'm not sure how much the solution costs.

What other advice do I have?

Our company does not have a business relationship with AWS. We're just a customer.

I'm not sure which version of the solution we're using.

The thing is that we are not forcing the end-user or the project team to deploy the application. They have the liberty to choose their own platform. Either they can go with AWS or they can go with Azure. Most of the projects which are deployed on non-Windows OS tend to go for AWS.

My area of expertise is more in the auditing of the security standards and maintaining the security requirements as per the industry standard. I'm more in a security architect kind of role.

Every solution has its pros and cons, however, for our purposes, this solution works quite well for us.

I'd rate it overall at eight out of ten.

Which deployment model are you using for this solution?

Public Cloud

If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?

Amazon Web Services (AWS)
Disclosure: I am a real user, and this review is based on my own experience and opinions.
Sarfraz Nawaz
Chief Executive Officer at Ampcome
Real User
Top 20
Scales according to our needs, which saves a lot in terms of upfront costs
Pros and Cons
  • "The most valuable feature is the scalability, as it grows according to our needs."
  • "The OLAP slide and dice features need to be improved."

What is our primary use case?

We are a digital transformation services company, and we are using Amazon Redshift for one of our clients. They are a logistics company that has transportation and other needs.

Their first requirement is for financial reporting, where we pull financial data from their many ERP systems and can provide a corporate-level view.

There is also an operations standpoint, where they are looking for operational insights. For this, we again pull different information from their ERPs, bring it into Redshift, and then model it in such a way that they will be able to see a consolidated view in terms of operational success across lines of business.

How has it helped my organization?

I've been working with data warehouses for a long time and it has always been the case that we had to invest quite a bit on infrastructure, upfront. We are used to dealing with Teradata, and the cost of setting up the data center and getting the appropriate licenses was a big deal. Now, we are able to spin up some clusters and then start using it, allowing us to incrementally pay as we expand.

This has become a big shift in how we spend because there is no capital cost upfront. Moreover, this works with startups as well as with enterprise, and they provide an equal footing. This means that even the advanced capabilities and insights that are available with a data warehouse are no longer limited to the larger clients. Even a startup can use these features, immediately.

What is most valuable?

The most valuable feature is the scalability, as it grows according to our needs.

The part that I like best is that you only pay for what you are using.

What needs improvement?

The OLAP slide and dice features need to be improved. For example, if a business wants to bring in a general ledger from an ERP, they want to slice and dice the data. What we have found is that they have a lot of formulas that are used to calculate metrics, so what we do is use SQL Server Analysis Services. The question then becomes one of adopting a single vendor and transitioning to Azure. If Redshift had similar capabilities then it would be very good.

For how long have I used the solution?

We have been using Amazon Redshift for about five years.

What do I think about the stability of the solution?

The stability is awesome. We have been using it for quite a while and haven't faced any issues.

What do I think about the scalability of the solution?

The scalability is very good. You can start at a very low scale and just keep expanding as required. It is the type of product that fits organizations of all sizes.

How are customer service and technical support?

We have contacted support on several occasions. With our most recent customer, they are pretty large and we were directly in touch with the regional account manager, who is the head of database analytics for India. This person was directly involved in our calls and helped with the evaluation, so the support has been pretty good.

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

We have worked with Teradata and more recently, have been working with Azure SQL Warehouse. Teradata is an on-premises solution and the upfront costs are high. Comparing Azure SQL Warehouse and Amazon Redshift, in terms of features I think that they are pretty much on par.

The SQL Data Warehouse does have better OLAP capabilities, and they also offer a level of serverless capability where they have split the compute and the storage. This means that they can operate at a lower cost in the development environment.

Many of our clients have begun to adopt Power BI, and once they start using it, they tend to lean towards Azure and the Azure SQL Data Warehouse. The fact that Power BI is free, makes quite an impact.

How was the initial setup?

The initial setup is straightforward, once you get used to it. There is a lot of documentation available.

What about the implementation team?

We handle the implementation and deployment of Redshift for our clients.

What other advice do I have?

I am interested in seeing a split between compute and storage, which is something that they are currently working on. We plan to start leveraging it at some point in the future.

In summary, I think that Amazon Redshift is a very good data warehouse and we really like it a lot.

I would rate this solution an eight out of ten.

Which deployment model are you using for this solution?

Public Cloud

If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?

Amazon Web Services (AWS)
Disclosure: I am a real user, and this review is based on my own experience and opinions.
Get our free report covering Snowflake Computing, Amazon, SAP, and other competitors of Microsoft Azure Synapse Analytics. Updated: January 2022.
563,148 professionals have used our research since 2012.