Buyer's Guide
Data Warehouse
November 2022
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Director, Consulting, Technology Services at a financial services firm with 1,001-5,000 employees
MSP
Easy to scale out and scale down services and relatively straightforward to install, but needs Managed VNet and more compatibility with SQL Server
Pros and Cons
  • "The ability to scale out services on-demand and scale them down when they are not required is most valuable. You are in control of your expenditures, and you are also in control of the horsepower that you need. That's a major advantage."
  • "The major challenge that we're seeing with Azure Synapse is around security concerns. The way it is working right now, it has Managed VNet by Microsoft option, similar to the implementation of Azure Databricks, which may pose a concern for financial institutions. For managed environments, the banks have very strict policies around data being onboarded to those environments. For some confidential applications, the banks have the policy to encrypt it with their own key, so it is sort of like Bring Your Own Key, but it is not possible to manage the resources with Microsoft or Databricks, which is probably the major challenge with Azure Synapse. There should be more compatibility with SQL Server. It should be easier to migrate solutions between different environments because right now, it is not really competitive. It is not like you can go and install SQL Database in some other environment. You will have to go through some migration projects, which probably is one of the major showstoppers for any bank. When they consider Synapse, they not only consider the investment in the actual service; they also consider the cost of the migration process. When you scale out or scale down your system, it becomes unavailable for a few minutes. Because it is a data warehouse environment, it is not such a huge deal, but it would be great if they can improve it so that the platform is available during the change of configuration."

What is our primary use case?

We mostly provide cloud data warehousing platforms for major banks in Canada. What we're trying to do is to create a standard platform environment that is compliant with the regulatory requirements imposed by the government and financial overseeing institutions for the banks. We help them to onboard the lines of business to these platforms and migrate the existing workloads to the cloud platforms.

What is most valuable?

The ability to scale out services on-demand and scale them down when they are not required is most valuable. You are in control of your expenditures, and you are also in control of the horsepower that you need. That's a major advantage.

What needs improvement?

The major challenge that we're seeing with Azure Synapse is around security concerns. The way it is working right now, it has Managed VNet by Microsoft option, similar to the implementation of Azure Databricks, which may pose a concern for financial institutions. For managed environments, the banks have very strict policies around data being onboarded to those environments. For some confidential applications, the banks have the policy to encrypt it with their own key, so it is sort of like Bring Your Own Key, but it is not possible to manage the resources with Microsoft or Databricks, which is probably the major challenge with Azure Synapse.

There should be more compatibility with SQL Server. It should be easier to migrate solutions between different environments because right now, it is not really competitive. It is not like you can go and install SQL Database in some other environment. You will have to go through some migration projects, which probably is one of the major showstoppers for any bank. When they consider Synapse, they not only consider the investment in the actual service; they also consider the cost of the migration process.

When you scale out or scale down your system, it becomes unavailable for a few minutes. Because it is a data warehouse environment, it is not such a huge deal, but it would be great if they can improve it so that the platform is available during the change of configuration.

For how long have I used the solution?

I have been using this solution for two years.

What do I think about the stability of the solution?

Generally, it is stable. We all heard about the Active Directory issue earlier this week, but it was not related to Synapse. It was related to the Azure platform.

What do I think about the scalability of the solution?

Its scalability is good. The only thing is that when you scale out or scale down your system, it becomes unavailable for a few minutes. Because it is a data warehouse environment, it is not such a huge deal, but it would be great if they can improve it so that the platform is available during the change of configuration.

How are customer service and technical support?

We're working with banks, and they have great support because Microsoft has multiple representatives closely monitoring each account. Whenever there is an issue, they're being proactive. They're making a lot of money out of it. Most of the banks, on average, spend between 30 to 50 million a year on Azure. They're pretty large accounts, and Microsoft has dedicated people supporting everything related to Azure.

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

We deliver platforms to different banks. Some of the banks go with Synapse, and some of the banks go with Snowflake. Overall, these are two major alternatives available right now.

There are multiple differences in terms of the support of different workloads. When one of the banks made a decision to go with Snowflake, the major reason for it was the support for the multi-cloud environment. The major pro of Synapse is the service, and the major con is that when you decide to move out of Synapse, you would have to rewrite the entire thing, whereas, with Snowflake, it would be just simple migration to different cloud providers.

How was the initial setup?

It is relatively straightforward as long as you understand what you're doing.

What about the implementation team?

You don't really need to maintain it. That's the entire point of the cloud. You pay for it to be maintained. 

We do deal with monitoring and other similar things, but most of the activities are automated. Overall, it doesn't require a lot of labor around it. We're delivering the platform as infrastructure as a cloud, so everything is going through the pipeline. 

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

It goes by the usage, and there are some limits. Synapse goes by particular pricing, and it is expensive. Both Azure Synapse Analytics and Snowflake are pretty expensive. They don't have standard pricing. They deal with each customer differently.

What other advice do I have?

For working with Synapse, you need to have an understanding and knowledge of the product to take full advantage of it. Synapse has a lot of features in terms of scalability, such as resource management, distribution, and partitioning. There are a lot of things that you need to consider when you go for it. It is not a simple database that you put in there, and it is running itself. 

I would rate Microsoft Azure Synapse Analytics a seven out of ten.

Disclosure: My company has a business relationship with this vendor other than being a customer: Partner
Deputy General Manager at a tech vendor with 10,001+ employees
Real User
Gave us 27% performance improvement and reduced costs by about 17%
Pros and Cons
  • "There are some performance features like partitioning, which you can do based on an integer, and it improves the performance a lot."
  • "With other columnar databases like Snowflake, you can actually increase your VM size or increase your machine size, and you can buy more memory and it will start working faster, but that's not available in BigQuery. You have to actually open a ticket and then follow it up with Google support."

What is our primary use case?

BigQuery is a PaaS solution. There's only one version available on Google Cloud. Because it's deployed on cloud, it will update automatically.

What is most valuable?

If I'm collaborating with Google Data Cloud, I can use the cache, and I don't have to pay again and again. There are some performance features like partitioning, which you can do based on an integer, and it improves the performance a lot. There's also the Array function. You can also enable Spark on BigQuery, which is actually faster than any other Spark. If you use Dataproc, Spark on BigQuery is much faster.

Spark will actually eliminate the usage of a lot of Adobe legacy things. It will act as a Spark SQL.

It is not that cost-friendly, but it is very performance-friendly. There are also machine learning features.

What needs improvement?

For example, if I have a query, and I have done everything to improve it, the query will still take 15 minutes. With other columnar databases like Snowflake, you can actually increase your VM size or increase your machine size, and you can buy more memory and it will start working faster, but that's not available in BigQuery. You have to actually open a ticket and then follow it up with Google support.

For how long have I used the solution?

I have been using this solution for two and a half years.

What do I think about the stability of the solution?

BigQuery is very stable. It is getting used a lot.

What do I think about the scalability of the solution?

It is definitely scalable. You do not have to do any configurations. It will be able to handle petabytes of data.

How are customer service and support?

Technical support is excellent. It is Google, and they always provide the best. We haven't needed to contact Google for BigQuery specifically, but I have contacted Google support for other things and they were pretty responsive.

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

I have experience with Snowflake.

What was our ROI?

I was working on a project where we were building systems and loading the data manually. Once we moved to BigQuery, we saw ROI in terms of cost savings. We saw 27% performance improvement in most of our queries. Our total costs were reduced by about 17%. In terms of cost and time, we were able to save effort.

There was some learning and training involved, which lasted six months, so we saw the real ROI after a year.

What other advice do I have?

I would rate this solution 8 out of 10.

My advice is to first identify your use case. If you have Google Cloud then you have two databases to compare, BigQuery and Snowflake. BigQuery is typically used to analyze petabytes of data. If you're looking for transitional query, then you should have a different system. BigQuery cannot handle unstructured data, so that is one thing you have to think about. 

In terms of latency, if you want single-digit millisecond latency then BigQuery is not good. It is very fast, but if you want single-digit millisecond latency, then you probably have to go to a no-SQL database solution.

My suggestion is to analyze your use case and then map it with the BigQuery features.

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?

Google
Disclosure: My company has a business relationship with this vendor other than being a customer: Partner
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Raghunandan Rajput - PeerSpot reviewer
Data Engineer at a tech services company with 51-200 employees
Real User
Top 10
Full AWS integration, well maintained, but lacking main features from competitors
Pros and Cons
  • "I find the most valuable features to be the MPP style of processing, which mostly all of the data warehouses provide. The ability to integrate all other AWS services, such as NSS and S3, with little effort is very helpful. The service is well maintained, there are update patches frequently."
  • "We recently moved from the DC2 cluster to the RA3 cluster, which is a different node type and we are finding some issues with the RA3 cluster regarding connection and processing. There is room for improvement in this area. We are in talks with AWS regarding the connection issues."

What is our primary use case?

Redshift is a managed service for data warehouses.

What is most valuable?

I find the most valuable features to be the MPP style of processing, which mostly all of the data warehouses provide. The ability to integrate all other AWS services, such as NSS and S3, with little effort is very helpful. The service is well maintained, there are update patches frequently.

What needs improvement?

We recently moved from the DC2 cluster to the RA3 cluster, which is a different node type and we are finding some issues with the RA3 cluster regarding connection and processing. There is room for improvement in this area. We are in talks with AWS regarding the connection issues.

In an upcoming release, I would like to have a Snowflake-like feature where we can create another cluster in the same data warehouse, with the same data. You can create a different cluster and compute nodes for each of your use cases, for retail, and for your data analyst all while keeping your underlying data safe.

Additionally, the cluster resize process takes down the cluster for too long, approximately 15 minutes. There are limitations to the size, you can resize only by a multiplier of two, for example, if you have four nodes then you can either go to eight nodes or you can come down to two nodes. There should be fewer limitations.

For how long have I used the solution?

I have been using Amazon Redshift for approximately one year.

What do I think about the scalability of the solution?

There are three people in my organization using this soltuon.

How are customer service and technical support?

Their technical support is good. They provide assistance when we need it but since we were experiencing a connection issue it was taking longer to get a resolution. We had to involve a vendor to get it resolved for us.

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

I have previously used ClickHouse.

How was the initial setup?

The installation was easy.

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

The price of the solution is reasonable. According to the RA3 cluster particularly, it provides 128 GB of storage with only four nodes. If you can manage your computations processes with the help of materialized views and proper queries. I think the IP clusters are very useful and overall fair for the price.

Which other solutions did I evaluate?

We have been evaluating Snowflake and are in the POC phase. If it passes our quality tests then we will be moving to it soon.

What other advice do I have?

I rate Amazon Redshift a seven out of ten.

Which deployment model are you using for this solution?

Public Cloud
Disclosure: I am a real user, and this review is based on my own experience and opinions.
Head of Data Value at Innova-tsn
Real User
Good business intelligence and analytics with pretty good stability
Pros and Cons
  • "The business intelligence is very good."
  • "The customization can sometimes be difficult to achieve."

What is most valuable?

We used to work on business intelligence projects, so we really enjoyed the service-like performance.  It's been great.

The business intelligence is very good.

We have found that the analytics environment is excellent.

What needs improvement?

We've discovered that the solution is quite a complex product, which can make it difficult to sell. Snowflake, for example, is simpler and therefore an easy sell.

The customization can sometimes be difficult to achieve.

For how long have I used the solution?

We've been working with the solution for a very long time. It's been more than 15 years personally and at least 15 years at this company, so it's been well over a decade at this point.

What do I think about the stability of the solution?

We don't deal with bugs or glitches and the product doesn't crash or freeze. The only real issues we come across are related to customization. It's quite stable. We haven't had problems.

What do I think about the scalability of the solution?

We have about 100 people using the product currently.

Our clients are quite sizeable companies.

How are customer service and technical support?

I've never used technical support and therefore can't really comment on their responsiveness or level of knowledge. I have an internal team that assists with troubleshooting as necessary.

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

As a consultancy, we work with a variety of products. This includes Oracle and Snowflake, for example.

How was the initial setup?

We are an integrator of the solution. Our clients are sizeable companies, and there are several providers involved in different projects with Exadata. We're not the only administrators. 

I personally haven't handled an installation. We're mostly focused on projects related to BI and analytics. Someone else handles the setup and we just use the product or have our clients use it. I don't have a sense of whether the implementation is difficult or complex or how long deployments take.

What other advice do I have?

We are a consultancy. We are partners with Oracle, with Snowflake, and with other vendors, software vendors.

We work in different deployment models with our customers. We try to fit our customers' needs. It depends on the customer and the project in terms of which deployment model we'll recommend or use.

Overall, I would rate the solution a nine out of ten. It's very good. We've had a great experience using it over the years.

Disclosure: My company has a business relationship with this vendor other than being a customer: Partner
Founder & CEO at a tech services company with 51-200 employees
Real User
Top 20
Integrates well with open-source, is stable, and has good support
Pros and Cons
  • "I like that it integrates to open-source."
  • "SAP Business Warehouse could integrate better with other ETL tools."

What is our primary use case?

We use SAP Business Warehouse to host the data. We are hosting financial services data.

What is most valuable?

I like that it integrates to open-source.

What needs improvement?

SAP Business Warehouse could integrate better with other ETL tools.

There is some complexity to the setup. It would be helpful if the setup could be simplified.

I would like to see more MLOps capabilities included.

For how long have I used the solution?

I have been using SAP Business Warehouse for one year.

We are using a previous version.

What do I think about the stability of the solution?

We did not experience any bugs or glitches with SAP Business Warehouse. It's a stable product.

What do I think about the scalability of the solution?

SAP Business Warehouse is scalable, but you need to understand the product well.  It requires some expertise.

We have five people in our organization who use this solution.

How are customer service and technical support?

Technical support is good. They were able to assist us in some specific issues we were experiencing.

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

I have some experience with Snowflake.

We did not previously use another solution, this was a new implementation.

How was the initial setup?

The initial setup can be a bit complex. It's not easy, but not overly complex, It's medium.

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

It's moderately expensive, but definitely has its branding and price value for it.

What other advice do I have?

SAP Business Warehouse is a good option if you are interested in memory analytics including HANA.

I would rate SAP Business Warehouse an eight out of ten.

Which deployment model are you using for this solution?

Private Cloud
Disclosure: I am a real user, and this review is based on my own experience and opinions.
Buyer's Guide
Data Warehouse
November 2022
Get our free report covering Microsoft, Micro Focus, Teradata, and other competitors of Snowflake. Updated: November 2022.
653,584 professionals have used our research since 2012.