Amazon Redshift Reviews

We use Microsoft Azure, but one of our clients is on AWS, so we did a POC for Amazon Redshift. Now, it's up to them to make the call on whether to continue with the solution based on pricing and their needs.

Redshift's versioning and data security are the two most critical features. When migrating into the cloud, it's vital to secure the data. The encryption and security are there. 

Redshift's GUI could be more user-friendly. It's easier to perform queries and all that stuff in Azure Synapse Analytics.

I have been working on Amazon Redshift for six months, but I haven't used the solution extensively because we only did a POC for one client.

I think Redshift is stable. There shouldn't be any issues. 

Redshift is serverless, so you can scale it as needed. If the amount of data increases, the nodes will automatically be connected.

We haven't contacted Amazon support yet because we didn't encounter any issues that required support from Amazon, but I imagine it's comparable to the service we get from Microsoft. 

I've worked with a couple of cloud-based database solutions like Amazon Redshift and Azure Synapses,

Setting up Redshift is a little complex and requires some prior knowledge, whereas Azure's GUI is more intuitive and it's easier to navigate the steps.

We use this solution for our enterprise data warehouse.

We use it for scaling our warehouse.

We also use it for analytics.

A feature I find most valuable in Amazon Redshift is that it's fast.

I also like that you can query the data lake using the Redshift spectrum.

You can build analytics on this solution, similar to QuickSight or Tableau, based on the Redshift Data API.

Amazon Redshift also has good integration and a good API. It's not hard to manage. It even has machine learning features.

This solution could be cheaper, but Amazon could constantly add new instances and decrease the size from previous ones, so it could be an AWS work model.

It would also be better if it can be integrated with non-AWS sources, e.g. additional open source connectors.

We've been using Amazon Redshift for a long time. We've been using it for years.

This solution is stable.

I find this solution scalable to a great extent.

Amazon's technical support works fine.

Setup was easy. This is a managed service, so you don't need to install anything. You just choose the size of the cluster and within 10 to 20 minutes, it's built.

This solution implements the pay-as-you-use model, so no license. It's just for underlying infrastructure.

I evaluated Cloudera and Azure.

We usually rely on some distribution, not like classic Hadoop. We do not use  open source Hadoop because our customers prefer some distribution to get support. Some paid features from Cloudera and Amazon provide their own support.

We provide expertise for different services of AWS, e.g. most of them because we are a premium partner and we have program competencies. We develop data, big data, machine learning, and migration, so we cover a large field.

We have some clients with Azure, but most of our clients are with AWS.

The deployment of Amazon Redshift is through AWS. It's a home-based, proprietary solution. It's fully managed by AWS.

Amazon Redshift has implemented most of the features that we currently need, so I can't name additional features that I expect from them in the next release.

The number of people needed for the deployment and maintenance of this solution in our organization is just one: only to set up. It's just one DevOps.

I would recommend Amazon Redshift as a solution for others who are thinking about using it.

I'm rating Amazon Redshift an eight out of ten.

We are using the latest version of Amazon Redshift, although I cannot state which one. It is actually updated automatically, which prevents us from tracking it.

We use Amazon Redshift as our data warehouse solution. We use it for collecting and analyzing our data. We store our data for analytics in the solution.

The solution has improved the performance of our queries.

We like that the solution is a scalable, column-store database. We are completely talking about an analytic database.

I cannot state which features of the solution are in need of improvement, since those which we make use of have not changed.

The solution has four maintenance windows so, when it comes to stability, I think it would be better to decrease their number.

I rate the solution as an eight out of ten because it is not 100 percent, as there is much service-related maintenance required. It would be nice to see support for the usual LTP features, such as those involving traditional processing.

The solution has four maintenance windows so, when it comes to stability, I think it would be better to decrease their number.

The solution is scalable.

We use the solution extensively, as part of our daily work.

The decision to increase our usage would depend on our business needs.

I cannot comment on technical support, as I have never had contact with them.

Prior to going with Amazon Redshift, I used Azure Data Warehouse and Google BigQuery.

The decision to go with Amazon Redshift was reached by the CTO, so that, in respect of the data warehouse, the entire environment is set up in Amazon.

I feel Amazon to be better than the other solutions we worked with.

The initial setup is easy. Just one or two clicks are needed to set up the solution.

We did not make use of a consultant or integrator.

Not much staff is required to maintain the solution.

I am not aware of the licensing terms.

I am just the user and we make use of the solution.

The solution is deployed solely on the cloud.

I believe there are around 20 people making use of the solution in our environment.

While the solution is not appropriate for every case in which usage must be evaluated, it can be used for sure.

I rate Amazon Redshift as an eight out of ten.

We are premium partners with Amazon. 

This service can merge and integrate well with all databases. 

Planting is the primary key enforcement that should be improved but there is probably a reason that they don't follow the reference architecture. It means they are creating clones of the data shading. Cost control measures could be improved along with added transparency.

I've been using this solution for nine months. 

AWS technical support is very good. 

We needed some help from experienced professionals for our initial setup. 

Licensing costs are reasonable. 

I would recommend this solution depending on the scale. You need to decide whether you want to be lined up with a single cloud provider or go over the service and have it deployed on multi cloud. There are many factors to take into consideration. 

I rate this solution seven out of 10. 

Our data warehouse is Redshift now.

Overall, I'm satisfied with the solution so far, and, from an accounting perspective, it works well for my tasks and duties. 

The product is very stable. 

Changing from local servers to the cloud is very easy. It's so nice not to have to worry about physical servers. 

We need more AWS applications. They have some solutions from Amazon that can manage performance, however, we will need something that can also manage financial reporting, visualization, and analytics - instead of having to go to other solutions like Tableau or Power BI. If they can offer comparable options, we'd like to be able to choose all AWS solutions instead of other platforms. 

The refreshment rate of data reaching Redshift from other sources should be faster.

It could be more efficient during tasks such as data refreshing or uploading. 

I've been using the solution for about a year or so. It hasn't been too long just yet.

The solution is very stable. It's better than OWC, as a technology. There are no bugs or glitches. It doesn't crash or freeze. It's reliable.

I cannot speak to how helpful technical support is as this is not my area of expertise here. I'm not directly connected with AWS. That said, it is my understanding that they are doing a pretty good job with our own technical team and they have been helpful.

We used ODBC before to maintain our tables. Oracle ODBC was used as a server, as a data warehouse environment.

Changing to Redshift was a big change for us. However, after a while, we get used to it and it is okay now as it's coming together under a bigger picture of a framework, as a bigger framework. We are going to keep everything in the cloud and moving to AWS and we will put everything there and manage it as a framework going forward.

I'm not using it day in, day out and I did not handle the initial setup. There is a team involved with that side of the product. I'm using it for the closing of the accounting cycle every month. I don't handle implementation tasks. 

I cannot speak to the pricing. I don't handle billing or payments. 

We're customers and end-users.

While I cannot speak to the exact version number, my understanding is that we are using the most up-to-date version of the solution. 

I'd advise those considering the solution to go for AWS products. They are the best. You will have more synergy between your software. It's nice not having multi-software working on the technology itself. If you can, use as many genuine Amazon products as possible and integrate them together. 

Overall, I would rate the product at a seven out of ten. 

We are a solution provider and Amazon Redshift is one of the products that we implement for our clients. We are working with a few customers that have it implemented right now.

The feature that we find most useful is the ability to do analytics on the fly. It's the most important because it gives us the ability to provide solutions to multiple customers.

We have had some challenges with respect to considering some of the high-end availability architecture for production. We don't find many issues now, but initially, we had some challenges.

This is an older product, so when it comes to usability, it requires a technical person to work with it. It requires a specialist and a good business case to work on it. It has to be a little more user-friendly than what it is today.

In our experiments, the handling of unstructured data was not very smooth.

We have been using Redshift for the last year and a half.

It is fairly stable and works reasonably well.

We tested the scalability to 10 or 15 terabytes and we didn't have an issue with it. I'm not sure what the limit is.

The technical support is very good and they have helped us to move forward with this product. We also had a lot of good support from the community, as well.

It is not complex for a specialist because it is fairly well documented and systematic.

The specialists required by this product are what you will find in most enterprises. However, in a smaller organization, you might have to engage multiple parties with separate expertise to set it up correctly. For example, you will require somebody with experience in database migration to the cloud.

At the moment, pricing is a little bit on the higher side, although it depends on the size of the company. If it's a fairly large enterprise that has a defined budget then they may not have too much of an issue with the pricing.

We have also tried Cosmos DB and Azure for our customers, but they were not chosen after the PoC. Azure and AWS have different database offerings and we experimented with both, but the customer ended up in production and we stayed with that.

My advice for anybody who is implementing Redshift is to ensure that the requirements include having technical people on board to continuously work on getting the results you want. Because it's not that user-friendly, there is a need for a technical resource in the company.

Also, I would suggest watching out for scalability beyond what we have tested. If there is a need for scaling then it should be tested, although it depends on the use case.

If Redshift had a proper interface then I would score it higher.

I would rate this solution a seven out of ten.

We are a service provider and we currently have five clients with active IT implementations that use Amazon Redshift. We also use it ourselves.

My clients primarily use this product for data analytics. They are mostly working with big data and using the machine learning functionality.

I like the cost-benefit ratio, meaning that it is as easy to use as it is powerful and well-performing. There are only three parameters that you need to understand, which are the distribution key, the sort key, and the compression method or encoding method. Once you understand these, you can tune the performance.

I would like a better way to ingest data in realtime because there is a bit too much latency.

There are too many limitations with respect to concurrency. It is now possible to auto-scale it, although that is still slow.

It could offer smaller nodes with decoupling of storage and processing because for the moment, the only nodes available to work that way are huge, and for large companies.

My first implementation of Redshift was three and a half years ago, in 2017.

We have not had many issues with stability.

Scalability can be a problem if you don't write your database queries correctly. For example, if you write a cartesian product in Redshift then you may end up consuming all of the resources. However, it does have features like workload management to prevent this from happening.

Our clients are mid-sized to very large companies.

I have been in touch with Amazon technical support and they are very good. They are efficient and resolve problems quickly. They know what they're doing and they're very professional.

I have also used Snowflake and its methods for ingesting real-time data are faster. It also offers a bit more functionality and a bit more flexibility. It's a bit easier to maintain and faster to scale, but more expensive as well.

To me, the big drawback with Snowflake is that the data is not stored in your AWS or Azure subscription, or AWS account. They store the data in their own account that they manage for you, which might be a problem for some companies in terms of compliance and legal requirements.

Azure Synapse and Google BigQuery are also competing solutions.

The deployment is very straightforward and it usually takes a couple of minutes. This is one of the reasons I like it.

As long as a person understands the AWS landscape, they can deploy it on their own. Otherwise, without realizing it, they might for example deploy a Redshift cluster that is not properly secure. Similarly, it could cost a lot of money if they don't know what they're doing. You don't need a very in-depth technical expertise, but you do need to understand how AWS works.

I have a team that provides maintenance for our customers. It is spread between France and Belgium and I have 25 people who report to me, with another 20 who I work with indirectly.

The cost of Redshift ranges from a few hundred dollars a month to thousands of dollars a month, according to the resources that you're going to use, the number of nodes, and the type of nodes.

My customers have implementations that cost about $500 a month for a very small one. I also have a customer with a monthly invoice of about $25,000 USD.

With the most recent update, we should now be able to decouple storage from processes.

My advice for anybody who is implementing Redshift is to make sure that they are using it for what it is made to do. It's an analytical database, so it's not meant to process transactional data. It's the perfect tool if you use it for the right purpose.

Overall, it is a very stable and robust product. That said, there is still plenty of potential for improvement.

I would rate this solution a seven out of ten.

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.

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.

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.

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.

We have been using Amazon Redshift for about five years.

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

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.

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.

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.

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

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

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.