Amazon Redshift Reviews

I'm a freelancer/consultant, so I use the solution across a wide variety of contexts. 

The most valuable feature is that the solution is fully embedded in the AWS stack. 

The product is the best database for analytics, BI, and whatever else I encounter. 

The customer support could be more responsive. 

I've used Redshift for seven years. 

The solution is very stable. 

The tool is highly scalable. I'm a freelancer, so I use the solution in different contexts, but the total number of end users is usually between 100 and 200.

I contacted technical support before, and they could be more responsive. 

The initial setup was straightforward. I rate it five out of five here.

The product is cheap considering what it provides; I rate it five out of five for affordability. 

I rate Amazon Redshift ten out of ten. 

I recommend the solution to anyone in an AWS environment. I see a lot of fuss about Snowflake, and I used both, but I'm not much of an Azure guy. I don't know why the pickup rate for Redshift in NL is so low, but that's more marketing-driven, as Snowflake has very aggressive marketing.

Amazon Redshift is one of the best products I've ever come across. 

If you want to create an enterprise data hub, that is where Redshift is used. Snowflake, Redshift, BigQuery, and Azure Synapse are enterprise data warehousing and cloud data technologies. Large enterprises have enterprise data. They have a lot of managed processes, business processes, customers, products, different assets, locations, equipment, etc. Then they have sales and marketing. There's a huge amount of data that is generated, and they will need a large warehouse or multiple data warehouses to create analytics out of that data.

We try to tell organizations to consolidate all their data into a single unified data platform that has all the enterprise data rather than being processed by multiple warehouses. It's processed on one central data platform, which is cloud-based. In which case, we recommend one of these four. We either recommend Snowflake, Azure Synapse, AWS Redshift, or Google BigQuery. It depends on what their early investment is and what kind of work they need to do.

Redshift is completely Managed on AWS cloud.

I would like to see improvement in the pricing and the simplicity of using this solution.

The product is very stable, and so are all other cloud-based managed Enterprise data platforms (Snowflake, BigQuery and Azure Synapse)

It's scalable as it's on hosted and Managed on AWS cloud.

Technical support is great, very professional.

Neutral

I would recommend Snowflake the highest, then Google BigQuery, Azure Synapse, and then Redshift.

If somebody is heavily invested into Microsoft, then going for Azure Synapse is what we recommend. If they're open to moving to a completely new system, we evaluate the landscape and we recommend either Snowflake or Google BigQuery. What we recommend and what we design and create and implement for our different enterprise customers is very different for each customer. There's no One-size-fits-all solution.

For example, for one of our customers, we have helped design and create their entire single unified data platform using Snowflake.

I would say Redshift needs a little more effort and expertise for setting up the kind of infrastructure one need. If you can do something with two-three people for Snowflake, you would need four people on Redshift. You need to have a little bit of knowledge of the AWS Cloud and AWS services to be able to use Redshift. A typical Redshift based Enterprise data work would need anywhere between 4 to 15 people.

The return on investment of moving from an on-premise to a completely cloud-hosted data platform is significantly high and worth the effort.

Redshift is costly compared to other solutions.

It's pay per use. You can have multiple models. You can go for yearly cost, which is a little discounted than the monthly cost. Depending on how much data you process and store, you can have different pricing. There's no fixed cost. All of these are based on how much data you store monthly and how much data you process.

I would rate this solution 6 out of 10. 

If an organization has invested heavily in AWS services and they have a good knowledge of the AWS ecosystem, then I would recommend Redshift. Otherwise, I would still recommend Snowflake because Snowflake works very well with AWS services. I can have my AWS S3 buckets in which I can store my enterprise data lake, and then Snowflake works with that seamlessly. If the organization has good knowledge of AWS and good knowledge of RDBMS data warehouses, then we can recommend Redshift to them.

It all depends on how much investment that organization has done in Redshift. For example, we have a customer which has a very large setup. It's a large US-based company, where they have invested heavily in AWS. They're an AWS house, so they like everything about AWS. For them, we have recommended Redshift so that the overall tech ecosystem remains optimum. 

For the on-premises version of Amazon Redshift, we need to start from scratch. However, with the cloud version whenever you want to deploy, you can scale up, and down, and it has a data warehousing capability. Redshift has many features.

They have enriched and elaborate documentation that is helpful.

We are using third-party tools to integrate Amazon Redshift, they should create their own interface on their own for it to be easily connected on the AWS itself.

I have been using Amazon Redshift for one year.

Amazon Redshift is reliable and has high availability.

The scalability of Amazon Redshift is good.

We have approximately 20 people using this solution in my organization.

Before we were using Amazon Redshift, we were working with Postgres, Greenplum, and Oracle SQL. These were on-premises databases, and we migrated to the cloud.

The price of Amazon Redshift is reasonable because it depends on the usage that you use and for DWH for the long term.

I would advise others that if they have a large set of data where you have a less number of updates, then choose Amazon Redshift. If there is more update and fewer inserts, then do not use Amazon Redshift.

I rate Amazon Redshift an eight out of ten.

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. 

Redshift is a managed service for data warehouses.

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.

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.

I have been using Amazon Redshift for approximately one year.

There are three people in my organization using this soltuon.

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.

I have previously used ClickHouse.

The installation was easy.

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.

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.

I rate Amazon Redshift a seven out of ten.

Our company uses AWS. So, it was logical to integrate with other services, too. The solution is easy to set up and use.

I do not like the product. It is difficult to work with unstructured data and JSON documents. It would be great if the solution could handle unstructured data more easily. It will be useful if the tool provides support for vector operations.

I have been using the solution for a couple of years.

The pricing is reasonable. The cost might increase if we process a huge amount of data.

The newer version of Postgres can deal with unstructured data more easily. Amazon Redshift is not able to do it yet. Amazon Redshift is difficult to use comparatively.

We use the serverless version. My recommendation depends on the problem an organization is trying to solve. If a company uses AWS products, introducing another vendor is not reasonable. Overall, I rate the product a seven out of ten.

We use Amazon Redshift to store customer data. Basically, it's just to store our customer data so that we can use our own data.

I use Redshift Spectrum a lot, so that integration is good. Also, Amazon Redshift offers a relatively flexible structure, especially in terms of like, nodes that you can assign. Moreover, it is serverless, which is great.

Specifically, with Redshift Spectrum, some SQL commands have to run on Redshift instead of Redshift Spectrum, which slows down a few things in the tool. In the solution, user-based access is quite hard. In general, certain permissions are difficult to manage. The solution is expensive compared to Snowflake. I have used Snowflake because they're cheaper than Amazon Redshift. Some of the commands are run on Redshift itself, and some of the commands are completed by Spectrum, which is problematic. However, it is faster when computed by Spectrum.

I have been using Amazon Redshift for six to seven years. Also, I don't remember the version of the solution I am using. I think it's multiple different versions across the platform. So, I think it would be the latest version for some areas of our platform and older versions for other areas. My company has a partnership with Amazon.

Stability-wise, I rate the solution an eight out of ten. I can't remember what stability issues we had faced in the past, but I feel that it was due to overloading clusters.

Once we moved to a serverless version, it became more scalable. The concurrency of queries on the same cluster has a big scalability issue. Scalability-wise, I rate the solution a seven out of ten.

Around 300 people in my company use the solution.

The solution's technical support is good since we have a partnership with Amazon and we have individual support. I rate the technical support a nine out of ten.

Positive

Previously, we were using Snowflake in our company. We switched since Amazon Redshift was cheaper. Now, I use Snowflake and Amazon Redshift.

I wasn't involved in the solution's initial installation. The deployment model is largely managed by our platform teams. Also, we have a team of engineers who constantly update and maintain the solution. Probably a team of engineers is specifically focused on improving our Amazon infrastructure.

I am not sure about the pricing of the tool since that's not my department. I know that Snowflake is cheaper to set up, manage, and store data. On a scale of one to ten, where one is a low price and ten is a high price, I rate the pricing a seven.

I recommended it for data storage. I don't recommend integrated solutions, like Pacemaker unless you have an advanced team to handle it. I like using it, but it's too expensive. So, I rate the overall solution a seven out of ten.

We use Amazon Redshift as our data warehouse.

I found the Amazon Redshift computing services easy. I found the computing instances the most incredible in the solution.

What would make Amazon Redshift better is improvising on the pricing structure. For example, Acronis provides backups in cybersecurity, yet the pricing is a bit lesser than Amazon Redshift. I was comparing AWS, Amazon Redshift, Azure, GCP, and Acronis, and I found that Acronis has a lesser price than the other solutions in the archiving space.

I have at least two months of familiarity with Amazon Redshift.

Amazon Redshift is a stable solution.

Amazon Redshift is a scalable solution that also suits enterprise companies.

I haven't contacted Amazon Redshift support because I'm not a client, but according to my subordinates, the support is excellent.

Amazon Redshift is very easy to deploy, and deployment-wise, it's impressive. It only takes two to three minutes max to deploy.

Pricing for Amazon Redshift is reasonable, though it could be somewhat higher than other solutions, such as Azure. Still, when you base your comparison on the services offered and the pricing, it's the most reasonable versus its competitors, such as RDS.

My company provides backup solutions.

I'm a business analyst with little expertise in a specific service or solution, but I've gone through all the solutions.

I have experience with Amazon Redshift.

What I'd tell others looking into implementing Amazon Redshift is that it's one of the market's best databases or data warehouses right now.

My rating for Amazon Redshift is nine out of ten.

I'm an Amazon partner.