Amazon Redshift Reviews

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. 

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.

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 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.

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.

Amazon Redshift is very fast. It has really good response times. It's very user-friendly.

Redshift is a multi-tier engine that works like a calculator. There is some missing functionality and sometimes it's so difficult to work in. We need to convert these functionalities using VACUUM inside Amazon Redshift and then it causes some complexity. Sometimes I'd like for them to support some special features or some special installations because we need automatic populations. I would like to see more programming outside of the cloud. I would like to see more functionalities under JSON files. the only functionality that they have now with JSON is reports. I would also like to see other data sources like MongoDB.

I have used Amazon Redshift for three years. I use the latest version because it is on Amazon's public cloud.

The management of the dates for what we can deliver to it, it's always specific to the form that's defined to Amazon Redshift.

I have used their technical support only a few times. Before talking to support I usually try to troubleshoot things myself and I'm usually able to resolve any issues. 

In the past year, we have used Azure, but the committee has chosen Amazon Redshift because it is better than Azure for our company needs. We have grown around Amazon Redshift and other AWS solutions.

Amazon Redshift is not as straightforward as other AWS tools but it is not that difficult.

Amazon Redshift costs less than Oracle Cloud or Microsoft Azure.

I started using Amazon Redshift because I started working for this company that was working with both Azure and Amazon. The company eventually moved all to Amazon. I wasn't sure why they didn't continue to use Azure. My experience was more with Microsoft technology so I prefer Azure. But, there are some interesting features in Amazon Redshift that works better. I have also used Oracle Cloud.

I would recommend Amazon Redshift as it is part of the AWS platform and they are the biggest in the world.

I would give Amazon Redshift a rating of eight on a scale of ten.