Amazon Redshift Reviews

We mainly use the solution for marketing analytics.

The solution works fast. I use Redshift to clear a lot of web page data. I use it mainly as an extraction tool to obtain the information I need for a project and store it in parquet files on a disk. Later, I work on the data using Python. I write back all my final results to Redshift and store the temporary files on a local machine.

They should provide a structured way to work with interim data than to store it in parquet files locally. Also, Redshift is unwieldy. There should be better integration between Python and Redshift. It could be more accessible without using so many sequels.

They should make writing and reading the data frames into and from Redshift easier. The performance could be better. I have used Redshift for extensive queries. For the large tables, it's easier to unload to Redshift, but subquery tables that run complex grids are slower for configuration. I have to use the unloaded command to unload the whole table. Further, I have to read the table into a server with extensive memory in Python and process the data ahead. It's not optimal. 

We have been using the solution for two years.

I rate the solution’s stability as a nine.

The solution is scalable. It handles different loads very well. We have 80-100 users using the solution in our company.

The setup was quite complicated. For instance, if you use AWS Glue to automate loads into Redshift, setting up the security for the requirements between the two is complex. I've struggled a lot to set up the cluster on VPC and to get all the endpoints set up correctly with the right access and services. Especially from Glue's endpoints, I had to repeat the same process every time. It consumes a lot of time. In comparison, the CloudOps executives do the setup very quickly.

I have heard complaints about the solution’s pricing, and thus I rate it as a five.

I rate the solution as an eight out of ten.

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 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.

• Easy to build out our snowflake design and load data
• Ability to dynamically increase space requirements
• Good speed
• Extremely reliable

We use Redshift as our primary BI data repository. It provides BI for all four of our product lines, which run on Redshift. It is low cost and highly reliable!

It would be nice if we could turn off an instance. However, it would retain the instance in history, thus allowing us to restart without beginning from scratch.

We have been using this a little over a year.

It is pretty easy to learn and use. If you've worked with SQL before, you won't have any problems. Also, it works very well with Talend, which is our ETL tool.

No issues of stability at this point.

No issues of scalability at this point.

I don't know that we've ever had to contact AWS for Redshift assistance. Everything is straightforward.

Not applicable.

This was our first foray into a data warehouse and customer facing BI.

We went into the project with a design in mind and Redshift provided a great working platform. Our ETL tool helped us out in building the metadata and Birst built out many of the necessary tables.

The primary implementation was done in-house, with assistance from Birst during the Birst installation.

The corporate expectation is to break-even after the first year of selling BI to our customer base. We'll know this by end of Q2, 2018. On the positive side, the addition of BI has helped close multiple sales, so we're beating the competitors with our BI tools (running on Redshift).

BI is sold to our customer base as a part of the initial sales bundle. A customer may elect to opt for a white labeled site for an up-charge.

We pretty much went with Redshift, as the company migrated everything to AWS. We might have looked at other database options, but we did not put much time into it.

Plan out your our DB design in advance and test your theories on running a small instance first. Use a good ETL tool, like Talend, so updates can be scheduled easily. Don't try to write these from scratch. Redshift has been a great DB for us to date. We haven't seen any slowdowns or outages!

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.

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.