Amazon Redshift Reviews

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.

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.

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. 

Positive

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. 

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 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!

Scalability: Ability to load huge number of datasets (I have experience with petabytes of data) and process those things. Storage is not limited. We can increase whatever we want.

Performance: The distributed architecture of Redshift has the capacity to process the workflow in a different cluster and coordinate those things in the leader node, making the process much faster.

Flexibility: This feature is helpful for user to increase the node size and config depending on their need. There is no need to wait for hardware to be in place whenever we increase the dataset. Redshift provides the option to increase the node or cluster size whenever required.

Multi-formatted accessibility: The Redshift engine has the capability to read the following file formats: CSV, DELIMITER, FIXEDWIDTH, AVRO, JSON, BZIP2, GZIP, LZOP. The user can choose which is best for their requirements.

VPC configuration: VPC configuration secures our dataset, which we keep inside the Redshift cluster. This VPC config doesn’t allow any third party in or out bound against firewall.

Python UDF calls: This is useful for a user to create their own user-defined function through Python and import that class into Redshift and process the dataset.

We were using MySQL & MongoDB for our regular operations, but when we grew, we were forced to handle a huge number of datasets. It could be petabytes of data in and out on a regular basis. We struggled a lot to complete the operations in a timely manner. With Amazon Redshift, we gained a lot in terms of timing, as well as project completion.

Some of the scoring mechanism really works well in the distributed architecture of Amazon Redshift.

Of course, every product has pluses and minuses. From that perspective, Amazon Redshift has some issues with snapshot restoring when we handle huge datasets. When our snapshot size is really huge, like 20 TB+, we are forced to wait a long time to get it restored. This is reasonable, as they need to transfer the entire dataset to the cluster.

My thought on this issue is that Amazon has their own data centers and they are connecting each region of storage through Direct Connect. The input and output network data transfer might not be a complex thing. For example, if they used 10 Gbps network transfer, they can transfer 1 TB in less than two minutes, but that’s not happening now. To restore 1 TB of data, it takes more than 30-40 minutes.

I have used it for the last 3.5 Years.

I am using Amazon Redshift for big data mapping and data aggregation.

We are using most of their products. Specifically, we are using their dedicated data-centre service (Direct Connect). We are using Amazon products such as Amazon EC2, S3, SQS, EMR, ML, CloudWatch, Redshift, DynamoDB, etc., for more than 10-12 years.

I have encountered stability issues. A few weeks ago, I encountered an issue with hardware failure and database health status failure. When we face these kind of issues, we can't do anything from our side until the Amazon technical team finds the issue and rectifies it. It takes time to get resolved. If we are in a rush to deliver something for a client and encountered these issue, we are really screwed.

Ofcourse. When the amount of data that we handle in the cluster grew, we need to increase the cluster or node size. Apparently, the size of node or cluster increases the hold time for synchronizing the data (meta data) with the node manager. The initial time increases when we start the cluster.

Customer Service good. But couldn't make direct call to customer service many times. I could catch them through their web UI rather making direct call.

Technical support is really great, but it’s paid support. The Basic Support plan doesn't have the option for technical support. It’s only providing billing support.

I have experience working in Hadoop as well. When I compare the two (Redshift & Hadoop), Redshift is more user friendly in terms of configuration and maintenance.

The initial setup of Amazon Redshift is so simple and straightforward. We do not need to read or understand any of the technical documentation. Simply said, it’s a plug-and-play service or platform.

I have implemented through in-house.

In terms of ROI, I can't directly convert to it. Because we are not using only Redshift. We are using multiple product to increase our revenue and decrease time consumption. So It's difficult to calculate ROI of Redshift usage.

Pricing and licensing is so important. In terms of pricing, it's bit high, as they are using standard hardware. My advice to users is: We need to start the cluster when we require it. At the end of the workday, we can just snapshot the clusters and shut them down. And then we restore those snapshots when we need them back. That way, we are charged only for usage rather than spending money on wait time or sleep.

I evaluated Hadoop and Spark, along with Redshift. I have no negative comments about those other products. Redshift is flexible in terms of configuration, maintenance and security, especially VPC configuration, which secures our data a lot.

Use this product for huge data mapping or aggregation. Use Redshift through VPC to keep their data very secure and for a long time.

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.