Amazon Redshift Reviews

We use Redshift Spectrum for creating temp tables during the Ignition process.

I have primarily used the Redshift Spectrum feature and found it most valuable.

During our last office project, Redshift couldn't perform well even for a data size of 6 TB. Thus, compared to Teradata and Snowflake, the solution needs to work faster. They should extend the plan by including better optimization and readability as we get while using Teradata. Also, they should provide zero-copy coding and sharing facilities.

I have been using the solution for three months.

I rate the solution's stability as a seven.

There is no issue with the solution's scalability.

The setup was straightforward as I have a POC. It was a simple process.

The solution is available at a mid-range price as compared to other vendors.

While using Redshift, we need to combine it with Glue to complete the process. Whereas, Databrix offers the same procedure without combining two solutions. Redshift would work well with small businesses if they already use AWS services. They can use Redshift if the database is not that huge. I recommend Snowflake over Redshift. I rate the performance as well as the overall product as a five.

I have used it for our reporting solution requirement. We gathered data from different processes and applications, like the high system process. Clients can review the data; we use it for connections and reports. Additionally, Redshift generates some configuration files without using an application.

For reporting purposes, Redshift is a great tool to use. Redshift has an advantage when it comes to administration, making it easier to manage and collaborate. Additionally, its server architecture allows for faster processing. Redshift also supports prepaid costs, which is another great feature. However, similar features are also available in Azure.

Redshift has some advantages in terms of administration and performance.

When compared to Snowflake, Amazon Redshift does not have the capability to dynamically increase the VM file. However, Amazon Redshift provides a virtual database called 'VW' that allows you to increase the size of the warehouse to run faster on a monthly basis without changing anything. This feature is not available in Redshift. So it's a limitation of Redshift.

It's not possible to immediately increase the virtual warehouse size in Amazon Redshift. When compared to Snowflake, we cannot increase the virtual warehouse size in Redshift. 

I have been using this solution since 2015. 

I don't see any issues with data loss or any other problems. Although there might be some loss in the data center, we monitor it, and everything is enabled. In such scenarios, the turn-up time is much faster. We've been using it since 2018, and I've got the same product for another customer using a limited rate. So, I don't see any significant impact, and it's a very stable product.

We have to consider the scalability of this solution carefully. In production, we have a proper size. We allocate 40% for data storage and 60% for temporary segments. We cannot increase data storage usage beyond 50%. It cannot exceed 80% of the total utilization, including network speed and query performance. We monitor all of these carefully.

So if the CPU utilization goes beyond 80%, I recommend upgrading to multiple nodes. It ensures that there won't be any issues. Around 30 people are using AWS and Azure modules along with me.

We have contacted the Redshift team for support related to other installations, such as WDL configuration for project implementation for a web application. When it was not working as expected, we had to provide authentication for the web chat. So, we used to contact them for that kind of knowledge.

The initial setup depends on who is doing it. In my opinion, it doesn't require much knowledge. Since we've been using it for a long time, it's much faster for me, but it might not be the same for others.

It's on the expensive side.

One reason we chose this solution is that we are in the process of moving everything to the cloud. But that's not the only reason. My company wanted to consolidate everything into one system, and AWS provided all the necessary information in one place. For example, Lambda is for specific storage and limited membership; all this information is available in one cloud network. This way, data segregation is much faster and easier to use. It's just everything in one cloud network, so we decided to use it.

I would recommend it. However, I think we need to consider other configuration levels. You need to decide, and I would not go with the first option.

To evaluate the data you are planning to migrate, we need to assess the environment. What is the value of your data, and what type of data is it? The density of the data is also important. Before implementing Redshift, we need to ensure that the AWS configuration is activated. After that, you need to set up enrollment and increase your storage. I don't recommend making a purchase on the same day, but it is a critical moment at a high level.

I suggest purchasing a renewal that meets the deposit requirements so that you can have a good experience and optimal performance. You can increase the budget for the building process. If you have the right team, such as those with experience in AWS or those who are learning about Azure databases, they can start using Redshift without any issues.

Overall, I would rate the solution a nine out of ten. 

We were using the solution for our data backup, but we wanted to optimize it, so we turned to AWS Glue. Amazon Redshift wasn't really great for us and wasn't working out.

Amazon Redshift was used for data storage while moving back from S3 to Amazon. However, it lagged, taking its own sweet time for data backups which also depended on the server location. Because of the aforementioned reasons, we started losing a lot of data that wasn't even real-time data. Ultimately, this affected our analytics at the end of the day. Also, we have been trying to do some work on our AI models, which emit out recommendations based on the live dataset. There were a lot of lagging issues. So, for example, sending out somewhere around 0.1 million or 100,000 emails used to take almost 12-14 working days, and this also includes the process of pulling all the data and sending them to CronJobs. Since we wanted all this work to happen in real-time, we had to get rid of the tool.

I would like Amazon Redshift to improve its performance, analytics, scalability, and stability. Other than these points, I am not aware of any other areas to address since Amazon provides a variety of independent services for their customers to choose from, and if one were to express dissatisfaction with Amazon Redshift, Amazon would likely suggest AWS Glue as an alternative. Similarly, if another issue arose, Amazon might recommend Amazon RDS. There are a lot of things they try to upsell to you, each with its own pros and cons and in different packages offering different perks. So, it all depends on your business needs and what you choose for your business. I wouldn't criticize Amazon for this because they have created packages tailored to their customer's needs, which helps to prevent customers from looking elsewhere.

I have been working with Amazon Redshift as an implementer for three years.

Stability-wise, it has a lot of issues with threats, and that is why we went for a threat shift optimization. In short, I mean to say that it is not stable at all.

If you require a highly scalable solution, I would not recommend Amazon Redshift. We currently have 12 clients using Amazon Redshift, and the scalability of the solution is terrible. In terms of scalability, I would rate this solution a three or four out of ten.

Amazon Redshift has a lot of documentation, but the setup is fine. Three years ago, the solution's deployment process took over a month or a month and a half.

Every solution has a cost and comes in different packages. Considering these factors, AWS Glue is on top. Though Amazon Redshift is good, it depends on what kind of business you're trying to do, what type of analytics you need, and how much data you have.

For Amazon Redshift, we pay around INR 60,000 annually. The cost factor also depends on the number of existing customers. In addition to the standard licensing fee paid for AWS, we incur a cloud storage cost of around a quarter million for the amount of data. We also have to bear additional costs for data security and cybersecurity, which are well taken care of by Amazon, hence the premium pricing. There are several other features and services provided by Amazon that justify the premium pricing.

Amazon Redshift is a horrible solution. I recommend my customer to use AWS Glue since while dealing globally with real-time data, which you need to make decisions, factors like how much cost and data is needed to make a decision should be considered. Apart from this, if customers are paying a huge price for the solution, then probably Amazon shouldn't mind spending on the tool. However, it may not be necessary for small businesses with only a few thousand data points. Although Azure is a better option, some clients prefer AWS, and we had to develop a solution using AWS for our client. Overall, I rate this solution a three or four out of ten.

We use Redshift as a central data warehouse. This data can be consumed directly by AWS services or different applications where we can provision the data via Athena. If we want to create more business intelligence tools and analysis, we write some SageMaker notebooks for deploying machine learning models based on the data.

We have a wide variety of use cases, but we generally use it to have one place where we can store data. We also connect enterprise legacy systems such as SAP systems. I'm mostly connecting shop floor assets and the industrial machinery to store relevant data in one place and make it available. Via Athena, combined data can then be retrieved with easy SQL queries.

Usually, we use the newest version of the solution. If there are new updates available, we try to take them directly.

Our customers usually have a hybrid cloud or full cloud architecture with minimum on-premises data centers.

We have five to ten customer projects per year in our department in which we set up data lake houses using Redshift. Those companies have between 3,000 and 15,000 people. Not everybody has to use Redshift. Depending on the project and the size of the consulted company, there are 2,000 to 3,000 end users who need access to the stored data.

We are a consultancy company of 1,500 people. Those who use a sophisticated data warehouse architecture tailored to the business requirements, profit a lot since this is the foundation of business intelligence which makes a company more resilient and adaptable to change. We try to select the correct service for our customers, and when using AWS, we usually do data warehousing with Redshift.

The main benefit is that our portal for end users is running in AWS, so we can easily connect it to other AWS services. The most important part for us is the connectivity inside AWS.

Pricing sometimes depends on the setup (key, etc.) which makes it hard for somebody new to AWS. Detailed research has to be conducted to end up with a competitive solution in terms of pricing and performance.

I have used Redshift for a year and a half.

I would rate the stability as nine out of ten since AWS provides a relatively resilient solution in general due to load balancing and auto scaling capabilities.

I would rate the scalability as ten out of ten.

We are a certified partner of AWS, so we have a different level of customer service, but usually, the customer service is fast and efficient even without a direct contact person.

Positive

My company has more than 20 years of experience with SAP in general and the Data Warehouse Cloud is also used for customer projects.

I'm familiar with AWS in general, so the setup is not difficult. For people who struggle with IAM or role-based management, the setup can be challenging.

In cases where there is deep knowledge of creating a microservices architecture using AWS, a project can be executed quite fast. The only reason for using AWS is the aim for AWS Redshift as a data warehouse, the setup is not as easy.

The amount of time it takes to deploy depends on the project. We try to do our projects incrementally, so we start with one department and deploy all of the relevant data from that. It takes about two to three months to draft a minimum viable product, connect a couple of machines, and use Redshift to work with data consumed by analysis tools or reporting capabilities. It is possible to set up a data warehouse in one or two weeks.

There are different types of projects, and if we do it within a waterfall approach, it can take a long time.

When creating a data warehouse using Redshift, we first analyze the current situation and then sketch the architecture in AWS with the required ETL process to ingest and consume data, including the right processing to aggregate and enrich data according to business requirements. This is where all the customization comes in.

For deployment and maintenance for only one customer, I would say that three to six experienced people can handle the job. For maintenance work, in my opinion, there is only one person required for two or three hours a week maximum.

I would rate the setup as eight out of ten.

The cost will depend on how you set up your warehouse and what kind of data you store. I would rate the pricing as six out of ten.

I would rate this solution as nine out of ten.

My advice is to use a consultant to set it up correctly and to get familiar with data warehousing in general. It's pretty straightforward once you're using the data management console. Anyone could use Google to set it up, but to do it correctly and sketch the perfect architecture, an external consultancy company should handle it because the usual IT departments aren't that experienced.

I think Redshift is worth the money, and there's always some return. Most companies don't have a full solution for business intelligence. AWS provides a pretty good service architecture to implement this. Anyone who uses Redshift or a data warehouse in general will have a return on investment.

It is storing warehouse data for the organization. We commission data warehousing, storage of data, and reporting.

Data Science and Machine Learning are valuable features. We have found Machine Learning use cases are very nice.

Infinite storage is available in Snowflake and is not available in Redshift. Analytical tools for integration would be helpful in the future.

I have been working with Amazon Redshift for seven years now.

We have found Amazon Redshift to be stable.

We have no problems with scalability.

The initial setup is very smooth and took us about six months to deploy.  The cost is comparable to Snowflake.

I would rate Amazon Redshift a nine out of ten. I am very satisfied with it.

We use the solution for data storage of reports.

Redshift Spectrum is the most valuable feature.

The product must become a bit more serverless. Users should have to pay only for the resources they consume.

I have been using the solution for one year.

The tool is quite stable.

Around 20 people in our organization use the product. The tool’s scalability is good.

The solution is deployed on the cloud. The initial setup was pretty easy.

The product is quite expensive.

We also tried using Athena. However, Redshift was faster.

We use the tool because we have everything on AWS. Amazon Redshift is best for fast reporting. People who want to use the solution must try using Athena. If it is not fast enough, they can try Redshift. Overall, I rate the product an eight out of ten.

I use Amazon Redshift for the creation of SQL ETL procedures in a business system. Business people check this in a front-end application, and it helps them plan sales for the next year.

Redshift is being deployed on a Microsoft Azure server.

There are about six people working on this project and using the solution, but there are many similar projects running on Oracle and Redshift.

I like it because the usage is very similar to Microsoft SQL server. The structure of the query and the temporary tables are very similar. Until recently, I thought it was the superior database, but now I think that Redshift is better.

The explain panel in the Redshift database could be better.

I have used this solution for 10 months.

The solution is stable. I haven't had any problems or downfall with the database in the 10 months that I have used the solution.

I have also used Microsoft SQL server and Oracle.

Setup was difficult because I had to set up 25 connections with different users and passwords. The connections have been predefined, but there were still problems when trying to connect for the first time. I had some problems with some certifications that were malfunctioning. This might have had something to do with the functionality of my keyboard because if I pushed a random combination on the keyboard, it would delete the certificate from the folder and the connection wouldn't work. I think this is a problem with the remote desktop rather than with Redshift.

I would rate this solution as eight out of ten. I can't give it a higher score because there are some issues with variable character columns in the table. Otherwise, it's a great database.

Some of my former colleagues from a previous job have joined my organization, and they have had some issues with the SQRs because some things work differently in Redshift, like the partition bar. If someone has issues with Redshift, my advice is to check with support.

I use the solution in my company for our data warehouse and databases.

The high price of the product is an area of concern where improvements are required.

I have been using Amazon Redshift for three years.

My company uses IBM Cognos as a reporting portal on top of Amazon Redshift.

My company moved from Netezza to Amazon Redshift since the latter is available on the cloud platform. My company used some migration tools to shift from Netezza to Amazon Redshift, and it took almost a year.

Amazon Redshift was not helpful in improving our organization's functioning, and I believe that previously, we had a better database named Netezza in place.

It is an expensive product.

The tool can handle some large-scale datasets for our company since we use data shares.

I am satisfied with the performance of the product.

The product is able to fulfill my company's needs associated with data analytics.

Amazon Redshift is used as a storage tool.

I rate the tool a seven out of ten.