Amazon Redshift Reviews

We are a digital transformation services company, and we are using Amazon Redshift for one of our clients. They are a logistics company that has transportation and other needs.

Their first requirement is for financial reporting, where we pull financial data from their many ERP systems and can provide a corporate-level view.

There is also an operations standpoint, where they are looking for operational insights. For this, we again pull different information from their ERPs, bring it into Redshift, and then model it in such a way that they will be able to see a consolidated view in terms of operational success across lines of business.

I've been working with data warehouses for a long time and it has always been the case that we had to invest quite a bit on infrastructure, upfront. We are used to dealing with Teradata, and the cost of setting up the data center and getting the appropriate licenses was a big deal. Now, we are able to spin up some clusters and then start using it, allowing us to incrementally pay as we expand.

This has become a big shift in how we spend because there is no capital cost upfront. Moreover, this works with startups as well as with enterprise, and they provide an equal footing. This means that even the advanced capabilities and insights that are available with a data warehouse are no longer limited to the larger clients. Even a startup can use these features, immediately.

The most valuable feature is the scalability, as it grows according to our needs.

The part that I like best is that you only pay for what you are using.

The OLAP slide and dice features need to be improved. For example, if a business wants to bring in a general ledger from an ERP, they want to slice and dice the data. What we have found is that they have a lot of formulas that are used to calculate metrics, so what we do is use SQL Server Analysis Services. The question then becomes one of adopting a single vendor and transitioning to Azure. If Redshift had similar capabilities then it would be very good.

We have been using Amazon Redshift for about five years.

The stability is awesome. We have been using it for quite a while and haven't faced any issues.

The scalability is very good. You can start at a very low scale and just keep expanding as required. It is the type of product that fits organizations of all sizes.

We have contacted support on several occasions. With our most recent customer, they are pretty large and we were directly in touch with the regional account manager, who is the head of database analytics for India. This person was directly involved in our calls and helped with the evaluation, so the support has been pretty good.

We have worked with Teradata and more recently, have been working with Azure SQL Warehouse. Teradata is an on-premises solution and the upfront costs are high. Comparing Azure SQL Warehouse and Amazon Redshift, in terms of features I think that they are pretty much on par.

The SQL Data Warehouse does have better OLAP capabilities, and they also offer a level of serverless capability where they have split the compute and the storage. This means that they can operate at a lower cost in the development environment.

Many of our clients have begun to adopt Power BI, and once they start using it, they tend to lean towards Azure and the Azure SQL Data Warehouse. The fact that Power BI is free, makes quite an impact.

The initial setup is straightforward, once you get used to it. There is a lot of documentation available.

We handle the implementation and deployment of Redshift for our clients.

I am interested in seeing a split between compute and storage, which is something that they are currently working on. We plan to start leveraging it at some point in the future.

In summary, I think that Amazon Redshift is a very good data warehouse and we really like it a lot.

I would rate this solution an eight out of ten.

We use Amazon S3 along with RedShift for storing our data. The data comes from various sources, including our client and third-parties. We get the data as an S3 file and then load it into RedShift using the ETL tools. RedShift will then act as the data source for Tableau, which is used for forecasting and other marketing activities.

The processing of data is very fast.

It would be useful to have an option where all of the data can be queried at once and then have the result shown. As it is now, when we run a query and we are looking at the results, part of the data remains to be processed at the back end. That works very well, but in some cases, we require the whole data to be queried at once and then have the results shown. We have not faced many use cases where it would have been useful, but in one or two, we used other methods to achieve this goal.

When our clients contact customer support, they don't want to speak with a machine. Instead, they want to chat with a real person who can provide a solution. Customer service bots can provide solutions but they cannot understand our problems.

I have been working with Amazon RedShift for about two and a half years.

RedShift is a stable solution.

Given that RedShift is a cloud-based solution, scalability is very good. I have not faced any issues regarding that. We have about 20 users, who are all developers.

Beyond the development stage and in terms of the users who make use of the data for Tableau, there are many people all around the world. I do not know the number, but it could be 1,000 or it could be 10,000. When it leaves us and goes into production, it is the client who takes care of it. One of the clients I am working with now has more than 10,000 personnel.

I do not have enough direct contact with the solution to see issues that would require contacting technical support. I work with the data but not so much on the technical side. It is the developers who would see these issues and would do so. The level of support is based on our subscription plan.

The company was using other solutions such as Google Cloud and the Microsoft Cloud Service, but I have not personally used these solutions.

I am very happy with what RedShift has. So far, anything that I have required has been there and whatever use case I have faced, the functionality is available.

My advice for anybody who is implementing this solution is to look into what certifications are available and which ones are required for different roles. Depending on the job, different certifications are relevant or required. For example, as a business analyst, a coding certification would not be useful for me and it would be a waste of money. These things should all be considered before beginning with any certifications.

I would rate this solution a nine out of ten.

The primary use case for this solution is related to statistical data.

The best part about this solution is the cost.

The performance of this solution is good if you have only a few use cases and a few queries, but for larger applications, it is not so good. 

Running parallel queries results in poor performance and this needs to be improved.

This solution is stable, although we have had some issues with maintenance.

The scalability of this solution needs to be improved.

We have dealt with technical support and it is ok.

The initial setup of this solution is straightforward.

The suitability of this solution depends on the environment and the requirements. For some, Amazon Redshift is perfect. However, some people will need better queries. Based on my research, many of the products are pretty close. It is possible that the much higher priced solutions have more differences.

This is a good solution but the queries need to perform better.

I would rate this solution a seven out of ten.

We primarily use the solution for analytics.

The solution's flexibility is its most valuable feature. It's also easy to scale and has relatively painless pricing. 

The speed of the solution and its portability needs improvement.

The solution is getting more stable with each new version. It's stable now, but it can always continue to improve.

The solution can scale easily.

I've never been in touch with technical support.

The initial setup was straightforward.

We use public and hybrid cloud deployment models. We are Amazon partners.

The solution itself is very popular. Many people use it these days.

I recently went to an AWS summit in Zurich. I was very impressed by AWS and the presentation. Their solutions are very good.

I'd rate this solution eight out of ten.

We are using the private cloud model of this solution. Our primary use case is for a data warehouse for BI.

The most valuable features are that it's easy to set up and easy to connect the many tools that connect to it.

Compatibility with other products, for example, Microsoft and Google, is a bit difficult because each one of them wants to be isolated with their solutions. That's a big problem now.

It is stable.

Scalability is okay. It's easily scalable. We don't have any plans to increase usage at the moment. We currently have two users directly using this solution. Indirectly we have around 50 users.

We require two staff members for maintenance and others are just consuming data from it.

There hasn't been a need to contact technical support at this point. We haven't had any technical issues. 

The initial setup was straightforward. The deployment took a few hours. 

We integrated it ourselves. 

We have seen ROI. It's been useful.

It's around $200 US dollars. There are some data transfer costs but it's minimal, around $20.

I would rate it a ten out of ten. 

We use it to build a data warehouse and a centralized location for all of our data sources, allowing for in-depth analysis by using SQL queries.

• Allows for the storage of huge amounts of data. 
• Assists users to perform ad hoc analysis on a lot sources together.

• Windows functions, such as LEAD and LAG.
• Allows you write complex queries and perform row by row processes.

In the next release, a pivot function would be a big help. It could save a lot of time creating a query or process to handle operations.

• Storing and querying data in near real time.
• Loading millions of raw CSV records.
• Running data comparisons and queries, then shutting it all down all within a few hours, once a week.

Easy to load and reload data.

• Fast load times 
• Flexibility in column definitions
• The ability to reload data multiple times at different times.

• It would be nice if it was a bit cheaper to retain data long-term. 
• Should be made available across zones, like other Multi-AZ solutions.

Per hour pricing is helpful to keep the costs of a pilot down, but long-term retention is expensive.

Redshift COPY command, because much of my work involved helping customers migrate large amounts of data into Redshift.

It helped my customers migrate off on-premise platforms such as Teradata to Redshift, at a fraction of the cost.

There are challenges with dealing with character set mismatches. Migrating data from other data sources can be challenging when you are working with multibyte character sets.

Two years.

No.

I personally haven’t hit scalability issues but at dinner a year ago with a few of my existing customers (all Fortune 500 companies), I was told there are scalability issues once you get to 32-nodes.

One of my previous customers told me they were migrating off Redshift because they hit the ceiling and had scalability issues. They told me the responsiveness they were getting was inferior to alternative solutions once your Redshift gets to a specific size.

I never utilized AWS technical support.

I’ve helped customers migrate off Teradata, SQL Server , Oracle Exadata, Greenplum, and ParAccel Matrix to Redshift. Some due to cost savings, others because of the EOL of the product.

Setup of Redshift infrastructure is pretty straightforward. I’ve been told that setting up partitions can be tricky in order to ensure good performance.

I have nothing to add here as I wasn’t involved in this part of the process. However, one of my customers went with Google Big Query over Redshift because it was significantly cheaper for their project.

I only provided advice to my customers, but some looked at Azure SQL DW , Greenplum, Netezza, and Google Big Query as possible alternatives

Be careful with vendor lock-in! You cannot move your Redshift environment to a different cloud provider or to an on-premise solution.