Amazon Redshift Reviews

• 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!

I used it as part of the Amazon Connect integration; I had to implement Redshift for a couple of customers. It's used for various use cases involving reporting and exporting data to external sources. I have also used it for some analytics integrations.

The use cases I have typically worked on involve transferring Amazon Connect data to different systems for analytics. The two or three deployments I have done with Redshift are more or less similar because it acts as a kind of data middleware. 

Redshift effectively gathers data from various sources and facilitates the integration of that data into different destinations. This is typically used for insights collection, data showcasing, and integration into a standard ETL process.

So, the overall performance and speed of Redshift have affected the query times.

For the use cases I worked on, particularly on the Connect side, the query times with Redshift are pretty straightforward. We started using Redshift for these cases, and it significantly helped. To achieve faster results from Redshift, we first need to optimize the queries. It does reduce a lot of time in how data is gathered and then presented from the queries.

For me, the most valuable feature of Redshift is the way it operates as a reliable Amazon service. It has the capability to gather data from various Amazon sources and can be easily integrated with some maintenance configuration and code; Lambda functions are required for this. It can be used in multiple places. 

It all depends on the use cases, how we can actually ship the data, and how we can use the data from multiple sources. It is a typical reliable software and works very efficiently with Amazon.

For Amazon Connect combined with Redshift, the integration is mostly straightforward. Using Redshift always depends on the use cases, as there are other methods Amazon Connect can use to achieve its goals. As for Redshift itself, it can be used to build pipelines.

When working with third-party services requires additional integrations and configurations, which can sometimes add more cost.

From the Amazon Connect side of things, we have integrated Redshift. However, as an overall product, I have limited experience. 

But from what I have experienced, whenever we do a Redshift integration, it needs to be planned carefully because although Amazon supports multiple data sources and different data consumption, Redshift needs to be configured very effectively and requires dedicated shared knowledge for successful deployments. 

Redshift is a major service of Amazon and is very scalable. It enables faster recalculations and data management, helping to retrieve data quickly. It’s a relatively old service within Amazon's offerings, with at least 10,000 customers. I've seen cases in different organizations where users experienced up to 35X times increase in throughput while using Amazon Redshift.

It's pretty much straightforward. I just need some sort of configuration and a bit of integration, and then that's it. We should be able to get that done.

For first-time usage of Redshift, the process is pretty straightforward, thanks to the documentation provided by AWS and the straightforward integration with Amazon Connect. 

It didn't take me much time to create, deploy, and configure. It’s very straightforward. However, having some prior knowledge about Redshift can speed up the process significantly. 

For me, coming from a different background and learning about Redshift for the first time, I ended up reading some database documentation and doing some trials and testing before committing the production data.

For someone who knows a bit about how databases and data warehousing work, it's quite straightforward to learn Redshift. It's easier for those involved in analysis, reporting, and ETL data warehousing, specifically database developers or data warehousing developers; they can learn it faster. 

However, for someone without this background, it might take a bit more time to understand the concepts and how they integrate in different ways.

Overall, I would rate it an eight out of ten because it has been straightforward for my use cases. It's easy to integrate for those use cases.

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.

We use Amazon Redshift to store customer data. Basically, it's just to store our customer data so that we can use our own data.

I use Redshift Spectrum a lot, so that integration is good. Also, Amazon Redshift offers a relatively flexible structure, especially in terms of like, nodes that you can assign. Moreover, it is serverless, which is great.

Specifically, with Redshift Spectrum, some SQL commands have to run on Redshift instead of Redshift Spectrum, which slows down a few things in the tool. In the solution, user-based access is quite hard. In general, certain permissions are difficult to manage. The solution is expensive compared to Snowflake. I have used Snowflake because they're cheaper than Amazon Redshift. Some of the commands are run on Redshift itself, and some of the commands are completed by Spectrum, which is problematic. However, it is faster when computed by Spectrum.

I have been using Amazon Redshift for six to seven years. Also, I don't remember the version of the solution I am using. I think it's multiple different versions across the platform. So, I think it would be the latest version for some areas of our platform and older versions for other areas. My company has a partnership with Amazon.

Stability-wise, I rate the solution an eight out of ten. I can't remember what stability issues we had faced in the past, but I feel that it was due to overloading clusters.

Once we moved to a serverless version, it became more scalable. The concurrency of queries on the same cluster has a big scalability issue. Scalability-wise, I rate the solution a seven out of ten.

Around 300 people in my company use the solution.

The solution's technical support is good since we have a partnership with Amazon and we have individual support. I rate the technical support a nine out of ten.

Positive

Previously, we were using Snowflake in our company. We switched since Amazon Redshift was cheaper. Now, I use Snowflake and Amazon Redshift.

I wasn't involved in the solution's initial installation. The deployment model is largely managed by our platform teams. Also, we have a team of engineers who constantly update and maintain the solution. Probably a team of engineers is specifically focused on improving our Amazon infrastructure.

I am not sure about the pricing of the tool since that's not my department. I know that Snowflake is cheaper to set up, manage, and store data. On a scale of one to ten, where one is a low price and ten is a high price, I rate the pricing a seven.

I recommended it for data storage. I don't recommend integrated solutions, like Pacemaker unless you have an advanced team to handle it. I like using it, but it's too expensive. So, I rate the overall solution a seven out of ten.

We primarily use Amazon Redshift for prediction modeling and business reporting.

The most valuable feature is its scalability.

The technical support should be better in terms of their knowledge, and they should be more customer-friendly.

I have been using Amazon Redshift for approximately one year.

This is a stable product.

The scalability is very good, and it is one of the best features of this solution.

We have approximately 10 people who use it, four of which are engineers. At this point, we do not have plans to increase the number of users.

The initial setup is straightforward. I do not recall, however, how long it took to deploy.

In summary, this is a good solution and I recommend it. That said, the customer support needs to be improved.

I would rate this solution a seven out of ten.

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.

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 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.