Amazon Redshift Reviews

We use it for data warehousing. Currently, I'm setting up a data link with Redshift to fetch data from our data lake.

The most valuable feature of Redshift is its cluster.

Redshift's serverless technology needs to improve because not everyone is technically inclined. Organizations want to quickly access and import data into their data warehouse without hassle.

Redshift's ETL tool, Glue, is not seamlessly integrated with Redshift. I've encountered many instances where it couldn't fetch the perfect data type from the source, which should be intuitive. Snowflake's ETL tool, on the other hand, is more intuitive and seamless.

I have been using this solution for two years. I am working with the latest version.

I haven't faced any stability issues because when it works, it runs continuously.

The initial setup is a complex process, especially for someone who is not familiar with nodes and configuring terms like RPUs. You need to consult the documentation to understand what an RPU is.

Moreover, Redshift can be difficult to maintain, especially the Redshift cluster instance.

When it comes to the initial deployment and implementation process of Redshift, there are two types of nodes to choose from: DC2 and RA3, which are for different requirements based on the load. One is for storage, one is for storage and checking, and one is for the computing center.

First, the user needs to know their exact requirement, unlike Snowflake, which automatically scales up and down based on the requirement using the Retrieval Service tool.

The service has not matured yet, and for the Redshift cluster, scaling has to be done manually. The cluster also needs to be set up manually, which is not ideal, especially when Snowflake is already in the market.

It is easy to deploy if you already know how to use Redshift. But if I were a new customer, I might need assistance.

Redshift is a bit less costly than Snowflake, but the effort justifies the cost for Snowflake.

I would suggest starting with a three-cluster that is DC two large, especially if you are setting up a cluster-based search. We offer a three-month or one-month trial, which will allow you to see if you can handle the manual scaling up, scaling down, and maintenance of Redshift. If not, then you can switch to a serverless data solution.

Overall, I would rate it a seven out of ten.

We use Amazon Redshift for our data warehouse to store a lot of our data for a client.

The most valuable feature of Amazon Redshift is its ability to handle really large sets of data. In our case, the solution does a lot of things that would be difficult to do otherwise.

Amazon Redshift is a little more expensive than other products.

I have been using Amazon Redshift for four years.

Amazon Redshift is super stable, and we haven't faced any outages or other issues.

The solution's scalability has been fine regarding how much data we can load into it. Once the solution is set up, we pay for what we use. Three people are using the solution in our organization.

Users should select Amazon Redshift depending on what their needs are. Amazon has other cheaper database products, but Amazon Redshift is a really good option for users who need a lot of computation.

Overall, I rate Amazon Redshift ten out of ten.

We use this solution for production and customer data for one of the lines of the business, which is basically one of the warehouses. I oversee the whole architecture infrastructure.

The price isn't bad for the performance for a cloud data warehouse. It's also connected to Databricks but uses SQL. It's comparable to BigQuery. If the analyst knows SQL, which is comfortable and easy to use to go between all of these tool stacks, I think it's reliable. It's a secure and reliable data warehouse.

The performance is good, and it's pretty fast. We also have Looker and MOLE connected to it for visualization, which works seamlessly. We're storing a lot of data. There's a lot of transactional data, clickstream data, and telemetry about the customer, what they're purchasing, call logs, and marketing data.

The analysts are familiar with SQL, and they're able to do this. Even the data scientists who aren't that savvy in Python, because they are very strong in SQL, are able to interact with it very quickly. I'm able to bring in more analysts for support.

There are physically too many pipelines for a company of this size to maintain. For a data scientist, it's very difficult to learn the data in all of these different environments. It's easier to train people in just one environment to start with, like Snowflake or Databricks. It's difficult to have so many technologies that are very comparable, and each comes with a price tag.

I have used this solution for seven months in my current company, but I have also used it in a couple of my previous companies.

The stability is good. For a mid-size company, it's very stable.

It's very scalable.

I would rate the technical support as 10 out of 10.

We had one or two tickets, and they responded extremely quickly. Technical support is good, but that's because we aren't running into many issues. The solution is pretty stable. The individuals who set it up did a very good job.

It wasn't too complex because only a few people were needed to set up the solution.

It's not very pricey compared to other tools. I would rate the price as 5 out of 10.

In my organization, we also use GCP, Amazon EC2, Databricks, and Snowflake. We also have Delta Lakehouse. I'm going to move everything into the Delta Lakehouse. For a company of this size, it's a lot of tools to physically maintain with a small data engineering team.

I think Snowflake has a few more features. In Redshift, you need to write a bit more SQL in some instances, but it's very user-friendly and fast. It can be used as a data warehouse solution as well. It can also do some analytics.

Redshift is comparable to other solutions. I wanted to go with Amazon EC2 because we also have Databricks, and I think I can cover some of those features with the combination of that.

I would rate this solution as eight out of ten. It's a very strong solution.

My advice is to do your research and see if it makes sense for you. You can always request a demo from Redshift.

I have used DBeaver to connect to SAP Amazon Redshift and my main use case is for SQL. I map data from a graph database into SQL.

Amazon Redshift has benefited the company by allowing us to scale. 

The solution could improve in handling more data formats and more native support for RDF.

I have been using Amazon Redshift for approximately one and a half years.

The stability of Amazon Redshift is good.

Amazon Redshift is a scalability solution.

I have not used technical support. If I need support I ask my colleagues.

The initial implementation of Amazon Redshift is simple. There was not anything difficult about getting started with the solution.

It's important to have a grasp of the environment you're working in, including a basic understanding of Amazon AWS. Additionally, when selecting an interface to work with, it's essential to choose wisely, as you'll likely be using it for an extended period of time.

I rate Amazon Redshift an eight out of ten.

My primary use for Amazon Redshift is for analytical purposes.

In terms of valuable features, I like the columnar storage that Redshift provides. The storage is one of the key features that we're looking for. Also, the data updates and the latency between the data-refreshes are valuable.

Pricing is one of the concerns that I have because if you compare Snowflake with Redshift, it provides some of the same services, but at a much cheaper rate. So pricing is one of the things that it could improve. It should be more competitive.

Otherwise, everything else looks good, especially the data storage and analytical processes.

I just started using Amazon Redshift. I'm still learning about the product and about how the pricing and the dynamic skilling are done.

I understand that Amazon Redshift is quite stable and it has features like higher readability. So I think it should be a good product to be used.

I have not been in touch with support but I will be needing their support in the near future to help me set up the environment.

In terms of the initial setup, as I said I've still not started using it, so I pray that it's going to be pretty easy for me to set it up.

Of course I would advise others to choose Amazon Redshift, as long as pricing is not a concern for them.

On a scale of 1 - 10, where 1 is the worst and 10 is the best, I'd give it an 8.

We use the solution to build a data warehouse schema for a target database for analytics. We are uploading data from different transactional databases into Amazon Redshift. We use it for reporting purposes. We use the tool mainly for querying and retrieving the data for analytics.

The fast querying of a huge amount of data greatly impacts our data workflows. All the queries work pretty fast.

Amazon Redshift is a really powerful database system for reporting and data warehousing. I like the product. It works really fast with significant volumes of data. The product covers all the main functionalities required for our data security and compliance needs. It has almost everything we need. It is the main data source for our analytics functionality. We can run our models using the data stored in the database. The ease of use is fine. It is pretty easy to integrate the solution with other products and third-party solutions.

The product must provide new indexes that support special data structures or data types like TEXT.

I have no complaints about the product’s stability.

The tool is scalable. About 30 to 50 analysts use the solution in our organization. We need one or two people to administer the solution.

I haven't heard any complaints about the support team from our DevOps engineers.

My project involves analytics and data warehousing. I use Amazon Redshift. I also use AWS Glue as an ETL tool.

I will recommend the product to others for data warehousing and data analytics. However, I do not recommend the solution for small companies that do not have enough volume of data to analyze. Overall, I rate the product an eight out of ten.

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.

It is scalable, easy to use, and has very good query performance. It is serverless as well.

They introduced machine learning directly in to Redshift, and you can now query using machine-learning functions.

It's very easy to migrate from other databases to Redshift. There are migration tools dedicated for this purpose, enabling migration from other databases like MS SQL directly to Redshift. The majority of the scripts will be automatically transposed.

AWS Snowflake has a very good feature for cloning databases. It makes it easy to clone a data warehouse, which is useful. I would like to see this feature in Redshift. 

We have been using Amazon Redshift from 2013.

For stability, I would give a rating of ten out of ten.

We have 16 Redshift users in our company, and I'd rate the scalability at ten out of ten. 

Redshift's technical support has been great.

The initial setup is simple.

In comparison to the price of similar solutions, Redshift's cost is the lowest.

I would recommend Amazon Redshift and would rate it at nine on a scale from one to ten, where one is the worst and ten is the best.