Amazon Redshift Reviews

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.

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.

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.

If you want to create an enterprise data hub, that is where Redshift is used. Snowflake, Redshift, BigQuery, and Azure Synapse are enterprise data warehousing and cloud data technologies. Large enterprises have enterprise data. They have a lot of managed processes, business processes, customers, products, different assets, locations, equipment, etc. Then they have sales and marketing. There's a huge amount of data that is generated, and they will need a large warehouse or multiple data warehouses to create analytics out of that data.

We try to tell organizations to consolidate all their data into a single unified data platform that has all the enterprise data rather than being processed by multiple warehouses. It's processed on one central data platform, which is cloud-based. In which case, we recommend one of these four. We either recommend Snowflake, Azure Synapse, AWS Redshift, or Google BigQuery. It depends on what their early investment is and what kind of work they need to do.

Redshift is completely Managed on AWS cloud.

I would like to see improvement in the pricing and the simplicity of using this solution.

The product is very stable, and so are all other cloud-based managed Enterprise data platforms (Snowflake, BigQuery and Azure Synapse)

It's scalable as it's on hosted and Managed on AWS cloud.

Technical support is great, very professional.

Neutral

I would recommend Snowflake the highest, then Google BigQuery, Azure Synapse, and then Redshift.

If somebody is heavily invested into Microsoft, then going for Azure Synapse is what we recommend. If they're open to moving to a completely new system, we evaluate the landscape and we recommend either Snowflake or Google BigQuery. What we recommend and what we design and create and implement for our different enterprise customers is very different for each customer. There's no One-size-fits-all solution.

For example, for one of our customers, we have helped design and create their entire single unified data platform using Snowflake.

I would say Redshift needs a little more effort and expertise for setting up the kind of infrastructure one need. If you can do something with two-three people for Snowflake, you would need four people on Redshift. You need to have a little bit of knowledge of the AWS Cloud and AWS services to be able to use Redshift. A typical Redshift based Enterprise data work would need anywhere between 4 to 15 people.

The return on investment of moving from an on-premise to a completely cloud-hosted data platform is significantly high and worth the effort.

Redshift is costly compared to other solutions.

It's pay per use. You can have multiple models. You can go for yearly cost, which is a little discounted than the monthly cost. Depending on how much data you process and store, you can have different pricing. There's no fixed cost. All of these are based on how much data you store monthly and how much data you process.

I would rate this solution 6 out of 10. 

If an organization has invested heavily in AWS services and they have a good knowledge of the AWS ecosystem, then I would recommend Redshift. Otherwise, I would still recommend Snowflake because Snowflake works very well with AWS services. I can have my AWS S3 buckets in which I can store my enterprise data lake, and then Snowflake works with that seamlessly. If the organization has good knowledge of AWS and good knowledge of RDBMS data warehouses, then we can recommend Redshift to them.

It all depends on how much investment that organization has done in Redshift. For example, we have a customer which has a very large setup. It's a large US-based company, where they have invested heavily in AWS. They're an AWS house, so they like everything about AWS. For them, we have recommended Redshift so that the overall tech ecosystem remains optimum. 

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. 

• Performance: Very fast query performance due to columnar-storage databases that leverage the Massively Parallel Processing (MPP) capabilities of its data warehouse architecture.
• Petabyte-scale data warehouse, without any loss in performance and low cost: One of our existing customers stores more than 500 terabytes of data in an AWS Redshift database and the warehouse performance was good. We want to highlight that even if the warehouse size increases to petabytes, Redshift would still work fine and there wouldn’t be any performance issues and would cost less also.

The end users were able to have access to real-time analytics.

We would really like to see a few more connectors included that would enable connecting with other databases and services. We have faced some difficulties pulling data from Teradata and storing it in Redshift. There is no direct connector available between Teradata and Redshift.

We are working with this product for the past 24 months.

We have not faced any stability related issue so far.

We did not encounter any scalability issues in the last 24 months that we have been working with Redshift.

We actually had to reach out to technical support a few times and they were really helpful and solved our problems. We would give it 4/5.

We were using an on-premise MySQL data warehouse. To reduce the cost and improve scalability, we switched to a cloud version of data warehouse databases.

Initial setup and configuration was pretty straightforward. First, we needed to create a Redshift cluster. Once the cluster was created, we created a database schema based on our need in the Redshift cluster.

AWS Redshift is one of the fastest and most cost-effective cloud-based databases. They have charged $3330 per TB/year for the ds2.8x large instances which have 244 GB RAM, 36-core CPU, 10Gbps network and 16 TB HDD.

You need to design the database structure with best sort and distribution keys, along with primary and foreign keys.

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.