We are using Amazon Redshift as our main data warehouse to store most of our data, the whole process consists in extract the data from different sources, we do some transformations when needed and the data is finally stored in Amazon Redshift in order to be used afterward by one of our Business Intelligence tools.
Pros
Easy setup (if you are on AWS Cloud Environment, just few clicks)
Easy learn (Good documentation)
Speed
Cons
It could bring some more features like we do have in Snowflake (Mainly the UI)
Likelihood to Recommend
If you are looking for a data warehouse where you don't need to worry about maintenance and scalability, Amazon Redshift should be one of your options once it is a self-managed data warehouse with many connectors and easy usage as well. Besides that, if your environment runs on AWS, it is even easier to integrate.
VU
Verified User
Analyst in Information Technology (10,001+ employees)
Amazon Redshift is primarily used as a data management solution by Product Analytics Group. We currently have various sources of capturing data like Heap, Delighted, Salesforce and it is convenient to build an ETL from these sources to Redshift. This enables us to merge all these data sources into single view in a BI tool like Power BI
Pros
Ease of setting up ETL
Uploading data into Redshift via AWS
Querying is quick
Cons
Missing option to restrict duplicate records
Lacks complex data sets like udf
Does not offer UI based querying & visualisation option like Looker
Likelihood to Recommend
It is well suited in scenarios where you have distributed data sources and would like to build an ETL pipeline with limited data engineering efforts. Operations time and cost is relatively low compared to other tools. Also it offers great connectivity with Heap with no technical know-how required. It is mostly self managed and reliable.
I am working with an insurance client where a lot of claims and policy data comes in every day, we use amazon redshift to perform ETL and analyze the data to gain business insights. Amazon redshift is an integral part of our data analysis.
Pros
Amazon redshift is super quick due to its Massive parallel processing
Amazon Redshift is compatible with many visualization tools which helps visualize the insights
Amazon redshift has almost 0 downtime and allows for a massive store of data
Since Redshift is a part of a larger AWS ecosystem, connecting with other resources is never a problem
Cons
Amazon redshift could have more detailed documentation including practical examples
Amazon redshift still lacks some of the advanced concepts which are possible with MS-SQL and others
It should have a feature where users can visualize the data stored for a better understanding
Likelihood to Recommend
Amazon redshift is best suited for data analysis and is not suited for transactions. for eg. you can use amazon redshift to gain insights from a large data set but cannot use it to do a transaction level update and insert
We use Amazon Redshift for our insights platform in our R&D space. Our team creates reports and dashboards on tools for business use. Amazon Redshift provides greater supply chain visibility, increased information on product movement, and high efficiency at a much faster rate.
Pros
Robust as compared to traditional database/data warehouse
Offers significant query speeds
Low cost of ownership
Cons
Provides MPP only for AWS-supported storages
Prerequisites for configuring tables are not easy
Not great for use with web apps
Likelihood to Recommend
Amazon Redshift performs extremely well for reporting/analytics data and is way ahead of other competitors. The biggest challenge is migrating data from on-premises databases to Amazon Redshift. The initial hurdle is a major one.
VU
Verified User
Project Manager in Information Technology (10,001+ employees)
Amazon Redshift is being used by some departments of our company to bring solution to data warehouse. Our data center was not large and scalable enough to have big scale data warehouse. So we take Amazon Redshift as one of the data warehouses we use to help us in data transformation.
Pros
It is very powerful, can hold anything you have.
It is scalable. Small or big, it can help you.
It is very fast. Can spin up cluster in minutes.
Cons
As data warehouse, it does not support fast I/O.
Learning can take more than expected.
You are not managing your data 100%.
Likelihood to Recommend
If you do not require a fast I/O rate. And frankly you should not expect that from data warehouse. And if you do not mind that your data is on cloud and only on AWS, and if you want a scalable and fast implementation of data lake, then you should consider Amazon Redshift.
VU
Verified User
Engineer in Information Technology (10,001+ employees)
My team is handling all the marking activities for all different product verticles for our company. We get a lot of streaming data that we focus on marketing. We also store this data carry out annual audits and aggregations to analyze our marketing progress. Amazon Redshift helped us with this, and it was a breeze enabling it in our environment as we were already on AWS.
Pros
Replication is excellent, we did not have to worry about reliability.
Their auto-scaling feature came to our rescue when it came to cost management.
Cons
It became expensive over time as the data increased over time.
It could not separate users from using the same infrastructure.
Likelihood to Recommend
The initial costs were very low, and it was super easy for us to spin up databases. Also, setting up multiple instances were easily managed with just a click of a button.
The costs increased gradually, and it became more expensive than planned. The query analyzer was not up to the mark and needed constant support from the AWS support team. Gladly they were willing to help and had a good experience with them.
We are performing a POC (proof of concept) across multiple cloud vendors, and we have evaluated GCP, Azure, and Amazon. We plan to go on-site cloud from on-premises, and we will evaluate all databases across all cloud providers. We are making the current database over Amazon Redshift, if it can help us do the exact same job as we have on-premises SQL Server. The on-prem option is good for replication and security, and we are evaluating how good it can be on ML application support.
Pros
Robust
Great UI
Cons
Price
Implementation in non AWS server
Likelihood to Recommend
Except for the price, Amazon Redshift is a great tool and has the fastest performance across all the data warehouses we have seen. It's easy to connect with Talend, which makes it a better option to use. I like the UI better than most of the other DW. Overall it's a great DW tool.
Redshift is our data warehouse used by our organization. It takes data from different sources and put them together in Redshift for our Analytics team to diagnose.
Pros
Since it's part of AWS it is fairly quick and easy to set up.
You can add nodes fairly quick to expand the data needs.
Performance from the analytics reports accessing Redshift is really good.
Cons
Better database management when looking up table metadata or sizes of tables.
Need a better query analyzer.
Finding errors during a data load can be a little daunting at times.
Likelihood to Recommend
It's very cost-effective from other databases we were using for our data warehouse. It was really easy to set up and it used our ETL tools to migrate data from different data sources. We added functionality add aggregate the data set for our Analytics team to analyze.
Amazon RedShift is used in all departments and accounts. This tool is newly integrated into the system so as to work with the data on the cloud. There are various projects which are moving from SQL servers to ARS because of its capacity of working and managing the data in the cloud.
Pros
We can connect with multiple servers and can fetch the data easily from one server to other.
It supports the syntax of the bots of the SQL servers, MS SQL and Oracle SQl. This makes it pretty handy to use.
Here we use views instead of tables, so we can clearly see the flow of data.
Cons
It works very slow in the cloud environment.
No statistical inbuilt functions are available within the tool.
Its user interface is not very attractive.
Often it goes into deadlock state, which kills the running jobs.
Likelihood to Recommend
Amazon Redshift is well suited for fetching data from multiple different sources and servers, and it is very easy to learn how to use this tool. It is less appropriate for situations where you may need to process only limited rows, as this takes a large amount of time since you cannot create multiple tables in it.
Capital One has many LOBs (line of businesses). I have supported IAM and Commercial LOB. They are using Redshift as a data warehouse solution. Oracle is not a Data Warehouse solution but was being used when the application was on on-premises. When they wanted to migrate all data to the Cloud, they chose Redshift as a solution to move the data from Oracle. Oracle is not a data warehouse solution. Redshift has been found as a good solution because of its unique features such as its MPP architecture, columnar architecture, and storage capacity.
Pros
User-experience. The user wants something quick to view the output, rather than spending too much time
preparing a code prior to seeing the output. Redshift provides SQL type queries. This makes any user happy and comfortable.
Architecture is very straightforward and simple to understand, such as MPP architecture, Encryption, and Columnar database design. We can easily address issues and help others to understand.
Scalability. We can scale-up and scale-down based on our workloads.
Performance tuning and database optimization can be done using the system tables and advisors. These solutions are similar to the solution available for Oracle SQL Server. It makes it easy to do the optimization for queries and databases.
Cons
The concurrency and scale up based on it could be improved. It would be good if it scale-up and scale-down the memory/CPU capacity automatically based on workload.
Often we experience slow on queries and dashboards. Self-tuning option in WLM does help.
Optimizing the areas such as Vacuum and reorganize the column data (sorting over time) automatically.
Likelihood to Recommend
Amazon Redshift is good for when you need a Data Warehouse solution or a user-experience such as SQL kind queries. It is also good if you have limited budget constraints. It's not suggested when someone has DML queries such as INSERT, UPDATE, DELETE.
