Likelihood to Recommend This is a tool geared for smaller to mid-sized business that has disparate sources of data from different platforms in varying incarnations. It’s a great ETL tool to solve the problems a scenario like that causes, but you can also achieve that with good BI Tools like
Qlik Sense . So be careful that you really need an ETL tool, as opposed to an end-use tool with a built-in ETL component. If you are going ELT and have a lot of data an not a lot of corporate resources, this is a better option than Microsoft or Informatica
Read full review If the number of connections is expected to be low, but the amounts of data are large or projected to grow it is a good solutions especially if there is previous exposure to PostgreSQL. Speaking of Postgres, Redshift is based on several versions old releases of PostgreSQL so the developers would not be able to take advantage of some of the newer SQL language features. The queries need some fine-tuning still, indexing is not provided, but playing with sorting keys becomes necessary. Lastly, there is no notion of the Primary Key in Redshift so the business must be prepared to explain why duplication occurred (must be vigilant for)
Read full review Pros Quick response for queries involving multi-million rows Low cost Read full review [Amazon] Redshift has Distribution Keys. If you correctly define them on your tables, it improves Query performance. For instance, we can define Mapping/Meta-data tables with Distribution-All Key, so that it gets replicated across all the nodes, for fast joins and fast query results. [Amazon] Redshift has Sort Keys. If you correctly define them on your tables along with above Distribution Keys, it further improves your Query performance. It also has Composite Sort Keys and Interleaved Sort Keys, to support various use cases [Amazon] Redshift is forked out of PostgreSQL DB, and then AWS added "MPP" (Massively Parallel Processing) and "Column Oriented" concepts to it, to make it a powerful data store. [Amazon] Redshift has "Analyze" operation that could be performed on tables, which will update the stats of the table in leader node. This is sort of a ledger about which data is stored in which node and which partition with in a node. Up to date stats improves Query performance. Read full review Cons As I said before, more training or greater visibility to training tools/options would be a plus. It’s easy to publish YouTube videos these days, I think they should make more of them. Differentiation would help, there’s not a lot out there to drive you to buy the product if you are well informed in the market. If you know the market, you steer towards the large or trendy products. It’s a good product, but lost in the noise of the field I think. Hitching the wagon to a major software brand (like Mule did to Salesforce) would help grow the user base, and thus increase the activity in the support community. More users also translates into product champions. Read full review We've experienced some problems with hanging queries on Redshift Spectrum/external tables. We've had to roll back to and old version of Redshift while we wait for AWS to provide a patch. Redshift's dialect is most similar to that of PostgreSQL 8. It lacks many modern features and data types. Constraints are not enforced. We must rely on other means to verify the integrity of transformed tables. Read full review Usability Just very happy with the product, it fits our needs perfectly. Amazon pioneered the cloud and we have had a positive experience using RedShift. Really cool to be able to see your data housed and to be able to query and perform administrative tasks with ease.
Read full review Support Rating The support was great and helped us in a timely fashion. We did use a lot of online forums as well, but the official documentation was an ongoing one, and it did take more time for us to look through it. We would have probably chosen a competitor product had it not been for the great support
Read full review Alternatives Considered Oracle>DB2>MS SQL Server>GreenPlum>Vectorwise
Read full review Than
Vertica : Redshift is cheaper and AWS integrated (which was a plus because the whole company was on AWS).
Than BigQuery: Redshift has a standard SQL interface, though recently I heard good things about BigQuery and would try it out again.
Than
Hive :
Hive is great if you are in the PB+ range, but latencies tend to be much slower than Redshift and it is not suited for ad-hoc applications.
Read full review Contract Terms and Pricing Model Redshift is relatively cheaper tool but since the pricing is dynamic, there is always a risk of exceeding the cost. Since most of our team is using it as self serve and there is no continuous tracking by a dedicated team, it really needs time & effort on analyst's side to know how much it is going to cost.
Read full review Return on Investment We had to move out of VectorWise after using the database for 2 years. Hence no positive impacts. Read full review Our company is moving to the AWS infrastructure, and in this context moving the warehouse environments to Redshift sounds logical regardless of the cost. Development organizations have to operate in the Dev/Ops mode where they build and support their apps at the same time. Hard to estimate the overall ROI of moving to Redshift from my position. However, running Redshift seems to be inexpensive compared to all the licensing and hardware costs we had on our RDBMS platform before Redshift. Read full review ScreenShots