FactSet Workstation vs. Amazon Redshift

FactSet works for all my IR needs. I do not see a function for which I use it for that it would be less appropriate. I believe that the tool's efforts towards becoming more integrated with AI are strong and that in time the Mercury offering will be just as competitive as some of the other AI offerings out there today such as AlphaSense

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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)

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• Easy/clear UI for navigation
• Easily find and sort through financial filings to get to the data
• Document search functionality seems to be improving consistently with more robust features

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• [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.

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• The user interface on stock monitor needs work - sometimes I wish to clone the same fields to another tab/watchlist and it appears the best way to do so is recreate it form scratch
• transcript to be more timely and more accurate
• on the consensus financial forecast tab, have more segment breakouts like Visible Alpha

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• 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.

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We need the FactSet data and capabilities to complete 75% of the financial analyses that we complete for both internal and external purposes. It is invaluable and I am not aware of any other provider that would be able to fill this gap that FactSet does

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It does everything I need. It is pretty user friendly and easy to work with whatever technology interface I am using (desk top, notebook, tablet, or mobile phone). I am able to get work done whether I am in the office, at home, or traveling. The user up time is very good. They are rarely doing maintenance when I need to use the platform

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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.

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I think the data delivery could be improved, but it's a good data set.

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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

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Product is magnitudes more affordable and provides 80% of the functionality that Bloomberg has and is working to build out the remaining. The workstation is more user friendly than bloomberg but still not perfect. Not as robust as a Bloomberg Terminal and doesn't have the chat/trading features.

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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.

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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.

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• hard to quantify, bc i havent brought any new business bc of it, so the ROI would be 0%. I use other systems for proposals.
• However, I use it for everyday work and equity/fi analysis and portfolio construction research at ticker level, and that part works 100%.

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• 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.

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