FactSet Workstation vs. MongoDB

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 asked by a colleague I would highly recommend MongoDB. MongoDB provides incredible flexibility and is quick and easy to set up. It also provides extensive documentation which is very useful for someone new to the tool. Though I've used it for years and still referenced the docs often. From my experience and the use cases I've worked on, I'd suggest using it anywhere that needs a fast, efficient storage space for non-relational data. If a relational database is needed then another tool would be more apt.

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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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• Being a JSON language optimizes the response time of a query, you can directly build a query logic from the same service
• You can install a local, database-based environment rather than the non-relational real-time bases such a firebase does not allow, the local environment is paramount since you can work without relying on the internet.
• Forming collections in Mango is relatively simple, you do not need to know of query to work with it, since it has a simple graphic environment that allows you to manage databases for those who are not experts in console management.

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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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• An aggregate pipeline can be a bit overwhelming as a newcomer.
• There's still no real concept of joins with references/foreign keys, although the aggregate framework has a feature that is close.
• Database management/dev ops can still be time-consuming if rolling your own deployments. (Thankfully there are plenty of providers like Compose or even MongoDB's own Atlas that helps take care of the nitty-gritty.

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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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I am looking forward to increasing our SaaS subscriptions such that I get to experience global replica sets, working in reads from secondaries, and what not. Can't wait to be able to exploit some of the power that the "Big Boys" use MongoDB for.

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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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NoSQL database systems such as MongoDB lack graphical interfaces by default and therefore to improve usability it is necessary to install third-party applications to see more visually the schemas and stored documents. In addition, these tools also allow us to visualize the commands to be executed for each operation.

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

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Finding support from local companies can be difficult. There were times when the local company could not find a solution and we reached a solution by getting support globally. If a good local company is found, it will overcome all your problems with its global support.

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While the setup and configuration of MongoDB is pretty straight forward, having a vendor that performs automatic backups and scales the cluster automatically is very convenient. If you do not have a system administrator or DBA familiar with MongoDB on hand, it's a very good idea to use a 3rd party vendor that specializes in MongoDB hosting. The value is very well worth it over hosting it yourself since the cost is often reasonable among providers.

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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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We have [measured] the speed in reading/write operations in high load and finally select the winner = MongoDBWe have [not] too much data but in case there will be 10 [times] more we need Cassandra. Cassandra's storage engine provides constant-time writes no matter how big your data set grows. For analytics, MongoDB provides a custom map/reduce implementation; Cassandra provides native Hadoop support.

• 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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• Open Source w/ reasonable support costs have a direct, positive impact on the ROI (we moved away from large, monolithic, locked in licensing models)
• You do have to balance the necessary level of HA & DR with the number of servers required to scale up and scale out. Servers cost money - so DR & HR doesn't come for free (even though it's built into the architecture of MongoDB