Microsoft Excel vs. MongoDB vs. SQLite

I don't really know another program as powerful as Excel. I've used Google Doc programs but do not feel they come close. So far, anytime I've needed a table of some sort for data, whether it's budget oriented or information off a survey, the best system has been Excel. We do web audits on occasion and we create an Excel worksheet featuring every URL of the pages we're auditing, notes, data about the content, information about files attached to the page and other information to help us determine what pages need updating, deleting or otherwise. We also use Excel primarily to export our Google Analytics to in order for us to create reports for clients that need to see specific information about their traffic.

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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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SQLite is a lightweight and efficient database management system. With SQLite, performance increases as memory are added. It's reliable and well-tested before release. SQLite handles memory allocation and I/O errors gracefully. SQLite provides bug lists and code-change chronologies. All bugs are disclosed, and it's compatible with iOS, Android, MAC, and Windows. SQLite is open-source, allowing developers to tailor it to their specific needs.

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• It is very good at embedded formulas and tying cells to one another
• It allows me to compare deals terms on a side-by-side basis and talk my clients through it easily.
• It is very helpful as well in terms of allowing me to filter/sort results in many different ways depending on what specific information I am most interested in prioritizing.

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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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• Our products are using SQLite in embedded Linux and in Windows software.
• It is truly a stable cross-platform database.
• The fact that it is a zero-configuration database engine, it is particularly a nice advantage when you work in the embedded world.
• Being a single database file, it provides ease for those who need to quickly transfer data to someone else, or quickly browse data.

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• Excel offers collaboration features that allow multiple users to work on the same spreadsheet, but managing changes made by different users can be challenging. Excel could improve its features by offering more granular control, better tracking of changes, and more robust conflict resolution tools.
• Itcan be a barrier to productivity when importing and exporting data from other applications or file formats. To improve its features, it should offer better support for standard file formats and more robust error handling and reporting tools.
• Excel can be challenging for finance students and working professionals, but it can be improved by offering more robust tutorials, better documentation, and more user communities and support forums.

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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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• Although it is excellent at what it does, you should be really careful and plan accordingly if you know that your database is going to scale at a huge level because it is not suitable of databases which are of Enterprise level and demands top-notch security and protection.
• If your project involves multiple people working on the same database simultaneously, then that becomes a big problem, because it only allows single write at one time. You really need to be forward thinking in a manner to predict if this database will cater to all the needs of your project.
• The most common difficulty with this is the lack of some of the basic functionality which is present in the other premier databases like Joints, Stored Procedure calls, Security and permission grants. If you do require all those things then you are better off not using this software.
• Lastly, if you are using this in an Andriod App development cycle then also your options are limited because it does not integrate with PostgreSQL and MYSQL.

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Excel remains the industry standard for spreadsheets and has maintained simple and straight-forward formula writing methods. Although there is a learning curve to do more complex calculations, there are countless help sites and videos on the Internet for almost any need.

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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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I'm giving it a 7 because it is my go to. But the fact other prefer Google Sheets when working with a team does get irritating. I've used the online version of Microsoft Excel that other teams can get into and it still seems behind Google Sheets. It's a little clanky and slow? If that's even a term.

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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 have given this rating cause its irreplaceable in some of the areas like no more installation need except from a single library. I find dialect is simple in use cases. its suitable for any professionals with various skill levels. its easily connect with various os and devices. very less maintenance or administration required.

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I have rarely, if ever, had issues with its availability.

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Excel load and performs calculations immediately. It integrate well with all Microsoft Office applications and does not slow them down.

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I have not had to use it often, but it is good.

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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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I haven't needed support yet.

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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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Out of Microsoft Excel, Microsoft Power BI, IBM SPSS, and Google Sheets, Microsoft Excel is by far the most common tool used for anything data-related across organizations. Accordingly, our organization has also implemented Microsoft Excel as a first-step tool. We recently adopted Microsoft Power BI (the free version), and use it occasionally (mostly for creating dashboards), but it is less commonly understood by stakeholders across our organization and by our clients. Accordingly, Microsoft Excel is more user-friendly and because of its popularity, we can easily look up how to do things in the program online. Google Sheets is a comparable alternative to Microsoft Excel, but because it's cloud-based and we have sensitive data that needs to be protected, we chose against using this software. Finally, a few users (including myself) have access to and utilize IBM's SPSS. For my role, it's a helpful tool to do more rigorous analyses. However, because of its cost and limited functionality as a simple spreadsheet, we only use it for more complex analyses.

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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.

We looked at other traditional RDBMS products, but found them to be cumbersome to deploy. They take up more space, and consume more computing resources than SQLite does. While the performance or direct integration to our primary applications may have been better or easier if we had gone with a traditional RDBMS, the performance of SQLite has been more than acceptable. The performance and speed to deploy made SQLite a much more attractive option for us than a traditional RDBMS.

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N/A I was not involved in this process.

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Each user can use it to whatever level of expertise they have. It remains the same so users can contribute to another's work regardless of whether they have more or less expertise

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• Excel has positively impacted the business as it has increased our efficiency.
• It also saves us the time that we would have spent on making the calculations that it does for us.
• Since it works on all devices and is compatible with both Windows and Mac, we do not have to invest in any other alternative.

• 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

• No licensing fees has a net increase on ROI
• The active community has kept support costs low, further increasing ROI
• The wide range of supported platforms and high level of compatibility has increased ROI by reducing time spent porting the database model to any platform specific solutions.

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