MongoDB vs. Oracle Observability and Management

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.

Incentivized

Ideal for a complex organization with requirements to build very complex reports. Especially useful for organizations that already have numerous Oracle products and need to pull information from them. This tool works best when plugged in with other Oracle tools and databases. If you're a larger company, and/or if you're managing a lot of data, Oracle IT Analytics Cloud Service is the perfect tool to manage your Oracle deployment. It provides a number of different options for intelligent analysis while not being too overwhelming to manage. Companies that want a robust tool to manage all data and present it in a visually appealing way to users will greatly benefit from this tool. The tool is very customizable and can be tailored to meet the needs of different users.

Incentivized

• 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.

Incentivized

• It helps in the detection and elimination of security threats.
• It enables us to detect and resolve IT issues before they impact the end users.
• It provides automatic diagnostics.
• It improves the efficiency of operations and productivity.

Incentivized

• 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.

Incentivized

• There's a pretty steep learning curve that needs to be overcome in order to properly deploy this tool. So, unless you're a seasoned IT administrator, you may have a fair amount of homework to do. Implementation and maintenance of this takes a bucket of consulting hours from outside consultants to come in and set up the tool and regularly maintain it, in the long run, this could be costly.
• The dashboard is not as easy to set up as I would like, however, after setup it will serve your purpose in the best possible way. You may not be able to find out how some data related to another and you can create a report that you think has all the details you need, but it comes up blank because the data really is not connected.
• There aren't enough self-learning materials available like tutorials and how-to videos. I would like to have access to more e-tutorials from inside the tool. A steep learning curve for most. It would be nice to have a robust learning portal within the application where users can access self-learning material directly from the application and step to spet guides on how to perform different tasks.
• Does not provide the ease of adding additional data sources without lots of complications. Even though it can handle large data sets, rendering of reports can take a fairly long time if the parameter set is large. For some time it seems like processing takes a bit of time when large data sets are being used. This is not the case with other competing tools.

Incentivized

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.

Incentivized

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.

Incentivized

Oracle Observability and Management is a valuable tool for monitoring, troubleshooting, and capacity planning

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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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The product management team is very responsive. They are on LinkedIn and Twitter, responding to your questions and offering ideas. I have not opened an Oracle support ticket for this product yet

Incentivized

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.

Incentivized

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.

Oracle Analytics Cloud is an enterprise solution and can't be compared apple-to-apple with a data visualization tool like Tableau. This is not the same use at all. Before selecting Oracle Analytics Cloud, it is most important to consider the data you are looking to collect and how you plan to visualize it. Other tools like Tableau and microstrategy feel smoother to work with, have better UI's and are quicker when processing data. It is also important to think through how you will use the data across your organizations. Can have a steep learning curve but once you are well trained on this tool, the possibilities are endless. The tool is highly customizable and will generate what you design it to generate. If you are having issues with reports and analytics, it is most likely due to data quality issues. Oracle Analytics Cloud also benefits by adding Essbase in it, to perform multi-dimensional analytics.

Incentivized

• 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

• Reduced security threats.
• Saves time taken in fixing issues.

Incentivized