Boomi vs. MongoDB

Legacy systems often need to be replaced or integrated with new applications in order to modernize businesses. A strong API strategy that avoids custom coding and third-party programs is essential to enable this integration. Boomi's new-age connectivity and integration solutions ensure safe, secure, and robust integration. In the age of information, businesses are under more pressure than ever to be able to collect and manage large amounts of data. This data comes in from a variety of sources, including personalized devices such as voice assistants and wearable tech. While this data can be immensely valuable to businesses, they often lack the infrastructure necessary to handle it effectively. This can lead to data build-up in databases or silos, and can eventually lead to problems with integration and security.

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

• Pre-built connectors to almost anything which greatly reduce time to release of your integration needs.
• Easy to use development platform with drag&drop features. Non-technical people could build simple integration processes in no time.
• Great user community where you can get quick help if needed. Boomi people hang around there a lot.

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

• More from a development perspective. It is always difficult to use the properties features. It takes a while to understand how the data/variables can be used across an integration.
• Dell Boomi should also invest more on API Management and not just seen as a ETL,ESB tool.
• Should roll out features more often based on users reviews.

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

Dell Boomi has provided us with the ability to connect our campus together using our various existing platforms. There are many supported features and have yet to run into something that we cannot do. Its user interface is very intuitive which would allow users to begin developing fairly easily. There is a myriad of resources available

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

My IT and Finance teams have noted that setting up the tool is a breeze. Dell Boomi has never caused an issue during a system implementation that I am aware of. We are pleased with the tool and recommend others consider it.

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

The atom sphere takes a time to load, when I open a process or when I open a log. One more slow processing is when I import objects from NetSuite.

About the performance of processing, it looks like Boomi takes a time to initialize some things such as connectors before starting the process. This is also performance we have.

Incentivized

Boomi support was responsive and knowledgable, however being a closed cloud service, it doesn't have good community support. We found the learning curve to be steep and there aren't avenues like google, forums, or blogs that provide community driven insight into the product or how to go about designing solutions using the tool

Incentivized

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.

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 decided to go with Dell Boomi because another department in our company was already using the software. We did not research competitor applications to use as our business solution. Dell Boomi was very easy and quick to set up, so once we decided to use Dell Boomi for systems integration, we had it set up and running within a few working days.

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.

• It has allowed us to scale significantly without having to add headcount, specifically those geared towards data entry. We went from a $10m ARR business to $200m ARR business with the same amount of Order Processors and 12x amount of transactions by leveraging Boomi to perform a lot of the work, and then having the Order Processing team to simply review that the transaction was processed successfully.

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