We primarily use MongoDB as a database to handle large volumes of data. It's useful when we need to manage millions of records quickly.
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We primarily use MongoDB as a database to handle large volumes of data. It's useful when we need to manage millions of records quickly.
The cloud solution offered by MongoDB, known as Atlas, has been invaluable to us. It provides a good, user-friendly interface. The ease of use and scalability make it stand out compared to relational databases.
Improvements could be made in query optimization, particularly when performing lookups or joining tables. Input functions to restrict the amount of data passed in pipelines would be beneficial for this purpose. Additionally, enhancing the documentation to make it more beginner-friendly is crucial. As someone with seven years of experience with MongoDB, I find the ecosystem intuitive, but newcomers often need help with the documentation.
We have been using MongoDB for seven years now, and we are currently using the latest version.
The platform has good stability.
We contacted the MongoDB team for assistance whenever we encountered issues, particularly when optimizing queries that took too long. They helped us understand the root cause of the problem and provided us with discounts on certain occasions. For instance, when we accidentally used a larger instance, which resulted in higher costs, they understood the situation and offered us a discount to mitigate the expense.
Positive
We chose MongoDB over other solutions because it can handle large volumes of data and is flexible in data manipulation.
The initial setup process is easy.
The product is affordable, but I don't have direct comparisons with other products as I haven't been involved in the billing process.
The NoSQL structure, particularly the document-based data management, has made data management easier for me. MongoDB's approach to handling data in documents rather than traditional tables has been particularly beneficial.
MongoDB's document-oriented model improves development speed by providing each document with its built-in key or ID, similar to a primary key in relational databases. This inherent ID facilitates faster execution of operations, such as searching for specific documents. Additionally, it allows for creating additional indexes, further enhancing performance. The familiarity of JSON-like structure makes it easy for developers, both front-end and back-end, to work with, leading to quicker development and visualization of data.
I advise others to understand the fundamentals of databases and how they store data. They should start with online videos to grasp the ecosystem, focusing on concepts like data storage. The document-oriented structure with binary objects is crucial for individuals with a programming background.
Several limitations related to querying certain documents can be challenging. They express concerns about the lookup process, where we sometimes need to fetch a large amount of data simultaneously. Additionally, there are limitations regarding the size of documents, which may require restructuring or storing data.
I rate it an eight out of ten.
I am a data scientist. I use the solution to fetch and update data
It is easy to handle unstructured data with the solution. The execution is fast. The tool is easy to learn.
The product must be added to a cloud platform. The link to Oracle must be provided on the cloud platform. It will help people to integrate the tool easily. We need the solution mainly for updating or manipulating data. All DBs need a query. We need to see the processing speed and whether we can fetch more data. When we have data, we can push it in batches or push all the data simultaneously. Ultimately, it must be fast to complete the project faster. These things must be improved in Oracle.
I have been using the solution for the last four years.
The vendor upgrades the database often. I am using Python 3.8.0. I am not able to install some Oracle tools with that version.
There are 15 members on my team.
I tried contacting the support team but did not get much response. So, I contacted my IT team, and the IT personnel helped me sort out the issue. I did not get any updates from Oracle, though.
The solution is deployed on the cloud. The installation is difficult. I tried with cx_Oracle. It is too difficult. I work with a finance company. They have many privacy and governance policies. The main issue I faced was with the installation.
I also use Oracle Database. MongoDB is more difficult to learn than Oracle.
If someone is working on a project that requires JSON, they might prefer using MongoDB. The choice depends on the project and the data we use. The product is good overall. There is an issue with installation, but the processing is fast, and we can update large amounts of data. If we need more analytics, we can choose MongoDB. Overall, I rate the product a seven out of ten.
