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Using MongoDB: Leveraging Capabilities While Handling Obstacles
What do you like best about the product?
A document-oriented data architecture is used by the adaptable and scalable MongoDB database, which enables dynamic schemas and simple changes to document structure. Comprising grouping, filtering, and converting data is made possible by its strong query language and indexing features. Because MongoDB uses sharding—a horizontal scalability technique that divides data across numerous servers—it is exceptionally well-suited for managing large-scale data and high-throughput applications. Data redundancy and failover are ensured by its built-in replication and high availability features, which also minimize downtime and guarantee data integrity. All things considered, MongoDB is a useful option for contemporary, data-intensive applications.
What do you dislike about the product?
When compared to traditional databases, its implementation can be less resource-efficient and straightforward, which makes it challenging to manage scenarios needing complicated transactional consistency across several documents. Furthermore, inconsistent data in sharded clusters might result in performance bottlenecks and unequal data distribution. Because of MongoDB's flexible design, inconsistent data structures may result, which could affect the quality of the data and complicate application and query logic. For applications demanding higher consistency assurances, MongoDB's default setup for Write Concerns and Read Concerns may not be ideal. Careful customization is therefore necessary. To overcome these obstacles and capitalize on MongoDB's advantages while minimizing its drawbacks, meticulous preparation and knowledge are needed.
What problems is the product solving and how is that benefiting you?
To create data-intensive applications, like IoT storage solutions and social media analytics systems. Because of its document-oriented data format, changing data requirements may be accommodated without requiring significant schema migrations, allowing for agile development and iteration. Due to its scalability, MongoDB can easily expand without compromising speed, making it an ideal solution for managing large datasets and high-throughput applications. Consulting businesses may create complex analytics and reporting solutions by utilizing its advanced querying and indexing capabilities to pull important insights from a variety of datasets. These functionalities are essential for creating data visualization apps, business intelligence tools, and custom reporting dashboards that are suited to the individual requirements of clients.
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Great NoSQL DB with few limitations
What do you like best about the product?
MongoDB is great NoSQL document db that offers features horizontal scaling, schema less architecture, good third party support
What do you dislike about the product?
Limited support of ACID transactions and complixity of sharding
What problems is the product solving and how is that benefiting you?
We are using MongoDB to track and report on the employees activity. This involves aggregation queries, geospatial queries and stored scripts to support an APIs for in house web application.
Quick DB
What do you like best about the product?
Ability to handle growing data volume, evolving data models.
What do you dislike about the product?
Learning ios required to make full use of the product.
What problems is the product solving and how is that benefiting you?
Ingest volumes from any data model.
Best NoSQL Database sofar
What do you like best about the product?
Easy to define schema and easy to use dashboard to configure and deploy your database.
What do you dislike about the product?
I personally don't dislike anything about mongodb.
What problems is the product solving and how is that benefiting you?
We were using mongodb to strore audit events for our application which has variable number of columns and way to much data, mongodb was best solution to cater that.
Best Non RDBMS for better debugs for Data storage
What do you like best about the product?
Many clusters available to practice and get the output based on indexes and queries
What do you dislike about the product?
Altas connection is not much seured and not much scope of usage for free cluster
What problems is the product solving and how is that benefiting you?
Platform available to test the Database and use it in hybrid platforms.
Also microservices can be integrated with the azure platform with the database integration
Also microservices can be integrated with the azure platform with the database integration
Best Open Source NoSQL database able to store large volume data effeciently.
What do you like best about the product?
Many popular SQL-based database technologies can help us to store structured data, however, when it comes to storing a huge volume of semi-structured, MongoDB which is a NoSQL-based database is one of the best in the business. It gives us the flexibility to store the less structures business application data seamlessly.
What do you dislike about the product?
Though MongoDB can store our data in large volumes smoothly It is less flexible when it comes to retrieving that data stored in multiple collections, As MongoDB doesn't support the Join feature amongst multiple collections for data retrieval. This causes data duplication and intervention of ad-hoc back-end code to perform join manually.
What problems is the product solving and how is that benefiting you?
Nowadays, we have humongous unstructured application data being generated daily which we want to store for various business purposes. MongoDB proves useful to do this for us, It is flexible enough to store our unstructured data, Also its open-source verbose documentation really benefited me to easily start using this from day one and learn at a faster pace, Moreover, Its auto-scaling and replication features strongly enables me to have high availability of my business data across the multiple users.
MongoDB: Flexible and Scalable NoSQL Database
What do you like best about the product?
One of the aspects I appreciate the most about MongoDB is its flexibility. The document-oriented data model allows me to work with JSON-like documents, making it easy to handle and manipulate data in a way that aligns with the structure of my Node.js applications.
What do you dislike about the product?
Compared to relational databases, MongoDB requires more careful planning for certain types of queries or complex relationships. Join operations, for example, are not as straightforward in MongoDB due to its denormalized approach, which can sometimes result in more complex code.
What problems is the product solving and how is that benefiting you?
MongoDB solves several problems that benefit me as a backend developer.
Firstly, it offers a flexible data model that eliminates the constraints of rigid schemas.
MongoDB's scalability and performance capabilities enable me to handle large volumes of data and high-traffic workloads efficiently.
MongoDB's integration with Node.js and its rich ecosystem of libraries streamline the development process.
Overall, MongoDB's solutions enhance my productivity, flexibility, and scalability resulting in faster development cycles.
Firstly, it offers a flexible data model that eliminates the constraints of rigid schemas.
MongoDB's scalability and performance capabilities enable me to handle large volumes of data and high-traffic workloads efficiently.
MongoDB's integration with Node.js and its rich ecosystem of libraries streamline the development process.
Overall, MongoDB's solutions enhance my productivity, flexibility, and scalability resulting in faster development cycles.
Reviewing MongoDB
What do you like best about the product?
MongoDB provides a flexible data schema that makes it simple for developers to store and manage unstructured data. It is an excellent fit for applications with constantly changing data because of this property.
Scalability: When the amount of data in a cluster increases, new servers can be added because MongoDB is horizontally scalable. This makes it simple to scale programmes as data needs increase.
High Performance: MongoDB can deliver high read and write throughput and is built to manage large volumes of data. As a result, it works well for applications that need high performance.
Scalability: When the amount of data in a cluster increases, new servers can be added because MongoDB is horizontally scalable. This makes it simple to scale programmes as data needs increase.
High Performance: MongoDB can deliver high read and write throughput and is built to manage large volumes of data. As a result, it works well for applications that need high performance.
What do you dislike about the product?
Absence of Transactions: Before to version 4.0, MongoDB did not enable multi-document transactions. Earlier versions of MongoDB had limited support for transactions, however, this is no longer a problem.
Data durability: Although MongoDB's write performance can be extremely quick, the system depends on an in-memory write operation, which could result in partial data loss if a failure happens before the data is written to the disc. MongoDB features a write concern option that enables developers to specify how many servers must approve a write operation before it is considered complete in order to ensure data durability.
Restricted Aggregation Functionality: MongoDB has a robust query language, but it has some restrictions on the ability to do complex analytics and aggregations. The application layer may need to perform additional processing on some complex aggregations.
Data durability: Although MongoDB's write performance can be extremely quick, the system depends on an in-memory write operation, which could result in partial data loss if a failure happens before the data is written to the disc. MongoDB features a write concern option that enables developers to specify how many servers must approve a write operation before it is considered complete in order to ensure data durability.
Restricted Aggregation Functionality: MongoDB has a robust query language, but it has some restrictions on the ability to do complex analytics and aggregations. The application layer may need to perform additional processing on some complex aggregations.
What problems is the product solving and how is that benefiting you?
Scalability: MongoDB's ability to expand horizontally across numerous servers, enabling the processing of huge datasets and high-volume workloads, is one of the main advantages of adopting MongoDB. Without having to make large changes to the underlying database architecture, this is especially helpful for applications that need to scale dynamically with changing data needs.
Versatile Data Model: The document-oriented data model used by MongoDB is very flexible and enables the storing of unstructured and semi-structured data, which can be difficult to manage in typical relational database systems. For modern, data-intensive applications that need the capacity to store and retrieve data in a flexible and dynamic way, this makes it the perfect option.
Versatile Data Model: The document-oriented data model used by MongoDB is very flexible and enables the storing of unstructured and semi-structured data, which can be difficult to manage in typical relational database systems. For modern, data-intensive applications that need the capacity to store and retrieve data in a flexible and dynamic way, this makes it the perfect option.
MongoDB a high-level database
What do you like best about the product?
We like Mongo DB because it is open source and can integrate with multiple data sources, making it scalable, reliable and easier than ever to handle large amounts of sparse data.
What do you dislike about the product?
The only drawback of using a MongoDB cluster is that you cannot directly download a copy of all the information stored there or you do not know how to do it.
What problems is the product solving and how is that benefiting you?
We are impressed by the fact that MongoDB is extremely scalable and fast compared to other databases and can store data in a dynamic format.
Easy To Use
What do you like best about the product?
Easy to use and perform queries. Faster data export and import
What do you dislike about the product?
Aggeration, and join operations takes too much time
What problems is the product solving and how is that benefiting you?
Saving the client's medical history and reports, providing updates to every system on any changes
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