MongoDB is an open source document-oriented database system. It is part of the NoSQL family of database systems. Instead of storing data in tables as is done in a "classical" relational database, MongoDB stores structured data as JSON-like documents with dynamic schemas (MongoDB calls the format BSON), making the integration of data in certain types of applications easier and faster.
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SQLite
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SQLite is an in-process library that implements a self-contained, serverless, zero-configuration, transactional SQL database engine. The code for SQLite is in the public domain and is thus free for use for any purpose, commercial or private. SQLite is one of the most widely deployed databases in the world.
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Fully managed, global cloud database on AWS, Azure, and GCP
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The flexible structure underlying MongoDB's construction is not found in other competitors; the ability to easily change the structure without affecting other stored documents. It is very ideal for projects that you cannot predict that the structure will change this way. Of …
MongoDB is probably the most famous NoSQL database of the moment. it has become one of the most promising startups. Some companies that currently use MongoDB are Foursquare or eBay. This type of database is designed to perform queries and aggregations on large amounts of data. …
MongoDB is the most complete database of NoSQL type. In my opinion, it has all the tools for a good development of a database. I have not had problems when using the application.
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.
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.
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.
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.
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.
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.
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.
I have had a wonderful experience with SQLite because in my every project I use SQLite in the development phase because it's really fast, doesn't crash and very easy to maintain as well. It saves a lot on physical memory and dedicated server usage. It has all the basic functionality you would need to get the job done and that too at no cost at all. What more could you ask for !!!
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.
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.
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.
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
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.
