Apache Geode is a distributed in-memory database designed to support low latency, high concurrency solutions, available free and open source since 2002. With it, users can build high-speed, data-intensive applications that elastically meet performance requirements. Apache Geode blends techniques for data replication, partitioning and distributed processing.
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MongoDB
Score 8.5 out of 10
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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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Apache Geode
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Apache Geode
MongoDB
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Apache Geode
MongoDB
NoSQL Databases
Comparison of NoSQL Databases features of Product A and Product B
The biggest advantage of using Apache Geode is DB like consistency. So for applications whose data needs to be in-memory, accessible at low latencies and most importantly writes have to be consistent, should use Apache Geode. For our application quite some amount of data is static which we store in MySQL as it can be easily manipulated. But since this data is large R/w from DB becomes expensive. So we started using Redis. Redis does a brilliant job, but with complex data structures and no query like capability, we have to manage it via code. We are experimenting with Apache Geode and it looks promising as now we can query on complex data-structures and get the required data quickly and also updates consistent.
MongoDB [is] great at storing JSON data grouped into "collections". In this format, you can store any JSON documents and conveniently categorize them by collections. The JSON document contained in MongoDB is called binary JSON or BSON and, like any other document in this format, is unstructured. Therefore, unlike traditional DBMS, any kind of data can be stored in collections, and this flexibility is combined with the horizontal scalability of the database. It should be noted that MongoDB does not have links between documents and “collections” (this is partially compensated by the Database Reference - links in the DBMS, but this does not completely solve the problem). As a result, a situation arises in which there is a certain set of data that is not related to other information in the database, and there is no way to combine data from different documents. In SQL systems, this would be an elementary task.
Easy to learn. When I picked up MongoDB for the first time, I had little background in database management or modeling. If you have a background in javascript (and JSON)... then you can figure out how to use MongoDB pretty fast.
Fast performance.
It's relatively easy to set up in certain environments because there are lots of ready-made solutions out there.
There's a lot of support in the existing ecosystem for it —, especially in the node.js realm.
Query syntax is pretty simple to grasp and utilize.
Aggregate functions are powerful.
Scaling options.
Documentation is quite good and versioned for each release.
MongoDB is one of the most famous non-relational databases in the world, there are famous active projects that use this database. I think that the same company that develops the database gives you the online induction totally free is something that really is very positive. Accounts with a first-class support to be able to relate the correct implementation of the database, in addition to teaching you the best practices to optimize your projects, I believe that with this decision it is more than obvious which is the best decision at the time of seeing with which database to work.
Still Experimenting. Initial results are good. we need to figure out if we can completely replace Redis. Cost wise if it makes sense to keep both or replacement is feasible.
It is one of the reasons why we prefer it to store documents in a JSON-style format, to access the desired document very quickly regardless of its size, to be readable by human eyes, and to be easily scalable and manageable.
I have reached multiple times to the MongoDB community for the help and they have provided each and easy solution for every problem. Over the internet and on stack overflow many people responds over the challenges. Now this tool is very much used in every company and projects so internally many people are there to give a 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.
The environment I work in is somewhat unique in that we use both MySQL and MongoDB. However, each is used for specific purposes that the other is not well suited for. MongoDB is not a relational database like MySQL, so it serves as the perfect place to dump key bits of data for quick retrieval later. This is something we can't easily do with MySQL. On this smaller database, MongoDB also lets us retrieve data more quickly with its fast and efficient querying.
We can make more open and flexible systems due to its easy adaptation to new evolutions in web applications.
In the latest versions it offers support for different transactions and we could carry out real tests related to the concurrency of the application.
MongoDB allows you to have distributed clusters, which improves the speed of the queries by reducing the latency that exists between the database cluster and the service that executes the query.
