MongoDB (from "humongous") is an open source document-oriented database system developed and supported by 10gen. 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. According to the vendor, organizations from cutting…
$0.10
million reads
RavenDB
Score 8.6 out of 10
N/A
RavenDB is a NoSQL Document Database that is fully transactional (ACID) across the database and throughout clusters. It is presented as an easy to use all-in-one database that minimizes the need for third party addons, tools, or support to boost developer productivity and get projects into production fast. Users can setup and secure a data cluster deploy in the cloud, on…
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Pricing
MongoDB
RavenDB
Editions & Modules
Shared
$0
per month
Serverless
$0.10million reads
million reads
Dedicated
$57
per month
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Offerings
Pricing Offerings
MongoDB
RavenDB
Free Trial
Yes
Yes
Free/Freemium Version
Yes
Yes
Premium Consulting/Integration Services
No
Yes
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
Fully managed, global cloud database on AWS, Azure, and GCP
Once I had got my head around the concept of a document database it was a happy bye-bye to SQL Server. Firebird - far too fiddly - I found myself writing a silly API to sit on top of Firebird just to do the most basic things. MongoDB - in the very short time I spent with it, it …
While MongoDB is in general more popular, I cannot fathom why that is. If you want ACID support (and as a developer, you'll always want that), MongoDB is way slower when compared to RavenDB. Furthermore, RavenStudio is just integrated, while
RavenDB is just smarter than the competitors. The mapping reduction sorting is head and shoulders above everything else I've used. Nothing really approaches comparable in terms of complexity. Because of the searching of predetermined categories, read efficiency is terrible. …
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Team Lead
Chose RavenDB
Much better support, more transparent pricing, much more easy setup process, native integration into c# / net core. We also tried to set up a Mongo Atlas cluster by self-study but weren't able to get this running. There is a much better response when searching in google, but a …
Installing and configuring. We had some big issues with indexing the data after the documents were created and wanted to expand the index, with millions of records this task mostly did not complete despite a dedicated server.
Being that ACID and cluster transaction support is a big plus against all of them. Cool prices on Azure and AWS is another plus. The ability to search between millions of documents.
We chose Raven over Mongo because it has robust support for multi-document transactions, first-class .NET and LINQ support, a well-designed API that has inspired imitation and has better tooling out of the box. We chose Raven over Redis because Raven is a full persistent …
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.
If you're a.NET developer searching for a system other than SQL Server for business assessment, then you must try RavenDB. RavenDB is a fantastic document-oriented system that has been specifically developed to work with all.NET or Windows systems. Developers are continually working on such systems to eliminate their flaws while also providing a few benefits. We must refresh ourselves on a regular basis since the free software system is like an open area where anybody may stand up with a brilliant solution to the issue. RavenDB is absolutely worth a look
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.
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.
We've had an excellent experience using RavenDB. Internally we are testing the newer features in 5.0 such as time series, which will effect the con specified previously dependent on the real world performance. We foresee that BattleCrate will continue to use RavenDB as we grow.
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.
RavenDB is easy to use and provides a very friendly and intuitive management tool. We can now map documents with indexes, transform unstructured data into JSON format and analyze text and spatial data in real-time. With an array of functional features like data visualization, SNMP monitoring, automated data backup, it is seamlessly helping us in managing databases' performance and generating custom reports.
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.
The support is really fast and flexible. Since one single working day, we got a response to our first request, only 4 days later we got a technical demonstration for our complete developer team to get in touch with raven and its performance. Also during our development, we got a quick response to questions.
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.
The given alternatives are also powerful and really good noSQL databases but the highest availability of RavenDB allows me/us to know it a lot better. RavenDB is encrypted by default wherever we use it in production and it has a high level of documents compression.
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
RavenDB has saved my customers a lot of money with their cloud services' tiered model. The database is able to grow with the project/company and can start out small at a low cost.
RavenDB is free for three nodes and three CPUs, which makes it great for development scenarios. You're able to start rapidly building applications without having to worry about licensing.
Scaling out has allowed us to use three small cloud servers when starting out and get the performance and throughput of a single larger server.