Apache Ignite™ is a distributed database for high-performance computing with in-memory speed
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MongoDB
Score 8.9 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.
$0.10
million reads
Redis Cloud
Score 10.0 out of 10
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Redis Labs in Mountain View, California offers Redis Enterperise Cloud, available on AWS, Microsoft Azure, and Google Cloud, delivered as a service and boasting maximal uptime, easy migration with on-prem deployments of Redis, designed to enable users to run any query, simple or complex, at sub-millisecond performance at virtually infinite scale without worrying about operational complexity or service availability.
*Redis is a trademark of Redis Ltd. Any rights therein are reserved to Redis…
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Pricing
Apache Ignite
MongoDB
Redis Cloud
Editions & Modules
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Shared
$0
per month
Serverless
$0.10million reads
million reads
Dedicated
$57
per month
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Offerings
Pricing Offerings
Apache Ignite
MongoDB
Redis Cloud
Free Trial
No
Yes
Yes
Free/Freemium Version
No
Yes
Yes
Premium Consulting/Integration Services
No
No
Yes
Entry-level Setup Fee
No setup fee
No setup fee
No setup fee
Additional Details
Contact vendor for pricing information.
Fully managed, global cloud database on AWS, Azure, and GCP
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Community Pulse
Apache Ignite
MongoDB
Redis Cloud
Considered Multiple Products
Apache Ignite
No answer on this topic
MongoDB
Verified User
Engineer
Chose MongoDB
MongoDB is our go-to database solution for any project, and the more we work with it the more we love it. Some say that NoSQL is pointless... Our developers wholeheartedly disagree, because they love working with it. Though both NoSQL and SQL have their purposes, in most …
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.
Redis Cloud is very well suited for scenarios where fast data access is required or somewhat unstructured data needs to be stored. For us, it has worked very well for user session storage. However, if you have large amounts of structured data that is not frequently accessed, Redis is not the solution and a traditional relational database is likely more appropriate.
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.
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.
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.
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