Graylog, headquartered in Houston, offers their eponymous platform for centralized log management that helps users find meaning in data faster so as to take action immediately. Graylog is available via Enterprise and Cloud plans, but also has a Small Business Plan, and an Open (free) plan with limited features.
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MongoDB
Score 8.7 out of 10
N/A
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
Pricing
Graylog
MongoDB
Editions & Modules
No answers on this topic
Shared
$0
per month
Serverless
$0.10million reads
million reads
Dedicated
$57
per month
Offerings
Pricing Offerings
Graylog
MongoDB
Free Trial
No
Yes
Free/Freemium Version
Yes
Yes
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
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Fully managed, global cloud database on AWS, Azure, and GCP
More Pricing Information
Community Pulse
Graylog
MongoDB
Features
Graylog
MongoDB
NoSQL Databases
Comparison of NoSQL Databases features of Product A and Product B
For small companies, Graylog is the best solution possible. It's easy to configure and "just works." Above everything else, it's free. The only thing I hold against it is the fact that it's Linux-based. [This] makes sense because Elasticsearch is Linux-based. But Linux adds a layer of complexity that we don't need for something basic as a logging server. I'm pretty sure that we would have had a logging server years earlier if I had to convince quite a few decision-making people to go ahead with it anyway.
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.
Graylog does a great job of its core function: log aggregation, retention, and searching.
Graylog has a very flexible configuration. The backend for storage is Elasticsearch and MongoDB is used to store the configuration. You have to option to make your configuration as simple as possible by storing everything on one box, or you can scale everything out horizontally by using a cluster of Elasticsearch nodes and MongoDB servers with several Graylog servers pointed to all the necessary nodes.
Graylog does a good job of abstracting away a fair portion of Elasticsearch index management (sharding, creation, deletion, rotation, etc).
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.
Graylog is easy to deploy. The tricky part is to configure all hosts that are going to send their log data to Graylog, considering the retention period of this data, it will need a lot of disk space to store it. Its rotation works fine. It is very simple to navigate and explore the data you send to it, and very easy to filter and export them too.
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.
Community support does not give simple straightforward answers; simply search up Graylog Issues and look at some of the responses on the forums. The documentation is your only hope if you are on the free version, as you can NOT purchase only support. The few times I have worked with Graylog Enterprise support they were great though.
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.
In terms of log aggregation, the free product fully stacks up with the competitors listed. Full control over the data ingests for flexible configuration. Graylog even better on that front than AlienVault USM because you cannot configure the variable mapping. We haven't used the threat exchange stuff or correlation. But with regex searches, we have created function dashboards that show threat theater pictures of our network based on logs from our firewall.
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
