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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Logstash
Score 9.0 out of 10
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Qlik Talend Cloud
Score 8.8 out of 10
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The Qlik Talend Cloud suite of solutions offer data integration, data quality, application integration, and data governance that work with key data sources, targets, architectures, or methodologies to ensure business users always have trusted and accurate data.
Logstash can be compared to other ETL frameworks or tools, but it is also complementary to several, for example, Kafka. I would not only suggest using Logstash when the rest of the ELK stack is available, but also for a self-hosted event collection pipeline for various …
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.
Perfect for projects where Elasticsearch makes sense: if you decide to employ ES in a project, then you will almost inevitably use LogStash, and you should anyways. Such projects would include: 1. Data Science (reading, recording or measure web-based Analytics, Metrics) 2. Web Scraping (which was one of our earlier projects involving LogStash) 3. Syslog-ng Management: While I did point out that it can be a bit of an electric boo-ga-loo in finding an errant configuration item, it is still worth it to implement Syslog-ng management via LogStash: being able to fine-tune your log messages and then pipe them to other sources, depending on the data being read in, is incredibly powerful, and I would say is exemplar of what modern Computer Science looks like: Less Specialization in mathematics, and more specialization in storing and recording data (i.e. Less Engineering, and more Design).
This tool fits all kinds of organizations and helps to integrate data between many applications. We can use this tool as data integration is a key feature for all organizations. It is also available in the cloud, which makes the integration more seamless. The firm can opt for the required tools when there are no data integration needs.
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).
Logstash design is definitely perfect for the use case of ELK. Logstash has "drivers" using which it can inject from virtually any source. This takes the headache from source to implement those "drivers" to store data to ES.
Logstash is fast, very fast. As per my observance, you don't need more than 1 or 2 servers for even big size projects.
Data in different shape, size, and formats? No worries, Logstash can handle it. It lets you write simple rules to programmatically take decisions real-time on data.
You can change your data on the fly! This is the CORE power of Logstash. The concept is similar to Kafka streams, the difference being the source and destination are application and ES respectively.
Talend Data Integration allows us to quickly build data integrations without a tremendous amount of custom coding (some Java and JavaScript knowledge is still required).
I like the UI and it's very intuitive. Jobs are visual, allowing the team members to see the flow of the data, without having to read through the Java code that is generated.
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.
As I said earlier, for a production-grade OpenStack Telco cloud, Logstash brings high value in flexibility, compliance, and troubleshooting efficiency. However, this brings a higher infra & ops cost on resources, but that is not a problem in big datacenters because there is no resource crunch in terms of servers or CPU/RAM
We use Talend Data Integration day in and day out. It is the best and easiest tool to jump on to and use. We can build a basic integration super-fast. We could build basic integrations as fast as within the hour. It is also easy to build transformations and use Java to perform some operations.
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.
Good support, specially when it relates to PROD environment. The support team has access to the product development team. Things are internally escalated to development team if there is a bug encountered. This helps the customer to get quick fix or patch designed for problem exceptions. I have also seen support showing their willingness to help develop custom connector for a newly available cloud based big data solution
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.
Logstash can be compared to other ETL frameworks or tools, but it is also complementary to several, for example, Kafka. I would not only suggest using Logstash when the rest of the ELK stack is available, but also for a self-hosted event collection pipeline for various searching systems such as Solr or Graylog, or even monitoring solutions built on top of Graphite or OpenTSDB.
In comparison with the other ETLs I used, Talend is more flexible than Data Services (where you cannot create complex commands). It is similar to Datastage speaking about commands and interfaces. It is more user-friendly than ODI, which has a metadata point of view on its own, while Talend is more classic. It has both on-prem and cloud approaches, while Matillion is only cloud-based.
Positive: LogStash is OpenSource. While this should not be directly construed as Free, it's a great start towards Free. OpenSource means that while it's free to download, there are no regular patch schedules, no support from a company, no engineer you can get on the phone / email to solve a problem. You are your own Engineer. You are your own Phone Call. You are your own ticketing system.
Negative: Since Logstash's features are so extensive, you will often find yourself saying "I can just solve this problem better going further down / up the Stack!". This is not a BAD quality, necessarily and it really only depends on what Your Project's Aim is.
Positive: LogStash is a dream to configure and run. A few hours of work, and you are on your way to collecting and shipping logs to their required addresses!
It’s only been a positive RoI with Talend given we’ve interfaced large datasets between critical on-Prem and cloud-native apps to efficiently run our business operations.
