Elasticsearch is an enterprise search tool from Elastic in Mountain View, California.
$16
per month
Microsoft Sentinel
Score 8.7 out of 10
N/A
Microsoft Sentinel (formerly Azure Sentinel) is designed as a birds-eye view across the enterprise. It is presented as a security information and event management (SIEM) solution for proactive threat detection, investigation, and response.
Elasticsearch, we did a demo about it. Also the CrowdStrike platform, we got a demo on it. How did they compare? I think Elasticsearch, for us, it's more hard to configure. Microsoft Sentinel is pretty straight to the point. We turn on stuff, it's plug-and-play. CrowdStrike, …
Elastic seems to have a much better interface for log search and is able to filter out noise. Microsoft Sentinel also appears to generate a lot of false positives.
Elasticsearch is a really scalable solution that can fit a lot of needs, but the bigger and/or those needs become, the more understanding & infrastructure you will need for your instance to be running correctly. Elasticsearch is not problem-free - you can get yourself in a lot of trouble if you are not following good practices and/or if are not managing the cluster correctly. Licensing is a big decision point here as Elasticsearch is a middleware component - be sure to read the licensing agreement of the version you want to try before you commit to it. Same goes for long-term support - be sure to keep yourself in the know for this aspect you may end up stuck with an unpatched version for years.
I recommend Microsoft Sentinel for effective threat detection and response. It is a great SIEM and SOAR solution for businesses, and we have used it effectively, which is why I recommend it. Since it works across on-premises and multi-cloud environments, it is ideal for businesses of all sizes. Being AI-equipped and its ability to handle threat analytics make it irresistible.
As I mentioned before, Elasticsearch's flexible data model is unparalleled. You can nest fields as deeply as you want, have as many fields as you want, but whatever you want in those fields (as long as it stays the same type), and all of it will be searchable and you don't need to even declare a schema beforehand!
Elastic, the company behind Elasticsearch, is super strong financially and they have a great team of devs and product managers working on Elasticsearch. When I first started using ES 3 years ago, I was 90% impressed and knew it would be a good fit. 3 years later, I am 200% impressed and blown away by how far it has come and gotten even better. If there are features that are missing or you don't think it's fast enough right now, I bet it'll be suitable next year because the team behind it is so dang fast!
Elasticsearch is really, really stable. It takes a lot to bring down a cluster. It's self-balancing algorithms, leader-election system, self-healing properties are state of the art. We've never seen network failures or hard-drive corruption or CPU bugs bring down an ES cluster.
I appreciate that it keeps the data within our, what we call our, authorization boundary. The fact that the data remains within Microsoft's, I guess, walled garden if you will, is very helpful for certain compliance needs in particular.
The large library of ingestion: ability to ingest is basically as easy as I can basically get it to be most of the time. There's occasionally some vendors that it's a little bit more challenging for, but given the ease of integration for a lot of things, basically it's become one of my requirements when I am looking at other tools is how easily do they integrate with Sentinel.
I think it should include more third party integration with non microsoft products as well as with other cloud providers. These integrations should be native.
It should improve ML and AI capabilities.
I find its documentation a little bit difficult to understand at the start. So the words should be simple.
To get started with Elasticsearch, you don't have to get very involved in configuring what really is an incredibly complex system under the hood. You simply install the package, run the service, and you're immediately able to begin using it. You don't need to learn any sort of query language to add data to Elasticsearch or perform some basic searching. If you're used to any sort of RESTful API, getting started with Elasticsearch is a breeze. If you've never interacted with a RESTful API directly, the journey may be a little more bumpy. Overall, though, it's incredibly simple to use for what it's doing under the covers.
The Microsoft Azure Sentinel solution is very good and even better if you use Azure. It's easy to implement and learn how to use the tool with an intuitive and simple interface. New updates are happening to always bring new news and improve the experience and usability. The solution brings reliability as it is from a very reliable manufacturer.
We've only used it as an opensource tooling. We did not purchase any additional support to roll out the elasticsearch software. When rolling out the application on our platform we've used the documentation which was available online. During our test phases we did not experience any bugs or issues so we did not rely on support at all.
As far as we are concerned, Elasticsearch is the gold standard and we have barely evaluated any alternatives. You could consider it an alternative to a relational or NoSQL database, so in cases where those suffice, you don't need Elasticsearch. But if you want powerful text-based search capabilities across large data sets, Elasticsearch is the way to go.
Microsoft Sentinel excels in cloud-native scalability, Microsoft ecosystem integration, and AI-driven threat detection with UEBA and Fusion rules, offering faster deployment and lower costs (48% cheaper per Forrester) than Splunk, QRadar, Exabeam, SentinelOne, Securonix, and Wazuh. It lags in third-party integrations and syslog parsing. Organizations choose Microsoft Sentinel for its cost-effectiveness, automation, and Microsoft synergy, especially in Azure-heavy environments, though Splunk and Exabeam lead in flexibility and UEBA, respectively.
We have had great luck with implementing Elasticsearch for our search and analytics use cases.
While the operational burden is not minimal, operating a cluster of servers, using a custom query language, writing Elasticsearch-specific bulk insert code, the performance and the relative operational ease of Elasticsearch are unparalleled.
We've easily saved hundreds of thousands of dollars implementing Elasticsearch vs. RDBMS vs. other no-SQL solutions for our specific set of problems.
As any cybersecurity product, this has to be more with risk to avoid loss in case of a ransomware that more than relate to a productivity increase. Maybe the impact could be that instead of having people that are checking 24/7 the dashboard, you could implement Sentinel and have less people checking that or people with less expertise. So the saving will be a minor but will be a saving in the cost of your team.
