Elasticsearch is an enterprise search tool from Elastic in Mountain View, California.
$16
per month
Microsoft Sentinel
Score 8.3 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, …
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.
Well, it's definitely suited to log in monitor most of the normal security infrastructure and collect security telemetry. It also extends well to Microsoft's entire suite with regards to data collection for things like Office 365, Power BI, power apps, and the like. It is also pretty good at collecting information from homegrown applications, especially if you're building in Azure.
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.
Sentinel is by far the most efficient tool in supporting the highest number of solutions and products when it comes to data connection (or ingestion) and that too in the least complex manner possible. Most of the data connectors in Sentinel are very easy to configure and deploy.
Incident Management is undoubtedly one of the main USPs of Sentinel. With an easy-to-use UI, variety of utilities (adding tasks, manual triggering of playbooks, activity logs etc.) and provision of having an investigation map from the incident details page, Sentinel clearly stands out in this area.
I personally love the feature of integrating 'Threat Intelligence' to Sentinel from a free and one of the most reliable sources, Microsoft itself. This not only saves time for an analyst in checking the reputation of an entity but also allows to take actions on the suspicious entities at earliest.
It takes some time to learn how to use and install it properly, and it does not connect effectively with external PaaS systems such as Salesforce CRM, Salesforce Commerce Cloud, and so on.
Microsoft can simplify the display of the logs to make them easier to study, and the user interface occasionally delays, which can also be enhanced.
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.
The key advantage of using Sentinel lies in Microsoft already being a renowned name in cloud services. Hence, the Collection of data at the cloud scale across all users, devices, applications, and infrastructure, both on-premises and especially in the MS Cloud, is super easy. Additionally, leveraging Threat Intel from Microsoft itself gives a sense of security, given their years of experience in the collection of intel. The AI and Machine learning features provided by MS is one of the finest.
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.
