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.
Great for standard web application performance monitoring, analytics and error reporting. Shows line level code errors, gives insight into performance issues (plugins, API issues, etc.). Automation and scheduled scanning in production gives client visibility into 'after deployment' value. Also lets a relatively small number of developers keep tabs on a handful of different site/applications without needing a bunch of tools. The UI is pretty complicated and can be overwhelming for new users. Documentation could be better for the learning curve,
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.
Great web interface. Lots of data available in a really clean format, with filtering options and more.
Per-user exception tracking. User is complaining about something being broken? Look up their account ID in Sentry and you can see if they've run into any exceptions (with device information included, of course).
Source map uploading. Took a little while to figure this out but now we have our deploy script upload sourcemaps to Sentry on each deployment, meaning we get to see stack traces that aren't obfuscated!
Very generous free tier – 10,000 events per month. We're nowhere near that yet.
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.
Its incredibly versatile, but that leads to complexity for the uninitiated, which can be intimidating. Nevertheless its a well polished product, in our case leading to only using it for a focus on frontend is still more cost effective than buying a one-to-rule-them-all tool...
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.
It is cheaper and offers better support for front-end applications for enterprise large environments with more then 30 scrum teams and hundreds of micro frontend applications. The configuration options, both with the agent and from the user interface, are superior to other tools, and the documentation is also very easy to use.
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.
