Elasticsearch vs. Guru

Elasticsearch is really well suited for searching text (Natural Language Processing) and you can fine tune the searches and scoring very well. I like the ability to find Significant Terms in the Index, where you can find aggregations that are really relevant to a specific search. It also allows for queries to lead to new queries via aggregations which is great for navigating your data. It is less suited to doing more complex aggregations where slices of data are required to be processing using guassian normalizations. And doing searches which join different documents is very very hard, and requires serious thought on how to denormalize data.

Incentivized

I think Guru is well-suited to organizations with subject matter experts committed to maintaining documentation. Guru cannot be managed by a single admin. It's essential that the SMEs are on board and are expected to participate in Guru as part of their role responsibilities. I'm not sure how well Guru would work for larger organizations with more information to house. I've only ever used Guru in SMBs with about 250 employees. It works well for that size.

Incentivized

• Super-fast search on millions of documents. We've got over 2 billion documents in our index and the retrieve speeds are still in the < 1-second range.
• Analytics on top of your search. If you organize your data appropriately, Elasticsearch can serve as a distributed OLAP system
• Elasticsearch is great for geographic data as well, including searching and filtering with geojson, and a variety of geospatial algorithms.

Incentivized

• Easy to learn. Anyone can make cards and use the AI to make them professional.
• Answer questions about my business, essentially a wiki for everything we do.
• The research mode is amazing. Full reports on various types of information including some rather complex topics. Complete with citations of where the information came from.
• Admins can manage a hierarchy to keep information secure and available to the correct people.

• Setting Java memory thresholds can be a pain for those not accustomed to things like Eden Space & Old Generation which can lead to over allocation, or more likely, under allocation. Apache Solr had a similar issue. It would be nice if the program would take an extra step and dogfood it's own advice by analyzing the system & processes to return a solid recommendation for that configuration. The proper configuration information is outlined in the documentation, it would be nice if that was automated.
• The only health check that ElasticSearch reports back is a "red" status without any real solid information about what is going on, though its usually memory thresholds or disk I/O. I am currently on ElasticSearch 1.5 so that may have changed for newer versions. When the status goes "red", I as the administrator of the software, feel like I lose control of whats going on which should rarely happen. Something more verbose would eliminate that.
• This is more of a critique of the ElasticStack in general. The whole top to bottom stack is starting to get feature creep with things that are better suited in other software and increasing the barrier for entry for people to get started with setting up a robust logging infrastructure. ElasticSearch as a storage search engine, is pretty streamlined, but I can see that the tools that comprise the ELK Stack are going to require a certification with constant study at some point. During major release for Logstash a while back, it literally took a month to learn a new language because Elastic completely changed the syntax. For a medium sized organization of only a couple of admins, that is a pretty high bar where time is money. They really should work on refining/automating the tools & search engine they have, instead of shoehorning/changing things on to an already rock solid foundation.

Incentivized

• Formatting has always been a pain point for me. We used Google Sites previously, and the ability to add multiple columns of smaller content boxes was great. To do the same thing in Guru, you need to create a table, which constrains you.
• While the AI functionality is great, it can be challenging at times to refine the responses. Specifically, you must edit the source that is being pulled rather than the response itself. In some cases, we've edited the source to make the answer as clear as possible, and even after multiple attempts, the populated answer was acceptable but still not ideal for minimizing confusion.
• Sometimes, when adding content, the cards glitch, and it won't save. Or if I go to add something to a landing page, it says it couldn't be saved. Then I do it all over again, and it works.
• While the cards have limited formatting, the landing pages are great; however, when trying to move around or adjust the content boxes, it can be hypersensitive and very tricky to work with.

Incentivized

We're pretty heavily invested in ElasticSearch at this point, and there aren't any obvious negatives that would make us reconsider this decision.

Incentivized

With Guru, information flows seamlessly through your organization, cutting through meeting and chat fatigue and giving your team time back to stop looking for information and do what you hired them to do. Guru does the heavy lifting to get you set up quickly, ensuring information is readily accessible when and where it’s needed, all while improving in quality over time

Incentivized

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.

Incentivized

While using the GURU card, the level of response I get is quality. The rate at which my responses and prompts through the search or chat is fast, responsive, and high-quality. I can easily see when the cards were modified, who modified them, and the new information available on the GURU.

Incentivized

Highly reliable day‑to‑dayGuru is consistently available when I need it. The platform loads quickly, search works reliably, and I rarely experience downtime or slow performance. It’s dependable enough that teams can trust it as a daily source of truth. Minimal unplanned outages or errors. In my experience, unplanned outages or errors are extremely rare. Even during high‑usage periods or heavy workflows, Guru remains stable and responsive.

Incentivized

Pages load quickly and consistently. Guru’s interface is lightweight, so cards, boards, and search results load fast with very little lag. Even when navigating between collections or opening larger cards, performance stays smooth and reliable. Integrations perform well without slowing systems down. Using Guru through the browser extension or Slack integration doesn’t noticeably impact performance. Cards surface quickly, and interacting with the integrations feels just as smooth as using Guru directly.

Incentivized

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.

Incentivized

The only reason I do not give it a a ten is because I think there is still some room for improvement in meeting the different time zone needs of their customers, but overall their support is top notch. Friendly, capable, and quick.

Incentivized

I would rate the in-person training for Guru a solid 9 out of 10. The session was incredibly valuable as it provided comprehensive insights into using Guru effectively. I learned a lot about the tool's functionalities, which significantly enhanced my proficiency and confidence in utilizing Guru for my daily tasks. The training was engaging, informative, and tailored well to ensure I could apply what I learned immediately. Overall, it was a highly productive and beneficial learning experience.

Incentivized

I would rate the online training for Guru a strong 8 out of 10. While it lacked the interactive nature of in-person sessions, the content was well-structured and delivered effectively. The training modules were clear and comprehensive, covering all essential aspects of using Guru. The flexibility of online training allowed me to learn at my own pace and revisit topics as needed. Overall, it provided a solid foundation and practical understanding of Guru's functionalities, making it a valuable learning experience despite the virtual format.

Incentivized

Do not mix data and master roles. Dedicate at least 3 nodes just for Master

Incentivized

You will need a very strong team of guru champions in order to get EVERYONE and EVERYTHING on Guru, it takes some craziness and over talking about guru everywhere to get people to be exicted, contribute and use. If you are starting any kind of buisness and you need KB, just go for guru as fast as you can because when you will grow you will thank yourself.

Incentivized

Elasticsearch is the most well-known and supported free data platform that we identified. We are taking advantage of community knowledge and practices. In terms of flexibility and breadth of use cases no other competitor came close to Elasticsearch. We've tried Solr in the past be we encountered issues which were deal-breaking for us. MongoDB - it just did not pass our evaluation parameters as a main data platform. We still use it for smaller purposes, though.

Incentivized

Compared with the vendors that we initially evaluate the AI functionality of, Guru makes the difference and also the interface capabilities, making it user-friendly, being able to build it up in a professionally way. there are no limitations on the customization of the interface, which supports multiple use cases at once and can apply to different teams that have different needs

Incentivized

Easily deployable across multiple teams and departmentsGuru is designed to scale horizontally across an organization. As teams grow, it’s simple to create new Collections, Boards, and permission sets without disrupting existing structures. This allows each department to manage its own knowledge while still contributing to a unified source of truth

Incentivized

• I am not in finance and I suspect even if I was this would be hard to measure. But for sure, Elasticsearch has enabled us to have the most flexible data model in the industry for our customer's data, and in doing so we have attracted many many technical customers and got much of their $$$.
• One problem with Elasticsearch is that because it runs on the JVM, there can be some stop-the-world JVM garbage collections happening that can take down nodes and reduce indexing speed. The solution for that tends to be "let's just upgrade the CPU on that machine". And before you know it you are paying $$$ because this'll happen with 40+ machines.
• On the other hand, I do think that ES is more efficient than other systems and so it requires fewer nodes to keep it highly tolerant and available, so we probably saved some money that way.

Incentivized

• The small support team can reliably scale to cover a broad swath of Tier 1 topics while maintaining decent first-response times, even when experiencing record-breaking, forecast-exceeding ticket volumes (e.g., 4 FT and 1 PT agents managing 880 tickets in one week).
• Tier 2 topics (e.g., Billing and Technical) that require specialized attention and are "owned" by a specific agent can be written and validated by that agent's manager. The team manager can utilize that to cross-train should the agent leave the company or be out of the office.
• Seeing my team's ebb and flow of weekly/monthly Guru engagement, as well as validation percentages in comparison to the ebb and flow of our ticket volume and production releases, helped me to communicate with C-suite leaders the necessity of having a margin of time to implement AI Agents and integrations in order to continue to scale.

Incentivized