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

Anything related to knowledge Management, that is to say; Updating knowledge from the side of maintainers, grouping and learning it from the side of learners, leaving feedback to maintainers, unverifying cards in a pinch and creating courses of related content for people of different disciplines and favouriting content that you find the most useful.

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

• Simplified navigation with the use of keywords, making it quite easy to find an article.
• Reading notices when a Guru is updated, and the new parts highlighted makes it much easier when we must always be up to date.
• Provides an organized view of policies and workflows.

Incentivized

• 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

• It's not clear how to relate/ attach other guru cards. The feature exists but is not very easy to spot.
• We often find it difficult to search because we don't remember the card's title. I would love it if the tag words worked better.
• Once editing a card, instead of adding someone to collaborate on a draft, it would be good to send the draft to someone via email. I find people often ignore these emails/pings if it's just a draft collaboration. The wording could be to ask someone to verify the draft.

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

I give this rating because I really find Guru useful and user-friendly. You can easily follow and understand the steps and information from Guru. It has suited every issue that I have handled, and I was able to resolve it with the help of Guru. I hope that more people will find it helpful.

Incentivized

I have never encountered an outage with Guru in the year+ we've had it. I also never encountered an outage at the previous company where I used Guru. It has been extremely reliable.

Incentivized

There is some occasional slowness, or multiple refreshes before content will load. This doesn't happen frequently, though, and I don't get complaints from teammates about it.

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

The platform is unique, comprehensive, and uses AI. These are standout features. I also like the verification process and the ability to search from anywhere or on any browser. Guru enhances productivity and knowledge transfer when someone leaves an organization. Guru's interface is very user-friendly and can be trained quickly with new hires.

Incentivized

Right now, only customer support using Guru

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

• Guru allows our team to quickly reference available learning/knowledge materials with our clients on a daily basis and provide better support at every outreach
• With that said, spreading those same resources across two major global teams in the USA and Germany can lead to some inconsistencies. The i-frame process is not very intuitive for this scenario and our team treats policy/procedural differences as separate card or article entities.
• Guru allowed our organization to pioneer and establish a dedicated knowledge team component, of subject matter experts who work in tangent with existing resources, create new ones, and vet collective knowledge.

Incentivized