Elasticsearch vs. Klipfolio Klips

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.

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Using Klipfolio is one of the finest ways we can expand our business because it is so simple to use and always has new features that make it better. We also appreciate the excellent customer service they offer. There are several benefits to making this investment in your company's efficiency and profitability. We think it's worth the money.

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• 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.

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• All my reporting requirements have been met.
• Salesforce, HubSpot, Mailchimp, Google Drive, and other business applications are quite easy to integrate with.
• The information you need is at your fingertips in a matter of seconds.
• Whenever I have a question, the customer service is always there to answer it.

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• Joining data requires duplicate de-normalized documents that make parent child relationships. It is hard and requires a lot of synchronizations
• Tracking errors in the data in the logs can be hard, and sometimes recurring errors blow up the error logs
• Schema changes require complete reindexing of an index

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• While Klipfolio covers so many of the bases, one area where I would like to see expansion would be offering additional design and graphics themes for even more customization.
• Klipfolio has an extensive offering but might be even better if there were a way that we could integrate with some small to mid-sized CRM solutions for audience list segmentation and marketing integrations.
• It would be interesting if Klipfolio could enable us to overlay the data learnings for cross-referencing of multiple client campaigns for comparative insights.

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

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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.

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My initial impressions of the software have been extremely positive. There are YouTube tutorials that explain how to make klips. The intuitive design of the UI It appears that everything in this software has been thoroughly tested to create all the visualizations that can be imagined as well as the user input controls that allow users to have exactly the data they want to be displayed in seconds, considering the various functions and formulas available in the Excel integrations and the extensive list of other services that can be integrated.

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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.

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It provides all the necessary information to be able to carry out the analysis of any type of business, to know how money is managed virtually, what to do to have greater visibility, in addition to being a platform that is always accessible and allows continuous and efficient work.

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

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None at all; just be sure of what information you will need for working.

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.

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These and many other BI tools are the most direct competitors. I only have experience with Klipfolio and Tableau. Tableau is definitely more capable, but much more difficult to learn and use. Klipfolio is simple and really packs a punch for its simplicity. I have yet to run into a major problem with it lacking a needed functionality.

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• 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.

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• It made reporting a breeze as we didn't have to spend time creating the reports
• The reporting forum really helped give our team more metrics to add to reporting
• Always ready to view Dashboard meant stakeholders could view reports at any given time