Transparent, resource-based pricing with Elastic Enterprise Search | Elastic Blog
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Transparent, resource-based pricing with Elastic Enterprise Search

Until now, standard search solution pricing has been based on models that are difficult to understand, expensive to scale, and/or beneficial to only the search vendor. At Elastic, we’re taking a different approach based on the principles of transparency, fairness, and scalability, and have introduced resource-based pricing for our products running on Elastic Cloud. And we believe that this pricing approach will revolutionize Enterprise Search buying and ownership.

The hidden costs of arbitrary pricing

Traditionally, search products are priced according to an arbitrary combination of number of documents, records, queries, ingestion operations, engines, users, retention history, domains, or some other search-specific criteria. And that combination changes depending on the search vendor.

Complicating queries

But then it gets more complicated. Understanding and predicting pricing often requires you to know exactly how the search will be used and how your users will behave as they search, and those can be tied to things that are typically out of your control as a buyer.

For example, what constitutes a query? Is it when the user types in something and presses Enter? Or, with query suggestion and auto-complete enabled, does each letter typed in constitute a new query in the pricing model? And if the vendor adds a new feature, like recommendations, that relies on queries in the back end, will your price suddenly jump, or will you max out your query limit for your current price tier?

Defining documents

And in some models, a document isn’t a document. Sometimes, because of the way a search solution has been architected, it cannot handle large documents, and needs to split them into multiple records. In most traditional cases, yes, these multiple records per document will count towards your price or tier limit. 

Paying for empty seats

And then there’s the per-user/per-seat model. Often a search product is anchored to another application or tool, such as Salesforce or ServiceNow, and is intended to enhance the search experience and workflow there. That add-on search product is often priced by user or seat because that’s how the anchor product is priced. Does it make sense? Maybe. But will every user be searching all the time, or are they paying for something not everyone will use, or that some will only use occasionally while others use it constantly. The per-seat model eliminates risk for the search vendor, ensuring the transaction is profitable for them, but does it benefit the end users? 

Mixing and matching use cases

All of this pricing complexity gets even more confusing when you start to look at using search across multiple use cases within the same organization. What if you want to enhance search on your corporate website (which has casual browsers, not logged-in users) and your internal helpdesk where agents are using a tool and have per-seat licenses. And your developers would like to embed search in a mobile app they’re building for your customers. This scenario can result in complicated contracts and confusing costs.

With most search solutions today, this is a really awkward conversation, and results in a confusing mix of pricing models, few of which are cost effective or fair for you, the buyer. 

Upgrade your search, upgrade your pricing

The above reasons (and more) are why we introduced resource-based pricing on Elastic Cloud. Now, you can choose to deploy our Enterprise Search products, like App Search, and only pay for the underlying resources you consume (RAM, disk, CPU).

And as your company grows or your use cases expand, you can easily add resources with a few clicks (entirely controlled by you), and see your costs continue to line up with your usage. No more paying for how many documents you might index someday or for users who may never actually use search. Just deploy, search, and scale. 

And of course, it’s based on actual usage. So if you flex your usage for a few days due to special events or high volumes, your additional usage costs will be applied for just that time period, eliminating the need to design (and pay) for the worst-case situation all the time.

Customer-first pricing

Will some of our own customers end up paying less for their search products under this model? You bet. Our resource-based pricing approach will be less expensive for search users in the long run. Powerful search and transparent pricing — no catch and no gimmick.

So give App Search on Elastic Cloud a spin for free, see how powerful it can be, and then talk to us about how simple our pricing model is compared to what you’re used to. We think you’ll find that there definitely is a better way to search.