Algolia offers AI-powered solutions to improve online search and discovery experiences, with tools for business teams and APIs for developers that help to improve user engagement and conversions across websites, apps, and e-commerce platforms.
$0
per month 10k search requests + 100k records
Grafana
Score 8.6 out of 10
N/A
Grafana is a data visualization tool developed by Grafana Labs in New York. It is available open source, managed (Grafana Cloud), or via an enterprise edition with enhanced features. Grafana has pluggable data source model and comes bundled with support for popular time series databases like Graphite. It also has built-in support for cloud monitoring vendors like Amazon Cloudwatch, Microsoft Azure and SQL databases like MySQL. Grafana can combine data from many places into a single dashboard.
$0
Pricing
Algolia
Grafana
Editions & Modules
Build
Free
per month Up to 10,000 search requests + 1 Million records
Grow Plus
Free / Pay as you go
per month 10K searches/month & 100K records included; $1.75 per extra 1K searches, $0.40 per extra 1K records
Grow
Free / Pay as you go
per month 10K search requests & 100K records included; $0.50 per extra 1K searches, $0.40 per extra 1K records
Elevate
custom
per year
Elevate
Custom
per year Custom search requests and records — volume-based discounts available
Grafana Cloud - Pro
$8
per month up to 1 active user
Grafana Cloud - Free
Free
10k metrics + 50GB logs + 50GB traces up to 3 active users
Grafana Cloud - Advanced
Volume Discounts
custom data usage custom active users
Grafana - Enterprise Stack
Custom Pricing
Offerings
Pricing Offerings
Algolia
Grafana
Free Trial
Yes
Yes
Free/Freemium Version
Yes
Yes
Premium Consulting/Integration Services
Yes
No
Entry-level Setup Fee
Optional
No setup fee
Additional Details
Pay as you go, scale instantly, or upgrade anytime for advanced features and capabilities.
We had several sales calls with Algolia to determine it was the right product for our client. Then when we entered into an agreement we had very detailed weekly onboarding sessions to teach us about the tool. The dashboard is very user friendly and there's so many different features. We're excited about the level of control we'll have with this tool compared to the default site search tools through a CMS like Drupal or Wordpress, or ElasticSearch via AWS. This is nice because we can see why a search is ranking a certain way right through the dashboard and will save us time from having to do trial and error to make the site search as relevant as possible. However, there are so many features that it can seem overwhelming to start at first. We are also one of the first clients using this in a non-ecommerce way so there were not as many uses cases we could reference. The tool is expensive but worth it so far.
Just about any organization with more than one server and more than one cluster as it scales very well. Configuration of the application takes time and finesse to fine tune to where the balance of load time and getting data quickly meets. The plugins add load time but fine tuning for the application to meet demand needs nailed down at implementation
Users get instant feedback as they type, even with complex filters like brand, model, price range, and financing eligibility. This speed significantly improves engagement and reduces bounce.
A user searching for “Camry 2020” or even “Camary 20” still sees relevant Toyota Camry listings from 2020. This reduces friction, especially on mobile where spelling errors are common.
Algolia handles multi-faceted filters efficiently. For example, a user can filter by location, transmission type, color, or inspection status without any lag.
We fine-tune the ranking of search results based on what matters to our business—like prioritizing cars with higher margins or better availability in key cities.
We can experiment with different ranking formulas or UI variations to improve KPIs like lead conversion or time-to-first-interaction.
Better integration of features (ex. synonyms feature is great but isn't respected by their re-ranking product)
Tooling to reduce spam search queries being triaged by system/logged to analytics panels
More automated summaries of analytics (ie. recommend synonyms to add, trends noticed in search volume in specific areas of site, easier ways to leverage API vs using website UI)
Algolia is a great tool, we didn't have to build a custom search platform (using Elasticsearch for example) for a while. It has great flexibility and the set of libraries and SDKs make using it really easy. However, there are two major blockers for our future: - Their pricing it's still a bit hard to predict (when you are used to other kind of metrics for usage) so I really recommend to take a look at it first. - Integrating it within a CI/CD pipeline is difficult to replicate staging/development environments based on Production.
Personally I find the Algolia integration not very complicated and the service super reactive. In terms of configuration, it's quite complete, at the end what matters is what we are able to index on Algolia. With rich data, the tool is amazing and a lot of things are possible.
It is infinitely flexible. If you can imagine it, Grafana can almost certainly do it. Usability may be in the eye of the beholder however, as there is time needed to curate the experience and get the dashboards customized to how it makes sense to you. I know one thing they are working on are more templates, based on data sources
Performance is always a major concern when integrating services with our client's websites. Our tests and real-world experience show that Algolia is highly performant. We have more extremely satisfied with the speed of both the search service APIs and the backend administrative and analytic interface.
It’s non existent. No tech support and no customer service… my application was blocked and is currently inactive causing huge business disruption, and I’m still waiting days later for a response to an issue which could be resolved very very quickly if only they would respond. Very poor from a company of that size
While AWS's offering is a typically cheaper solution, it requires a lot of work to gain any of the core features of Algolia. The cost of dev time and long-term maintenance would be more than the costs incurred with Algolia, which is why it made the most sense financially. On the engineering side, we could give our stakeholders access to Algolia to adjust the indices themselves, which would allow us to focus on other work.
Grafana blows Nagios out of the water when it comes to customization. The ability to feed almost any data source makes it very versatile and the cost is great.
Overall is a scalable tool as the environment and the backend functions are the same and many things are done directly on the tool so without the need of further specific developments. However some things could be improved such as documentation for integration that could help in doing whitelabel solutions
Users who had abandoned our product (attributing slow search speeds as the reason) returned to us thanks to Algolia
We used Algolia as our product's backbone to relaunch it, making it the center of all search on our platform which paid off massively.
Considering we relaunched our product, with Aloglia functioning as its engine, we got a lot of press coverage for our highly improved search speeds.
One negative would be how important it is to read the fine print when it comes to the technical documentation. As pricing is done on the basis of records and indexes, it is not made apparent that there is a size limit for your records or how quickly these numbers can increase for any particular use case. Be very wary of these as they can quite easily exceed your allotted budget for the product.
