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.
N/A
Apache Solr
Score 7.3 out of 10
N/A
Apache Solr is an open-source enterprise search server.
N/A
Pricing
Algolia
Apache Solr
Editions & Modules
Build
Free
Up to 10,000 search requests + 1 Million records
Grow Plus
Free to start, then pay-as-you-go
10,000 search requests/month and 100,000 records included; $1.75 per additional 1K search requests and $0.40 per additional 1K records
Grow
Free to start, then pay-as-you-go
10,000 search requests/month and 100,000 records included; $0.50 per additional 1K search requests and $0.40 per additional 1K records
Elevate
custom
per year
Elevate
Custom
Custom Custom search requests and records; volume-based discounts available
No answers on this topic
Offerings
Pricing Offerings
Algolia
Apache Solr
Free Trial
Yes
No
Free/Freemium Version
Yes
No
Premium Consulting/Integration Services
No
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.
Algolia is a specialized tool with the largest customer base, the longest history, and the highest level of R&D investments. They provide exceptional assistance and services and are open to collaborating on feature improvement. The tool itself is very powerful, efficient, and …
Algolia gives way more control for a non-developer than AWS Elasticsearch Service. Previously we'd have to have our developers make adjustments to site search relevancy, typos, prioritizing certain attributes over others, etc. but now the marketing and website team can do that …
There are many open source search products available. Prior to Algolia, we used an in-house search system adopted from an open-source system. While this was nice in that we could modify it in any way we wanted, it also required dedicated engineering and setting up many …
Mostly for instant search capability, then because SFCC option can be easier to use, but front end capabilities where not nice at the time we implemented it. Elasticsearch is more similar with database and index management, but was more expensive at the time + Algolia cartridge …
Algolia easier to implement, whereas Amazon Cloudsearch is more technical to setup. Algolia is faster and has less latency than Amazon Cloudsearch, Algolia seemed to have more features than Amazon Cloudsearch
Offloading search logic to Algolia saved dev time and allowed our engineers to focus on higher-impact features instead of maintaining complex queries or custom search infra.
Before switching to Algolia, we were using SearchSpring. In our experience, the support was slow, the tech felt outdated, and things just didn’t work consistently. The widgets were clunky and limited, and overall it didn’t give us the flexibility or performance we needed. …
Algolia works out of the box, you don't need to setup a lot to see how it works for you. Its also pretty flexible and customizable if you need to. With elasticsearch you have to think about deployment strategies, where to host it, how to send data for it and build custom …
While we evaluated high-performance alternatives like Typesense, we ultimately selected Algolia for its superior "out-of-the-box" search intelligence and business-centric features. Typesense is an impressive, cost-effective engine—especially for developers comfortable with …
Even though CloudSearch is fully integrated into the AWS ecosystem, it is ideal for companies already using AWS services.. Algolia is much faster and focused on high-performance search experiences, with an easier-to-use API interface and better customization capabilities. …
We initially attempted an in-house search solution, which, though tailored to our preferences, demanded significant resources for upkeep. While our internally built search system allowed a deep understanding of rankings, Algolia emerged as a more efficient alternative. …
Algolia prioritizes simplicity and quick setup, excelling in user-friendly search experiences. Elasticsearch offers versatility and complexity, suitable for intricate scenarios, while Amazon CloudSearch provides essential features and seamless integration within the AWS …
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 …
There were few alternatives when we started by using Algolia and it was the better rated in terms of price & performance. Now there are more alternatives, but we keep algolia as is isolated from the rest of our stack so that we can have better performance & control.
Algolia has focused solely on site search for 10+ years, while Google has previously abandoned similar products. Algolia offers end-to-end AI processing, personalization, and automatic query categorization at scale. Deployment and usability is easier with Algolia compared to …
Algolia provides the best user experience, ease of integration and implementation, extremely high performance on large catalogs. The features offered are powerful and complete, with machine learning systems to improve result personalization. The service management can be done …
We tryed to promote Redis as cache solution for application, in order to replace Apache Solr, but it won't go well. Redis best pratices requires some more computer resources. With Elastic Search, the use case was another, and don't compete with Apache Solr.
We have considering AWS search and Elastic search but decide to go with Solr as we need high speed and flexible query, and so far it meets all our requirement so we still continue with Solr.
We tried to use both Elasticsearch and Swiftype with Drupal 8 but there are currently no good modules that integrate Drupal with those solutions. So Solr was really the only option for a Drupal 8 web site. It's not as easy to learn or use as Swiftype, but in the end I think it …
Before using Solr, we used a self-made search engine. Solr has helped us increase our capacity to serve our customers the results they are looking for easily without breaking down. Our previous platform was not dynamic enough to accommodate our growing traffic or smart enough …
Azure Search is not as mature as Apache Solr at this point. So the range of query flexibility is less than Solr. Also, when indexing content goes beyond 1 TB, it might become costly for Azure Search.
Between Solr and ElasticSearch, there is a constant struggle to pick the best one. ElasticSearch is part of ELK and ties in well with LogStash and Kibana which makes it great for logs and big data stuff. Add some logs and see which works best for your particular access methods …
We switched from search indexes stored in mysql to soar and it's made a world of difference for our growing businesses. The relational databases are very poor for handling the complex data searches require and Solr delivered all the tools we need to get the performance our end …
Apache Solr in general stacks up very well to its competitors, it provides much of the same features and performance and has the benefits of being an open-source project with an active contributor base that works consistently and improves the platform. Depending on your setup …
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.
Very effective for end-user searching applications and for generating search results. Also very well suited to those looking for high reliability and performance. If [you're doing] fuzzy searching or if you are working on a smaller end-user application or an internal application that does not require high performance and flexible/adapting searching then it may not be necessary to use Solr.
Algolia is brain-dead simple to set up. I've implemented search with Algolia in a dozen different ways now, and it never took me longer than a few minutes to get the functionality I want. With Algolia, the only challenge is designing your search UI -- if you don't want to use their baked in UI solutions.
Results come back incredibly fast. I'm not sure how Algolia does it, but every keystroke I make in a search field returns new results instantly. It's hard to believe that I'm searching large datasets on a remote server when it works so fast.
Very little customization is needed for 99% of use-cases. Algolia's out of the box setup works great, and it takes no prior knowledge to set up.
Faceted navigation and field collapsing/grouping : filtering and quick results were what we needed for our websites. Our customers needed to have this functionalities for good and efficient results.
We tested them with our customers' registered searches (they received all new goods matching with their registered searches by emails and/or mobile push). Results were incredible by comparison with our old system (old MySQL requests).
Note : we didn't put all our data in Solr. Just what we need for searching uses. Other data stayed in our MySQL database.
Auto-suggest : our old auto-suggest wasn't performing well. With Apache Solr, our new one was worked really well ! The suggestions came quickly and suggestions were good.
We also extended auto-suggestion with geo-spatial data and it worked well.
Hit highlighting : we used this functionality and we didn't have problem and nasty surprise.
Keep all data status during data upgrading (see next details for improvements)
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)
After working 8 years and through 100+ implementations on international sites, Algolia beats the alternatives on several grounds. It offers a fair price that brings a ROI ; It has the financial backbones and the interest in investing in R&D more than any other competitors. It is a true specialized and not an add-on, and thus benefits from a very strong engineering and innovative approach. The tool is very reliable and fast
Algolia is very intuitive to use, especially the Merchandising Studio. The application provides a virtually seamless view of how product will appear on the frontend and making adjustments is fluid and reflects immediately online. Some slow-down occurs when you have a lot of rules enabled or are pinning / boosting a lot of product. But overall it functions very solidly.
It takes some time to deploy and currectly maintein it. And also, to learn how to use and integrate in the enviroment as well. Once you get theses steps done, it usability is very simple, and almost of the time it don't require no further attention on it. Even for maintence, if you deploy it on a cluster mode, it is very reliable and easy to take one host down.
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
Algolia is a specialized tool with the largest customer base, the longest history, and the highest level of R&D investments. They provide exceptional assistance and services and are open to collaborating on feature improvement. The tool itself is very powerful, efficient, and reliable. More technical and less pretty than most of its competitors who are trying to make the UI friendly, but with far more features and a continuous improvement with the latest technologies.
We switched from search indexes stored in MySQL to soar and it's made a world of difference for our growing businesses. The relational databases are very poor for handling the complex data searches require and Solr delivered all the tools we need to get the performance our end users are demanding.
Algolia has been a consistent product that works flawless with very few errors or downtime. With the plan options it’s very easy for us to scale especially with this usage pricing. We have 100% gotten our ROI on this product.
It's enabled us to deliver fast, relevant search results on our new website. The site is still in beta and being actively developed so our complete ROI is still unknown.
It integrates very well with Drupal so it has saved us from having to develop a custom solution.