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
PostgreSQL
Score 8.8 out of 10
N/A
PostgreSQL (alternately Postgres) is a free and open source object-relational database system boasting over 30 years of active development, reliability, feature robustness, and performance. It supports SQL and is designed to support various workloads flexibly.
N/A
Pricing
Algolia
PostgreSQL
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
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Offerings
Pricing Offerings
Algolia
PostgreSQL
Free Trial
Yes
No
Free/Freemium Version
Yes
No
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.
Algolia was by far and away the easiest of the three to implement. PostgreSQL has many search modules that can be used on top of your usual database, however, none are particularly efficient and can quickly become overwhelmed at scale. Equally, they do not handle business …
I'd definitely recommend Algolia for a business operating in the ecommerce space and looking to integrate search quickly. Using the tool is easy to set up and works well. Out of the box you can have search, autocomplete, and recommendations that are all integrated. If you integrate directly, Algolia works well for also using their internal A/B test system. Areas where Algolia can be harder to use are in user-generated marketplaces. On a site where you control / own / produce all your inventory of results, you are solely optimizing for revenue/conversion. When you have a platform where there are different creators for each item, you need to balance revenue optimization with trying to support the business goals of the sellers on your marketplace platform. Algolia offers less tooling there which can be difficult and will require you build additional tooling/monitoring for that. Given that need, you likely cannot use all of Algolia's UI tools like A/B testing.
PostgreSQL is best used for structured data, and best when following relational database design principles. I would not use PostgreSQL for large unstructured data such as video, images, sound files, xml documents, web-pages, especially if these files have their own highly variable, internal structure.
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.
Recent pricing model changes made Algolia considerably more expensive. I understand that companies change their models all the time, but my plan almost doubled in price overnight. They let me keep my legacy plan for as long as I wanted, but I had already outgrown it, so a small increase in demand caused big price spikes. It's still cheap for what it is though.
The documentation is generally good, but sometimes hard to navigate. I was trying to find examples of how to combine geo-queries with normal ones, and I couldn't find an example, but it wasn't actually hard to figure out.
Some of the advanced features can be hard to understand at first. This isn't really a con, as it just means Algolia is loaded with features, but I was a bit overwhelmed the first time I tried to customize an index.
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.
Postgresql is the best tool out there for relational data so I have to give it a high rating when it comes to analytics, data availability and consistency, so on and so forth. SQL is also a relatively consistent language so when it comes to building new tables and loading data in from the OLTP database, there are enough tools where we can perform ETL on a scalable basis.
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.
The data queries are relatively quick for a small to medium sized table. With complex joins, and a wide and deep table however, the performance of the query has room for improvement.
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
There are several companies that you can contract for technical support, like EnterpriseDB or Percona, both first level in expertise and commitment to the software.
But we do not have contracts with them, we have done all the way from googling to forums, and never have a problem that we cannot resolve or pass around. And for dozens of projects and more than 15 years now.
The online training is request based. Had there been recorded videos available online for potential users to benefit from, I could have rated it higher. The online documentation however is very helpful. The online documentation PDF is downloadable and allows users to pace their own learning. With examples and code snippets, the documentation is great starting point.
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.
Although the competition between the different databases is increasingly aggressive in the sense that they provide many improvements, new functionalities, compatibility with complementary components or environments, in some cases it requires that it be followed within the same family of applications that performs the company that develops it and that is not all bad, but being able to adapt or configure different programs, applications or other environments developed by third parties apart is what gives PostgreSQL a certain advantage and this diversification in the components that can be joined with it, is the reason why it is a great option to choose.
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.
Easy to administer so our DevOps team has only ever used minimal time to setup, tune, and maintain.
Easy to interface with so our Engineering team has only ever used minimal time to query or modify the database. Getting the data is straightforward, what we do with it is the bigger concern.
