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
IBM Security QRadar SIEM
Score 8.6 out of 10
N/A
IBM Security QRadar is security information and event management (SIEM) Software.
N/A
Pricing
Algolia
IBM Security QRadar SIEM
Editions & Modules
Build
$0
per month Up to 10,000 search requests + 1 Million records
Grow
$0.50
per month per 1,000 search requests
Algolia Recommend
$0.60
per month per 1,000 Recommend requests
Premium
Custom
per month Customized pricing
Elevate
custom
per year
No answers on this topic
Offerings
Pricing Offerings
Algolia
IBM Security QRadar SIEM
Free Trial
Yes
Yes
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.
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.
I would only recommend IBM Security QRadar SIEM in a few situations. For one, it's very easy to setup and use if all your log sources are generic from known vendors. It's also significantly cheaper than Splunk, which is nice if you're trying to save money or be more efficient. I would not recommend IBM Security QRadar SIEM for environments with a lot of custom logs and complicated detection requirements.
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.
Need to spend more time configuring the system to properly interpret and normalize different type of data collected from multiple resources.
While Rule creation QRadar uses that rules to detect security threats and generate alerts, but to creating and managing rules is bit complex & tedious work to complete.
IBM Security QRadar SIEM is excellent in handling large & complex systems that requires in-depth knowledge and extensive training to configure and maintain the system which includes upgrading, optimization of performance & issue troubleshooting.
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.
QRadar is an established and stable product, we have been using it for many years and want to continue to focus on it. Anyone who has used the product and knows it knows how reliable it is and how it facilitates continuous monitoring of threats from outside and inside. it is an exceptional product that is very useful for us.
Algolia has a good interface and they have done some improvements. However, some non technical users have a challenging time in the use for the first days of learning. But once the main aspects are learned is a straight forward operation
As a grade I give 8 as QRadar is not easy to learn. It requires some time to master it. It also needs a team of people actively working on the product. Once you learn to use it the software works very well and it is easy to correlate and understand detected threats. It only takes time to learn how to use it well and configure it properly.
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
Customer support is Good of IBM, While Using IBM QRadar its deployment is to slow and suddenly stop working and crashed we have contacted IBM Support and Rised a Ticket within a few minute we get call back from customer support and Query Resolved by them Fast And Rapid Support of Ibm
The training was very useful and the people who taught us were very knowledgeable. Although the software may initially seem difficult to learn they made things much easier for us.
The training was very useful and the people who taught us were very knowledgeable. Although the software may initially seem difficult to learn they made things much easier for us.
Initial patience is required to learn how to use the product, and it takes a dedicated team to use it. One person is not enough, and it's not enough to just set it up and check it once in a while. It has to be used daily and kept under control to be used effectively
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.
IBM Qradar takes the best from its competitors. Reliable and stable but sometimes very expensive, the SIEM from IBM offers a wide range of scenarios in which the customers can suite and size their own infrastructures. IBM Qradar doesn't really needs to stack up againt its competitors because it already sets an example in the SIEM world.
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.