The honest comparison — pricing, AI capabilities, setup complexity, and who each one is actually built for.
All three are legitimate products used by large companies. The right choice depends on your infrastructure, budget, team size, and how much AI relevance matters to your users. This page breaks it down without the marketing fluff.
Hosted search-as-a-service. Excellent out-of-the-box relevance, beautifully designed SDKs, and fast implementation. Pricing becomes a concern at scale — typically $500–$2,000+/mo for mid-size catalogs.
The open-source workhorse. Infinitely flexible, runs anywhere, handles massive scale. But it requires real DevOps investment — relevance tuning, cluster management, and search expertise are not optional.
Microsoft's managed AI search service. Built-in vector search, semantic ranking, and OCR. Predictable, index-size-based pricing. Ideal for teams already in the Azure ecosystem or who want managed AI without the Algolia price tag.
| Feature | Algolia | Elasticsearch | Azure AI Search | RayoSearch |
|---|---|---|---|---|
| Pricing model | Records + operations | Self-hosted / Elastic Cloud | Index size (SUs) | Per site, flat monthly |
| Starting cost | ~$50–100/mo | Free (self-host) | ~$25/mo | Free beta |
| At-scale cost | $$$ (operations-based) | $ (infra cost) | $$ | $ |
| Managed hosting | ✓ | ± (Elastic Cloud) | ✓ | ✓ |
| Setup complexity | Low | High | Medium | Very Low |
| Vector / semantic AI | ± (NeuralSearch add-on) | ± (manual config) | ✓ (built-in) | ✓ (via Azure) |
| Typo tolerance | ✓ | ± (fuzzy config) | ✓ | ✓ |
| UI widget / embed | ± (InstantSearch) | ✗ | ✗ | ✓ (visual builder) |
| No-code widget builder | ✗ | ✗ | ✗ | ✓ |
| Analytics dashboard | ✓ (paid plans) | ± (Kibana) | ± (Azure Monitor) | ✓ |
| Custom ranking | ✓ | ✓ | ✓ | ✓ |
| Multi-language | ✓ | ✓ | ✓ | ✓ |
| Open source | ✗ | ✓ | ✗ | ✗ |
| Works without devs | ± (JS SDK needed) | ✗ | ✗ | ✓ (1 script tag) |
Pricing and features reflect publicly available information as of March 2026 and may change. ✓ = fully supported · ± = partial / add-on required · ✗ = not supported
Search pricing models are notoriously confusing. Here's what they actually cost.
Algolia charges per search operation and per record stored. On the free plan you get 10k records and 10k operations/month — this evaporates fast. A mid-size e-commerce store with 50k products and 100k monthly searches can easily hit $500–$1,500/month. NeuralSearch (their AI relevance feature) is an additional cost on top of the base plan.
Open-source Elasticsearch is free to run, but "free" means paying for servers, storage, and the DevOps engineer who manages it. Elastic Cloud (their managed service) starts at ~$16/month but gets expensive quickly with storage and compute. Relevance engineering is manual — expect to invest significant time in query tuning.
Azure AI Search charges by Search Unit (SU) — a combination of replicas and partitions. A basic tier starts at ~$25/mo per SU. Pricing scales with index size and query volume, but is far more predictable than operations-based models. Vector search and semantic ranking are included in standard tiers.
RayoSearch is free during beta. Post-beta pricing will be per-site and flat monthly — you bring your own Azure AI Search index, and RayoSearch adds the widget layer, analytics, and builder on top. No per-operation fees, no record limits imposed by us.
Algolia, Elasticsearch, and Azure AI Search are all search infrastructure. They give you an API. You still have to build the search UI, connect it to your data, design the widget, handle edge cases, and build an analytics layer.
RayoSearch is the layer on top of Azure AI Search that gives you all of that — a visual widget builder, a one-line embed, and an analytics dashboard — without any of the infrastructure work.
Start free during beta →Connect your index, design your widget, paste one script tag. RayoSearch makes your Azure AI Search index user-facing — without writing a single line of UI code.
Request beta access →Free during beta · No credit card required
We're onboarding a small group of early users. Beta members get full access, hands-on onboarding support, and a direct line to shape the product roadmap.
We'll review your application and reach out within 2–3 business days.