Mobile apps live or die by their search experience. Whether you're building a product catalog, content discovery, or an in-app search bar, the API behind it determines latency, relevance, and user retention.
The challenge is that mobile search has constraints desktop doesn't: variable network conditions, need for offline support, limited screen real estate, and SDK size budgets. A search API that works great in a web backend might feel sluggish on a 3G connection with 200ms added round-trip time.
This comparison covers the best search APIs for mobile app development in 2026, focusing on mobile SDK availability, latency characteristics, and pricing that scales with your user base.
Key Takeaways
- SearchHive SwiftSearch provides a lightweight mobile SDK with built-in caching and autocomplete, starting free
- Algolia remains the mobile search leader with native iOS/Android SDKs and sub-100ms median latency, but pricing scales steeply
- Typesense offers an open-source, self-hostable alternative with a small native SDK footprint
- Meilisearch is the best choice for teams wanting open-source with minimal operational overhead
- Elastic App Search suits enterprise apps already in the Elastic ecosystem
- Google Custom Search API works for simple cases but lacks the SDK quality and features of dedicated search platforms
1. SearchHive SwiftSearch
Best for: Apps needing web search integration, AI-powered results, unified search + content
SwiftSearch offers a purpose-built mobile SDK for iOS and Android that handles the specific challenges of mobile search: network variability, battery optimization, and small payload sizes.
Pricing:
| Plan | Price | Queries/Month |
|---|---|---|
| Free | $0/mo | 500 searches |
| Starter | $12/mo | 2,000 searches |
| Pro | $39/mo | 10,000 searches |
| Business | $99/mo | 50,000 searches |
The mobile SDK is under 500KB, supports offline caching of recent results, and includes built-in autocomplete that works locally while fetching fresh results in the background.
# SearchHive SwiftSearch — mobile integration example
from searchhive import SwiftSearch
client = SwiftSearch(api_key="sh_live_...")
# Search with mobile-optimized response (smaller payload)
results = client.search(
query="best coffee shops near me",
engine="google",
mobile=True, # Returns mobile-formatted results
geo_location="13.7563,100.5018" # Bangkok coordinates
)
for r in results[:5]:
print(f"{r.title}")
print(f" {r.snippet[:100]}...")
For iOS/Android, the native SDKs handle connection pooling, request deduplication, and automatic retries with exponential backoff. This matters on mobile where spotty connections are the norm, not the exception.
The unified platform is a differentiator — if your app also needs web scraping or deep research capabilities, SwiftSearch shares an API key and SDK with ScrapeForge and DeepDive.
2. Algolia
Best for: E-commerce and content apps needing instant, typo-tolerant search
Algolia is the established market leader for mobile search. Their mobile SDKs for iOS (Swift) and Android (Kotlin) are mature, well-documented, and include UI components out of the box.
Pricing:
| Plan | Price | Records | Requests/Month |
|---|---|---|---|
| Free | $0/mo | 10,000 | 100,000 |
| Standard | $1/mo | 30,000 | 1M |
| Premium | Custom | Custom | Custom |
| Elevate | Custom | Custom | Custom |
Algolia's free tier covers 10K records and 100K search requests — enough to prototype and launch a small app. The Standard plan at $1/month for 1M requests is extremely competitive.
The real cost appears at scale. Premium pricing kicks in when you need advanced features like AI relevance tuning, custom ranking, or multi-index search. Enterprise plans start around $10K/year.
// Algolia iOS SDK
import AlgoliaSearchClient
let client = SearchClient(appID: "YOUR_APP_ID", apiKey: "YOUR_API_KEY")
let index = client.index(withName: "products")
index.search(query: "wireless headphones") { result in
switch result {
case .success(let response):
for hit in response.hits {
print(hit["name"] as? String ?? "")
}
case .failure(let error):
print(error)
}
}
Algolia's median search latency is under 100ms globally, thanks to their distributed network. For mobile apps where every millisecond of perceived latency affects engagement, this matters.
3. Typesense
Best for: Teams wanting open-source search with a small SDK footprint
Typesense is an open-source, typo-tolerant search engine with native SDKs for iOS and Android. Self-hosting means no per-query costs.
Pricing:
| Plan | Price | Records | Queries |
|---|---|---|---|
| Self-hosted | Free | Unlimited | Unlimited |
| Cloud Free | $0/mo | 10,000 | 100,000 |
| Cloud Growth | $29/mo | 100,000 | 1,000,000 |
| Cloud Pro | $99/mo | 1,000,000 | 10,000,000 |
The self-hosted option has zero query costs. The cloud pricing is competitive with Algolia at the free tier (identical limits) and offers 2x the records at $29/month versus Algolia's equivalent tier.
# Typesense Python client
import typesense
client = typesense.Client({
'api_key': 'your_key',
'nodes': [{'host': 'localhost', 'port': '8108', 'protocol': 'http'}]
})
results = client.collections['products'].documents.search({
'q': 'wireless headphones',
'query_by': 'name,description',
'num_typos': 2
})
for hit in results['hits']:
print(hit['document']['name'])
Typesense's mobile SDK size is under 200KB — smaller than Algolia's. The tradeoff is that the self-hosted version requires you to manage infrastructure, scaling, and high availability yourself. The cloud option removes this burden.
4. Meilisearch
Best for: Teams wanting open-source with minimal setup, good relevance out of the box
Meilisearch provides typo-tolerant, filterable search with minimal configuration. It's open-source (MIT license) with optional cloud hosting.
Pricing:
| Plan | Price | Records | Queries |
|---|---|---|---|
| Self-hosted | Free | Unlimited | Unlimited |
| Cloud Free | $0/mo | 5,000 | 50,000 |
| Cloud Dev | $30/mo | 500,000 | 5,000,000 |
| Cloud Prod | $120/mo | 10,000,000 | 100,000,000 |
The self-hosted version is straightforward to deploy — a single binary with no external dependencies. Docker, Kubernetes, and bare-metal all work. The official mobile SDKs for iOS and Android handle indexing and search.
import meilisearch
client = meilisearch.Client('http://localhost:7700', 'master_key')
index = client.index('products')
results = index.search('wireless headphones', {
'limit': 20,
'attributesToRetrieve': ['name', 'price', 'image']
})
for hit in results['hits']:
print(hit['name'], hit['price'])
Meilisearch's relevance out of the box is strong. It uses a built-in ranking algorithm that handles proximity, typo tolerance, and attribute priority without manual tuning. For mobile apps where you want to ship search quickly without a relevance engineering team, this is a real advantage.
5. Elastic App Search
Best for: Enterprise apps in the Elastic ecosystem
Elastic App Search provides managed search with a REST API and client libraries. If your backend already runs Elasticsearch, this is the natural extension.
Pricing:
| Plan | Price | Records | Queries |
|---|---|---|---|
| Free | $0/mo | 10,000 | 100,000 |
| Standard | $95/mo | 500,000 | 1,000,000 |
| Enterprise | Custom | Custom | Custom |
Elastic's mobile SDKs are functional but less polished than Algolia's. The focus is on the server-side API — most mobile integrations go through a backend rather than calling App Search directly from the app.
For enterprise apps with existing Elasticsearch infrastructure, the integration is seamless. For standalone mobile apps, the $95/month floor and less mature mobile SDK make it a harder sell.
6. Google Custom Search API
Best for: Prototyping, simple web search integration, Google Workspace users
Google's Custom Search API is the simplest option for adding web search to a mobile app. It's not a search-as-you-type platform — it's a programmatic interface to Google's web search.
Pricing:
| Plan | Price | Queries |
|---|---|---|
| Free | $0 | 100/day (3,000/month) |
| Paid | $5/1,000 queries | No minimum |
The free tier of 3,000 queries/month covers a small app with modest search usage. At $5 per 1,000 queries, the paid tier is straightforward but lacks advanced features — no autocomplete, no faceting, no typo tolerance.
from googleapiclient.discovery import build
service = build("customsearch", "v1", developerKey="your_key")
results = service.cse().list(
q="best coffee shops",
cx="your_search_engine_id",
num=10
).execute()
for item in results.get("items", []):
print(item["title"], item["link"])
Google Custom Search works for apps that need web search results directly. It doesn't provide a custom search experience over your own data — for that, you need one of the dedicated platforms above.
Comparison Table
| API | Mobile SDK | Free Tier | Entry Price | Autocomplete | Offline Cache | Typo Tolerance |
|---|---|---|---|---|---|---|
| SwiftSearch | iOS + Android | 500/mo | $12/mo | Yes | Yes | N/A (web search) |
| Algolia | iOS + Android | 100K/mo | $1/mo | Yes | Yes | Yes |
| Typesense | iOS + Android | 100K/mo | $0 (self-host) | Partial | No | Yes |
| Meilisearch | iOS + Android | 50K/mo | $0 (self-host) | Partial | No | Yes |
| Elastic App Search | REST client | 100K/mo | $95/mo | Yes | No | Yes |
| Google CSE | HTTP only | 3K/mo | $5/1K | No | No | No |
Recommendation
For mobile apps needing web search (searching the internet from within your app), SearchHive SwiftSearch is the best option — purpose-built mobile SDK, offline caching, and the only option here with both search and scraping capabilities under one platform.
For in-app search over your own data, the choice depends on your scale and infrastructure preferences:
- Algolia for apps where latency and polish matter most, and budget allows
- Typesense for teams comfortable self-hosting or wanting open-source
- Meilisearch for the best relevance with least configuration
Building a mobile app that needs search? SearchHive SwiftSearch offers a free tier and native mobile SDKs with built-in caching. Get started with the docs.