Backmesh ist ein Open-Source Backend as a Service (BaaS), das für KI-Anwendungen entwickelt wurde. Es fungiert als sicheres LLM-API-Gateway und ermöglicht Entwicklern, LLM-APIs wie OpenAI und Gemini direkt von Web- oder mobilen Apps aufzurufen, ohne private Schlüssel preiszugeben. Es bietet Funktionen wie JWT-Authentifizierung, Ratenbegrenzung pro Benutzer und integrierte Analysen zur effektiven Verwaltung und Überwachung der API-Nutzung.
Supabase ist eine Open-Source-Alternative zu Firebase und bietet eine komplette Backend-Lösung auf Basis von Postgres. Es bietet eine Reihe von Tools, darunter eine Datenbank, Authentifizierung, sofortige APIs, Edge-Funktionen, Echtzeit-Abonnements, Speicher und Vektor-Embeddings, um die Anwendungsentwicklung vom Prototyp bis zur Produktion zu beschleunigen.
Produktübersicht
Backmesh Produktübersicht
Backmesh ist ein Open-Source Backend as a Service (BaaS), das für KI-Anwendungen entwickelt wurde. Es fungiert als sicheres LLM-API-Gateway und ermöglicht Entwicklern, LLM-APIs wie OpenAI und Gemini direkt von Web- oder mobilen Apps aufzurufen, ohne private Schlüssel preiszugeben. Es bietet Funktionen wie JWT-Authentifizierung, Ratenbegrenzung pro Benutzer und integrierte Analysen zur effektiven Verwaltung und Überwachung der API-Nutzung.
Supabase Produktübersicht
Supabase ist eine Open-Source-Alternative zu Firebase und bietet eine komplette Backend-Lösung auf Basis von Postgres. Es bietet eine Reihe von Tools, darunter eine Datenbank, Authentifizierung, sofortige APIs, Edge-Funktionen, Echtzeit-Abonnements, Speicher und Vektor-Embeddings, um die Anwendungsentwicklung vom Prototyp bis zur Produktion zu beschleunigen.
Detailed feature comparison
| Feature | Backmesh | Supabase |
|---|---|---|
| Hauptkategorie | API | Backend |
| Hinzugefügt | 2025-08-11 | 2025-08-10 |
| Preismodell | Freemium | Freemium |
| Offizielle Website | backmesh.com | supabase.com |
| Produkttyp | Website | Website |
| Performance data | ||
| Nutzerbewertung | Nicht verifiziert | Nicht verifiziert |
| Kommentare | 0 | 0 |
| Monatliche Besuche | 118 | 29.3M |
| Monatliches Wachstum | -49.8% | 11.7% |
| Favoriten | 120 | 125 |
| Details | Details ansehen | Details ansehen |
Backmesh vs Supabase monthly traffic
Compare Backmesh and Supabase by monthly reach, traffic trend, visit depth, top regions, and acquisition sources.
How to interpret the traffic data
In the Backmesh vs Supabase monthly traffic comparison, Backmesh currently shows 118 visits and Supabase shows 29.3M; Supabase has about 247,904.8 times the visible traffic of Backmesh, an absolute difference of about 29.3M visits. This reflects visible reach, not feature quality or paid users.
Both tools provide verified traffic details, so monthly trends, visit depth, regions, and acquisition sources can be compared on the same basis.
Backmesh monthly traffic:
Latest traffic
Monthly traffic trend
- 2025/9: 1.1K Monatliche Besuche
- 2026/1: 1.2K Monatliche Besuche
- 2026/2: 1.1K Monatliche Besuche
- 2026/3: 424 Monatliche Besuche
- 2026/4: 235 Monatliche Besuche
- 2026/5: 118 Monatliche Besuche
Top-Regionen
Top 5 countries/regions
| Country/region | Percentage | Traffic |
|---|---|---|
| 🇩🇴Dominican Republic | 100% | 118 |
Suchbegriffe
Supabase monthly traffic:
Latest traffic
Monthly traffic trend
- 2025/9: 13.8M Monatliche Besuche
- 2026/1: 18.6M Monatliche Besuche
- 2026/2: 20.1M Monatliche Besuche
- 2026/3: 25.3M Monatliche Besuche
- 2026/4: 26.2M Monatliche Besuche
- 2026/5: 29.3M Monatliche Besuche
Top-Regionen
Top 5 countries/regions
| Country/region | Percentage | Traffic |
|---|---|---|
| 🇺🇸United States | 47.42% | 13.9M |
| 🇮🇳India | 23% | 6.7M |
| 🇧🇷Brazil | 13.44% | 3.9M |
| 🇬🇧United Kingdom | 8.16% | 2.4M |
| 🇵🇰Pakistan | 7.98% | 2.3M |
Traffic-Quellen
| Source type | Percentage | Traffic |
|---|---|---|
| Direkt | 94.28% | 27.6M |
| Verweis | 3.43% | 1M |
| 2.29% | 669.9K |
Suchbegriffe
Usage comparison
Compare the core capabilities of Backmesh and Supabase
Backmesh Core features
Supabase Core features
Use cases
Backmesh Use cases
Supabase Use cases
Backmesh vs Supabase:In-depth comparison and selection guidance
First decide whether the products solve the same kind of need
This in-depth Backmesh vs Supabase comparison uses only the product records, taxonomy, audience, traffic, and community signals available on this page. Backmesh is primarily listed under “API”, while Supabase is primarily listed under “Backend”, so the first decision is whether your actual task matches their recorded scope.
The structured fields currently show these decision-relevant differences: Primary category (Backmesh: API; Supabase: Backend); Monthly visits (Backmesh: 118; Supabase: 29.3M); Monthly growth (Backmesh: -49.8%; Supabase: 11.7%); Favorites (Backmesh: 120; Supabase: 125); Website (Backmesh: backmesh.com; Supabase: supabase.com). These facts are more useful for selection than brand visibility alone.
What market visibility and monthly traffic mean
In the Backmesh vs Supabase monthly traffic comparison, Backmesh currently shows 118 visits and Supabase shows 29.3M; Supabase has about 247,904.8 times the visible traffic of Backmesh, an absolute difference of about 29.3M visits. This reflects visible reach, not feature quality or paid users.
Both tools provide verified traffic details, so monthly trends, visit depth, regions, and acquisition sources can be compared on the same basis.
If public market visibility is an important first-pass criterion, investigate Supabase first. The final choice should still follow taxonomy, use case, and a real trial because higher traffic does not prove broader capabilities or better workflow fit.
Product positioning, use cases, and roles
Backmesh and Supabase currently overlap in shared categories: Backend; shared tags: BaaS, Entwicklerwerkzeuge, Open Source und Serverless. This can place both on the same shortlist, but it does not prove equal implementation, depth, or cost.
Backmesh's unique categories/tags are API, No-Code, Anthropic, API-Gateway, API-Management, Backend, Gemini und Großes Sprachmodell; Supabase's are Datenbank, Plattform als Dienst, No-Code & Low-Code, KI, Authentifizierung, Backend als Dienst, Firebase-Alternative und Postgres. These unique fields are the strongest differentiators: validate the product whose recorded scope matches the task instead of following traffic alone.
What ratings, comments, and favorites can tell you
Backmesh has no verified rating, 0 comments, 120 favorites, and 118 likes;Supabase has no verified rating, 0 comments, 125 favorites, and 136 likes。
Neither product has enough rating or comment samples for a credible reputation ranking.
Selection guidance by actual need
When to evaluate Backmesh first
Put Backmesh on the priority trial list when the task aligns with “API” and especially API, No-Code, Anthropic, API-Gateway, API-Management und Backend. This follows recorded positioning and does not imply unlisted capabilities are absent.
Backmesh also currently records: pricing is freemium, product type is website, 118 verified monthly visits, no verified user rating. Verify any hard requirement around price, platform, or reach before trial, and do not let sparse review data substitute for testing.
When to evaluate Supabase first
Put Supabase on the priority trial list when the task aligns with “Backend” and especially Datenbank, Plattform als Dienst, No-Code & Low-Code, KI, Authentifizierung und Backend als Dienst. This follows recorded positioning and does not imply unlisted capabilities are absent.
Supabase also currently records: pricing is freemium, product type is website, 29.3M verified monthly visits, no verified user rating. Verify any hard requirement around price, platform, or reach before trial, and do not let sparse review data substitute for testing.
How to validate the recommendation before deciding
The available data describes positioning, public visibility, and community signals, but it cannot prove output quality, speed, integration effort, privacy, or long-term cost in your workflow. Before deciding, run the same representative tasks in Backmesh and Supabase, then record completion time, accuracy, manual corrections, and the real paid threshold. A like-for-like trial turns this comparison into a defensible adoption decision.




