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MongoDB
Base de Datos Vectorial · 5.8M visitas mensuales

MongoDB es una plataforma de datos para desarrolladores construida sobre una base de datos de documentos NoSQL líder. Su oferta en la nube, MongoDB Atlas, proporciona un conjunto integrado de servicios, incluida una potente Búsqueda Vectorial para IA generativa, búsqueda de texto completo y análisis en tiempo real. Está diseñada para aplicaciones modernas, ofreciendo flexibilidad, escalabilidad y una experiencia unificada para que los desarrolladores construyan más rápido y de manera más eficiente en múltiples nubes.

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SingleStore
Base de Datos Vectorial · 161K visitas mensuales

SingleStore es una plataforma de datos de alto rendimiento y en tiempo real diseñada para IA empresarial y aplicaciones intensivas en datos. Unifica cargas de trabajo transaccionales (OLTP) y analíticas (OLAP), incluida la búsqueda vectorial, en una única base de datos SQL distribuida, ofreciendo latencia de milisegundos a escala.

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MongoDB vs SingleStore: precios, funciones y tráfico

Compara MongoDB y SingleStore por posicionamiento, precio, capacidades, tráfico y opiniones.

Actualizado 5 ago 2026

Resumen del producto

MongoDB Resumen del producto

MongoDB es una plataforma de datos para desarrolladores construida sobre una base de datos de documentos NoSQL líder. Su oferta en la nube, MongoDB Atlas, proporciona un conjunto integrado de servicios, incluida una potente Búsqueda Vectorial para IA generativa, búsqueda de texto completo y análisis en tiempo real. Está diseñada para aplicaciones modernas, ofreciendo flexibilidad, escalabilidad y una experiencia unificada para que los desarrolladores construyan más rápido y de manera más eficiente en múltiples nubes.

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SingleStore Resumen del producto

SingleStore es una plataforma de datos de alto rendimiento y en tiempo real diseñada para IA empresarial y aplicaciones intensivas en datos. Unifica cargas de trabajo transaccionales (OLTP) y analíticas (OLAP), incluida la búsqueda vectorial, en una única base de datos SQL distribuida, ofreciendo latencia de milisegundos a escala.

Preview

Detailed feature comparison

FeatureMongoDBSingleStore
Categoría principalBase de Datos VectorialBase de Datos Vectorial
Añadido2025-08-062025-08-15
PrecioFreemiumFreemium
Sitio oficialwww.mongodb.comwww.singlestore.com
Tipo de productoSitio webSitio web
Performance data
ValoraciónSin verificarSin verificar
Comentarios00
Visitas mensuales5.8M161K
Crecimiento mensual-6.2%31.5%
Favoritos127132
DetailsVer detallesVer detalles

MongoDB vs SingleStore monthly traffic

Compare MongoDB and SingleStore by monthly reach, traffic trend, visit depth, top regions, and acquisition sources.

How to interpret the traffic data

In the MongoDB vs SingleStore monthly traffic comparison, MongoDB currently shows 5.8M visits and SingleStore shows 161K; MongoDB has about 36.3 times the visible traffic of SingleStore, an absolute difference of about 5.7M 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.

MongoDB monthly traffic:

Latest traffic

Visitas mensuales
5.8M
Duración media
6:09
Páginas por visita
8.88
Tasa de rebote
31.08%
Data updated 2026-06-15

Monthly traffic trend

  • 2025/9: 5.6M Visitas mensuales
  • 2026/1: 5.8M Visitas mensuales
  • 2026/2: 5.5M Visitas mensuales
  • 2026/3: 6.1M Visitas mensuales
  • 2026/4: 6.2M Visitas mensuales
  • 2026/5: 5.8M Visitas mensuales

Regiones principales

Top 5 countries/regions
Country/regionPercentageTraffic
🇮🇳India58.41%3.4M
🇺🇸United States26.77%1.6M
🇬🇧United Kingdom5.84%341.3K
🇵🇰Pakistan4.71%275.2K
🇨🇴Colombia4.27%249.5K

Fuentes de tráfico

Source typePercentageTraffic
Directo86.31%5M
Referido10.12%591.4K
Correo electrónico3.57%208.6K

Palabras clave

atlasmongo dbmongodbmongodb atlasmongodb compass

SingleStore monthly traffic:

Latest traffic

Visitas mensuales
161K
Duración media
2:48
Páginas por visita
5.62
Tasa de rebote
37.01%
Data updated 2026-06-15

Monthly traffic trend

  • 2025/9: 178.9K Visitas mensuales
  • 2026/1: 167.6K Visitas mensuales
  • 2026/2: 141.6K Visitas mensuales
  • 2026/3: 156.9K Visitas mensuales
  • 2026/4: 122.5K Visitas mensuales
  • 2026/5: 161K Visitas mensuales

Regiones principales

Top 5 countries/regions
Country/regionPercentageTraffic
🇮🇳India62.41%100.5K
🇺🇸United States19.21%30.9K
🇰🇷Korea, Republic of9.24%14.9K
🇭🇷Croatia5.14%8.3K
🇵🇹Portugal4%6.4K

Fuentes de tráfico

Source typePercentageTraffic
Directo70.02%112.7K
Referido20.65%33.3K
Correo electrónico9.33%15K

Palabras clave

single storesinglestoresinglestore careerssoftmaxsoftmax function
Traffic-based selection guidance: If public market visibility is an important first-pass criterion, investigate MongoDB 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.

Usage comparison

Compare the core capabilities of MongoDB and SingleStore

MongoDB Core features

Base de Datos Vectorial
Backend
Base de Datos
Gestión de Datos

SingleStore Core features

Base de Datos Vectorial
Base de datos
Backend

Use cases

MongoDB Use cases

Base de datos en la nube
base de datos
IA generativa
Atlas
Backend
gestión de datos
plataforma para desarrolladores
NoSQL
escalabilidad
Búsqueda vectorial

SingleStore Use cases

Base de datos en la nube
base de datos
IA generativa
plataforma de datos
OLAP
OLTP
Generación Aumentada por Recuperación
Análisis en tiempo real
SQL
Base de datos vectorial

MongoDB vs SingleStore：In-depth comparison and selection guidance

First decide whether the products solve the same kind of need

This in-depth MongoDB vs SingleStore comparison uses only the product records, taxonomy, audience, traffic, and community signals available on this page. MongoDB is primarily listed under “Base de Datos Vectorial”, while SingleStore is primarily listed under “Base de Datos Vectorial”, so the first decision is whether your actual task matches their recorded scope.

The structured fields currently show these decision-relevant differences: Monthly visits (MongoDB: 5.8M; SingleStore: 161K); Monthly growth (MongoDB: -6.2%; SingleStore: 31.5%); Favorites (MongoDB: 127; SingleStore: 132); Website (MongoDB: www.mongodb.com; SingleStore: www.singlestore.com); Added (MongoDB: 2025-08-06; SingleStore: 2025-08-15). These facts are more useful for selection than brand visibility alone.

What market visibility and monthly traffic mean

In the MongoDB vs SingleStore monthly traffic comparison, MongoDB currently shows 5.8M visits and SingleStore shows 161K; MongoDB has about 36.3 times the visible traffic of SingleStore, an absolute difference of about 5.7M 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 MongoDB 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

MongoDB and SingleStore currently overlap in shared categories: Base de Datos Vectorial; shared tags: Base de datos en la nube, base de datos e IA generativa. This can place both on the same shortlist, but it does not prove equal implementation, depth, or cost.

MongoDB's unique categories/tags are Backend, Base de Datos, Gestión de Datos, Atlas, gestión de datos, plataforma para desarrolladores, NoSQL y escalabilidad; SingleStore's are Base de datos, Backend, plataforma de datos, OLAP, OLTP, Generación Aumentada por Recuperación, Análisis en tiempo real y SQL. 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

MongoDB has no verified rating, 0 comments, 127 favorites, and 123 likes；SingleStore has no verified rating, 0 comments, 132 favorites, and 132 likes。

Neither product has enough rating or comment samples for a credible reputation ranking.

Selection guidance by actual need

When to evaluate MongoDB first

Put MongoDB on the priority trial list when the task aligns with “Base de Datos Vectorial” and especially Backend, Base de Datos, Gestión de Datos, Atlas, gestión de datos y plataforma para desarrolladores. This follows recorded positioning and does not imply unlisted capabilities are absent.

MongoDB also currently records: pricing is freemium, product type is website, 5.8M 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 SingleStore first

Put SingleStore on the priority trial list when the task aligns with “Base de Datos Vectorial” and especially Base de datos, Backend, plataforma de datos, OLAP, OLTP y Generación Aumentada por Recuperación. This follows recorded positioning and does not imply unlisted capabilities are absent.

SingleStore also currently records: pricing is freemium, product type is website, 161K 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 MongoDB and SingleStore, 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.

Preguntas frecuentes

How should I choose between MongoDB and SingleStore?
Compare positioning, pricing, taxonomy, and traffic maturity, then verify the latest details on each official website.
Where does this comparison data come from?
The factual baseline is derived from product, taxonomy, traffic, and community data. Reviewed editorial conclusions show their source and verification date.
What do unknown fields mean?
Unknown means there is not enough reliable evidence; the page does not fill gaps with assumptions.