Datenmanagement · 43.9K monatliche besuche

Activeloop bietet Deep Lake, eine spezialisierte Datenbank für KI, die für die Verwaltung, Abfrage und das Streaming großer multimodaler Datensätze (Text, Bilder, Audio, Video) zum Erstellen fortschrittlicher KI-Anwendungen konzipiert ist. Es vereinfacht komplexe Dateninfrastrukturen und ermöglicht es Entwicklern, leistungsstarke Retrieval-Augmented Generation (RAG)-Systeme, semantische Suchmaschinen und intelligente KI-Agenten mühelos zu erstellen.

Website besuchen Details ansehen

Zilliz

Maschinelles Lernen · 174.3K monatliche besuche

Zilliz ist eine Vektordatenbank für Unternehmen, die für skalierbare KI-Anwendungen entwickelt wurde. Angetrieben durch das beliebte Open-Source-Projekt Milvus, bietet es einen hochleistungsfähigen, kostengünstigen und vollständig verwalteten Dienst (Zilliz Cloud) zum Speichern, Indizieren und Durchsuchen von Milliarden von Vektor-Embeddings. Es ist darauf ausgelegt, Anwendungen wie RAG, Empfehlungssysteme und multimodale Suche zu unterstützen, mit nahtlosen Integrationen in wichtige KI-Frameworks und Cloud-Plattformen.

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Activeloop vs Zilliz: Preise, Funktionen und Traffic

Vergleiche Activeloop und Zilliz nach Positionierung, Preis, Funktionen, Traffic und Nutzerfeedback.

Aktualisiert 05.08.2026

Produktübersicht

Activeloop Produktübersicht

Preview

Zilliz Produktübersicht

Preview

Detailed feature comparison

Feature	Activeloop	Zilliz
Hauptkategorie	Datenmanagement	Maschinelles Lernen
Hinzugefügt	2025-08-07	2025-09-11
Preismodell	Freemium	Freemium
Offizielle Website	www.activeloop.ai	zilliz.com
Produkttyp	Website	Website
Performance data
Nutzerbewertung	Nicht verifiziert	Nicht verifiziert
Kommentare	0	0
Monatliche Besuche	43.9K	174.3K
Monatliches Wachstum	-28.9%	-6.8%
Favoriten	146	127
Details	Details ansehen	Details ansehen

Activeloop vs Zilliz monthly traffic

Compare Activeloop and Zilliz by monthly reach, traffic trend, visit depth, top regions, and acquisition sources.

How to interpret the traffic data

In the Activeloop vs Zilliz monthly traffic comparison, Activeloop currently shows 43.9K visits and Zilliz shows 174.3K; Zilliz has about 4 times the visible traffic of Activeloop, an absolute difference of about 130.3K 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.

Activeloop monthly traffic:

Latest traffic

Monatliche Besuche

43.9K

Ø Besuchsdauer

0:39

Seiten pro Besuch

2.05

Absprungrate

39.69%

Data updated 2026-06-15

Monthly traffic trend

Top-Regionen

Top 5 countries/regions

Country/region	Percentage	Traffic
🇮🇳India	38.71%	17K
🇺🇸United States	35.49%	15.6K
🇩🇪Germany	9.3%	4.1K
🇻🇳Vietnam	9.03%	4K
🇷🇺Russia	7.47%	3.3K

Traffic-Quellen

Source type	Percentage	Traffic
Direkt	85.99%	37.8K
Verweis	13.94%	6.1K
E-Mail	0.07%	31

Suchbegriffe

activeloopcourse for fine tunningfine tunning course active looppotential fieldweight normalization neural networks

Zilliz monthly traffic:

Latest traffic

Monatliche Besuche

174.3K

Ø Besuchsdauer

1:03

Seiten pro Besuch

2.3

Absprungrate

43.45%

Data updated 2026-06-15

Monthly traffic trend

Top-Regionen

Top 5 countries/regions

Country/region	Percentage	Traffic
🇺🇸United States	40.94%	71.4K
🇻🇳Vietnam	29.53%	51.5K
🇮🇳India	14.45%	25.2K
🇩🇪Germany	7.67%	13.4K
🇬🇧United Kingdom	7.41%	12.9K

Traffic-Quellen

Source type	Percentage	Traffic
Direkt	71.91%	125.3K
Verweis	26.14%	45.6K
E-Mail	1.95%	3.4K

Suchbegriffe

aicloud aideepseekgoogle bardzilliz

Traffic-based selection guidance: If public market visibility is an important first-pass criterion, investigate Zilliz 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 Activeloop and Zilliz

Activeloop Core features

Datenbank

Suchen

Datenmanagement

Zilliz Core features

Datenbank

Suchen

Maschinelles Lernen

Use cases

Activeloop Use cases

Retrieval-Augmentierte Generierung

Semantische Suche

Vektordatenbank

KI-Infrastruktur

KI-Datenbank

Datenmanagement

LangChain

LlamaIndex

Multimodale Daten

Zilliz Use cases

Retrieval-Augmentierte Generierung

Semantische Suche

Vektordatenbank

Unternehmens-KI

Großes Sprachmodell

maschinelles Lernen

Milvus

Empfehlungs-Engine

Ähnlichkeitssuche

unstrukturierte Daten

Best suited roles

Activeloop Best suited roles

Keine verifizierten Daten

Zilliz Best suited roles

KI-Forscher

Datenwissenschaftler

DevOps-Ingenieur

Machine Learning Ingenieur

Produktmanager

Softwareentwickler

Lösungsarchitekt

Activeloop vs Zilliz：In-depth comparison and selection guidance

First decide whether the products solve the same kind of need

This in-depth Activeloop vs Zilliz comparison uses only the product records, taxonomy, audience, traffic, and community signals available on this page. Activeloop is primarily listed under “Datenmanagement”, while Zilliz is primarily listed under “Maschinelles Lernen”, so the first decision is whether your actual task matches their recorded scope.

The structured fields currently show these decision-relevant differences: Primary category (Activeloop: Datenmanagement; Zilliz: Maschinelles Lernen); Monthly visits (Activeloop: 43.9K; Zilliz: 174.3K); Monthly growth (Activeloop: -28.9%; Zilliz: -6.8%); Favorites (Activeloop: 146; Zilliz: 127); Website (Activeloop: www.activeloop.ai; Zilliz: zilliz.com). These facts are more useful for selection than brand visibility alone.

What market visibility and monthly traffic mean

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 Zilliz 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

Activeloop and Zilliz currently overlap in shared categories: Datenbank und Suchen; shared tags: Retrieval-Augmentierte Generierung, Semantische Suche und Vektordatenbank. This can place both on the same shortlist, but it does not prove equal implementation, depth, or cost.

Activeloop's unique categories/tags are Datenmanagement, KI-Infrastruktur, KI-Datenbank, LangChain, LlamaIndex und Multimodale Daten; Zilliz's are Maschinelles Lernen, KI, Unternehmens-KI, Großes Sprachmodell, maschinelles Lernen, Milvus, Empfehlungs-Engine und Ähnlichkeitssuche. 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

Activeloop has no verified rating, 0 comments, 146 favorites, and 114 likes；Zilliz has no verified rating, 0 comments, 127 favorites, and 100 likes。

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

Selection guidance by actual need

When to evaluate Activeloop first

Put Activeloop on the priority trial list when the task aligns with “Datenmanagement” and especially Datenmanagement, KI-Infrastruktur, KI-Datenbank, LangChain, LlamaIndex und Multimodale Daten. This follows recorded positioning and does not imply unlisted capabilities are absent.

Activeloop also currently records: pricing is freemium, product type is website, 43.9K 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 Zilliz first

Put Zilliz on the priority trial list when the task aligns with “Maschinelles Lernen” and especially Maschinelles Lernen, KI, Unternehmens-KI, Großes Sprachmodell, maschinelles Lernen und Milvus, or the users include KI-Forscher, Datenwissenschaftler, DevOps-Ingenieur und Machine Learning Ingenieur. This follows recorded positioning and does not imply unlisted capabilities are absent.

Zilliz also currently records: pricing is freemium, product type is website, 174.3K 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 Activeloop and Zilliz, 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.

Vergleichs-FAQ

How should I choose between Activeloop and Zilliz?

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.