ToolMage
Sign in
Activeloop
Data Management ยท 43.9K monthly visits

Activeloop provides Deep Lake, a specialized Database for AI, designed to manage, query, and stream large-scale multimodal datasets (text, images, audio, video) for building advanced AI applications. It simplifies complex data infrastructure, enabling developers to create powerful Retrieval-Augmented Generation (RAG) systems, semantic search engines, and intelligent AI agents with ease.

VS
Zilliz
Machine Learning ยท 174.3K monthly visits

Zilliz is an enterprise-grade vector database built for scalable AI applications. Powered by the popular open-source project Milvus, it provides a high-performance, cost-effective, and fully-managed service (Zilliz Cloud) for storing, indexing, and searching billions of vector embeddings. It's designed to power applications like RAG, recommendation systems, and multimodal search, with seamless integrations into major AI frameworks and cloud platforms.

Activeloop vs Zilliz: pricing, features, traffic, and use cases

Compare Activeloop and Zilliz across positioning, pricing, traffic, and user feedback using structured factual data.

Updated Aug 12, 2026

Product overview

Activeloop Product overview

Activeloop provides Deep Lake, a specialized Database for AI, designed to manage, query, and stream large-scale multimodal datasets (text, images, audio, video) for building advanced AI applications. It simplifies complex data infrastructure, enabling developers to create powerful Retrieval-Augmented Generation (RAG) systems, semantic search engines, and intelligent AI agents with ease.

Preview

Zilliz Product overview

Zilliz is an enterprise-grade vector database built for scalable AI applications. Powered by the popular open-source project Milvus, it provides a high-performance, cost-effective, and fully-managed service (Zilliz Cloud) for storing, indexing, and searching billions of vector embeddings. It's designed to power applications like RAG, recommendation systems, and multimodal search, with seamless integrations into major AI frameworks and cloud platforms.

Preview

Detailed feature comparison

FeatureActiveloopZilliz
Primary categoryData ManagementMachine Learning
Added2025-08-072025-09-11
PricingFreemiumFreemium
Official websitewww.activeloop.aizilliz.com
Product typeWebsiteWebsite
Performance data
User ratingNot verifiedNot verified
Comments00
Monthly visits43.9K174.3K
Monthly growth-28.9%-6.8%
Favorites148130
DetailsView detailsView details

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

Monthly visits
43.9K
Avg. visit duration
0:39
Pages per visit
2.05
Bounce rate
39.69%
Data updated 2026-06-15

Monthly traffic trend

  • 2025/9: 73.7K Monthly visits
  • 2026/1: 72K Monthly visits
  • 2026/2: 48.9K Monthly visits
  • 2026/3: 61.1K Monthly visits
  • 2026/4: 61.8K Monthly visits
  • 2026/5: 43.9K Monthly visits

Top regions

Top 5 countries/regions
Country/regionPercentageTraffic
๐Ÿ‡ฎ๐Ÿ‡ณIndia38.71%17K
๐Ÿ‡บ๐Ÿ‡ธUnited States35.49%15.6K
๐Ÿ‡ฉ๐Ÿ‡ชGermany9.3%4.1K
๐Ÿ‡ป๐Ÿ‡ณVietnam9.03%4K
๐Ÿ‡ท๐Ÿ‡บRussia7.47%3.3K

Traffic sources

Source typePercentageTraffic
Direct85.99%37.8K
Referral13.94%6.1K
Email0.07%31

Search keywords

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

Zilliz monthly traffic:

Latest traffic

Monthly visits
174.3K
Avg. visit duration
1:03
Pages per visit
2.3
Bounce rate
43.45%
Data updated 2026-06-15

Monthly traffic trend

  • 2025/9: 232.4K Monthly visits
  • 2026/1: 193.2K Monthly visits
  • 2026/2: 175.9K Monthly visits
  • 2026/3: 184.2K Monthly visits
  • 2026/4: 187.1K Monthly visits
  • 2026/5: 174.3K Monthly visits

Top regions

Top 5 countries/regions
Country/regionPercentageTraffic
๐Ÿ‡บ๐Ÿ‡ธUnited States40.94%71.4K
๐Ÿ‡ป๐Ÿ‡ณVietnam29.53%51.5K
๐Ÿ‡ฎ๐Ÿ‡ณIndia14.45%25.2K
๐Ÿ‡ฉ๐Ÿ‡ชGermany7.67%13.4K
๐Ÿ‡ฌ๐Ÿ‡งUnited Kingdom7.41%12.9K

Traffic sources

Source typePercentageTraffic
Direct71.91%125.3K
Referral26.14%45.6K
Email1.95%3.4K

Search keywords

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

Database
Search
Data Management

Zilliz Core features

Database
Search
Machine Learning

Use cases

Activeloop Use cases

RAG
retrieval augmented generation
semantic search
vector database
AI infrastructure
database for AI
data management
LangChain
LlamaIndex
multimodal data

Zilliz Use cases

RAG
retrieval augmented generation
semantic search
vector database
AI
enterprise AI
llm
machine learning
milvus
recommendation engine
similarity search
unstructured data

Best suited roles

Activeloop Best suited roles

No verified data available

Zilliz Best suited roles

AI Researcher
Data Scientist
DevOps Engineer
Machine Learning Engineer
Product Manager
Software Developer
Solutions Architect

Activeloop vs Zilliz๏ผšIn-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 โ€œData Managementโ€, while Zilliz is primarily listed under โ€œMachine Learningโ€, 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: Data Management; Zilliz: Machine Learning); Monthly visits (Activeloop: 43.9K; Zilliz: 174.3K); Monthly growth (Activeloop: -28.9%; Zilliz: -6.8%); Favorites (Activeloop: 148; Zilliz: 130); 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

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.

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: Database and Search; shared tags: RAG, retrieval augmented generation, semantic search, and vector database. This can place both on the same shortlist, but it does not prove equal implementation, depth, or cost.

Activeloop's unique categories/tags are Data Management, AI infrastructure, database for AI, data management, LangChain, LlamaIndex, and multimodal data; Zilliz's are Machine Learning, AI, enterprise AI, llm, machine learning, milvus, recommendation engine, and similarity search. 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, 148 favorites, and 118 likes๏ผ›Zilliz has no verified rating, 0 comments, 130 favorites, and 100 likesใ€‚

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 โ€œData Managementโ€ and especially Data Management, AI infrastructure, database for AI, data management, LangChain, and LlamaIndex. 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 โ€œMachine Learningโ€ and especially Machine Learning, AI, enterprise AI, llm, machine learning, and milvus, or the users include AI Researcher, Data Scientist, DevOps Engineer, and Machine Learning Engineer. 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.

Comparison 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.

Related AI tools

Vectorize
Freemium

Vectorize

Vectorize is a RAG-as-a-Service platform that simplifies building AI applications on unstructured data. It offers managed RAG pipelines, extensive data source connectors, and the flexibility to use its managed vector database or connect your own, enabling developers to deploy production-ready AI solutions quickly.

Rag
Visits 220.3KFavorites 105Likes 107
Weaviate
Freemium

Weaviate

Weaviate is an open-source, AI-native vector database designed for developers. It enables scalable, low-latency vector, keyword, and hybrid search. Ideal for building AI applications like semantic search, recommendation engines, and Retrieval-Augmented Generation (RAG) systems, it integrates seamlessly with popular machine learning models to store and query data based on semantic meaning.

Vector Database
Visits 141.5KFavorites 111Likes 118
Chroma
Freemium

Chroma

Chroma is the open-source, AI-native retrieval database designed for building powerful AI applications with Retrieval-Augmented Generation (RAG). It simplifies storing and searching embeddings, documents, and metadata, offering vector search, full-text search, and a scalable, serverless cloud platform. It's built to be easy to use, cost-effective, and powerful, from local development to large-scale production.

Vector Database
Visits 237.6KFavorites 134Likes 122
Vespa.ai
Freemium

Vespa.ai

Vespa.ai is a high-performance AI search platform for building large-scale applications. It unifies vector search, text search, and machine-learned ranking to power advanced use cases like Retrieval-Augmented Generation (RAG), recommendation engines, and intelligent search. Designed for real-time inference and scalability, it's trusted by leading companies like Spotify and Perplexity to handle massive datasets with low latency.

Search
Visits 43.6KFavorites 112Likes 96
PostgresML
Freemium

PostgresML

PostgresML is a powerful open-source extension that integrates machine learning and AI directly into your PostgreSQL database. It enables GPU-accelerated inference, vector search, and complete RAG pipelines using simple SQL commands, eliminating data movement and simplifying the MLOps stack for high-performance, scalable AI applications.

Mlops
Visits 3.7KFavorites 118Likes 110
Vectra

Vectra

Vectra is an open-source, production-grade SDK for Node.js and Python, designed to build, manage, and query advanced Retrieval-Augmented Generation (RAG) pipelines. It offers a comprehensive toolkit for developing context-aware AI applications, optimized for low latency, high precision, and scalability.

Rag Pipelines
Visits 3.7KFavorites 28Likes 28
Qdrant
Freemium

Qdrant

Qdrant is a high-performance, open-source vector database and similarity search engine built in Rust. It's designed to power next-generation AI applications by efficiently managing and searching billions of high-dimensional vectors. With advanced features like rich filtering, payload storage, and various quantization methods, Qdrant enables developers to build scalable and cost-effective solutions for semantic search, recommendation systems, and Retrieval Augmented Generation (RAG).

Vector Search
Visits 303.9KFavorites 134Likes 120
Milvus
Freemium

Milvus

Milvus is a high-performance, open-source vector database built for AI applications. It enables developers to manage and search through billions of high-dimensional vectors with minimal latency. Ideal for building scalable systems like retrieval-augmented generation (RAG), recommendation engines, and semantic search, Milvus offers flexible deployment options from local prototyping to large-scale distributed clusters.

Machine Learning
Visits 534.2KFavorites 105Likes 118
LanceDB
Freemium

LanceDB

LanceDB is an open-source, AI-native multimodal lakehouse designed for building and scaling AI applications. It provides a unified platform for storing, searching, and managing complex data like text, images, voice, and vectors. Ideal for RAG, semantic search, and model training, LanceDB offers blazing-fast hybrid search, massive scalability to petabytes, and significant cost savings, making it a powerful foundation for enterprise-grade AI.

Vector Database
Visits 74.1KFavorites 114Likes 109
XMOX
Paid

XMOX

XMOX is a leading managed AI agents platform that provides enterprise-grade infrastructure and services for deploying, scaling, and managing intelligent agents. It eliminates operational complexity, allowing businesses to harness the power of multi-modal AI agentsโ€”including language, code, and voiceโ€”with advanced RAG integration, zero-touch operations, and intelligent auto-scaling.

Platform As A Service
Visits 3.7KFavorites 104Likes 87
Bilberrydb
Freemium

Bilberrydb

Bilberrydb is an enterprise-grade, multimodal vector database designed for building advanced AI applications. It enables lightning-fast embedding search across diverse data types including 3D models, images, videos, audio, text, and tabular data on a unified platform.

Vector Database
Visits 4.2KFavorites 102Likes 107
AI News Hub

AI News Hub

AI News Hub is a comprehensive platform providing real-time AI announcements, curated blog updates on agentic AI, RAG, and production tools. It offers a personalized feed, bookmarking capabilities, and a rich collection of learning resources, including roadmaps, courses, and videos, to keep developers and enthusiasts informed and skilled in the rapidly evolving AI landscape.

Aggregation
Visits 3.8KFavorites 26Likes 26
Mixpeek
Freemium

Mixpeek

Mixpeek is a developer-first API and multimodal data warehouse for processing, searching, and analyzing unstructured data like video, audio, images, and documents. It simplifies the AI/ML pipeline with unified semantic search, automated classification, and seamless model management, allowing developers to build powerful multimodal applications.

Machine Learning
Visits 27.6KFavorites 89Likes 106
MyScale
Freemium

MyScale

MyScale is a high-performance vector database that uniquely combines vector search with the power of SQL. It's designed for building advanced AI applications like RAG, semantic search, and recommendation systems, simplifying the tech stack by allowing developers to run hybrid queries on vectors and structured data using a single, familiar interface.

Vector Database
Visits 43.4KFavorites 106Likes 103
Skald
Freemium

Skald

Skald is an open-source RAG API designed for developers to quickly build AI agents without the complexity of managing RAG infrastructure. It simplifies knowledge storage, context management, and semantic search, offering a powerful solution for integrating long-term memory into AI applications.

Rag
Visits 3.7KFavorites 95Likes 120