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What is Weaviate?

Weaviate is an open-source, AI-native database that helps organizations build and ship AI applications on a single, scalable foundation. It stores data objects alongside the vector embeddings produced by your chosen machine learning models and scales smoothly to billions of records. Teams can supply their own vectors or use Weaviate's built-in vectorization, then query their data through vector, keyword, and hybrid search to surface the most relevant results, even with complex filters. By integrating with leading large language models, Weaviate makes it straightforward to build retrieval-augmented generation, grounded question answering, and intelligent search over proprietary data. Beyond core retrieval, Weaviate offers a growing platform: the Query Agent converts natural-language questions into precise, cited queries; Engram provides managed memory that lets AI agents retain context over time; and Weaviate Embeddings handles vectorization as a managed service. Organizations can self-host under an open-source license or adopt fully managed Weaviate Cloud on AWS, GCP, or Azure, with SOC 2 Type II compliance, multi-tenancy, replication, and role-based access control. From semantic search and recommendations to agentic automation, Weaviate turns business data into AI-powered products.

What is LlamaIndex?

LlamaIndex functions as a dynamic "data framework" aimed at facilitating the creation of applications that utilize large language models (LLMs). This platform allows for the seamless integration of semi-structured data from a variety of APIs such as Slack, Salesforce, and Notion. Its user-friendly yet flexible design empowers developers to connect personalized data sources to LLMs, thereby augmenting application functionality with vital data resources. By bridging the gap between diverse data formats—including APIs, PDFs, documents, and SQL databases—you can leverage these resources effectively within your LLM applications. Moreover, it allows for the storage and indexing of data for multiple applications, ensuring smooth integration with downstream vector storage and database solutions. LlamaIndex features a query interface that permits users to submit any data-related prompts, generating responses enriched with valuable insights. Additionally, it supports the connection of unstructured data sources like documents, raw text files, PDFs, videos, and images, and simplifies the inclusion of structured data from sources such as Excel or SQL. The framework further enhances data organization through indices and graphs, making it more user-friendly for LLM interactions. As a result, LlamaIndex significantly improves the user experience and broadens the range of possible applications, transforming how developers interact with data in the context of LLMs. This innovative framework fundamentally changes the landscape of data management for AI-driven applications.

Media

Media

Integrations Supported

Databricks
DeepEval
Mem0
Model Context Protocol (MCP)
OpenAI
Comet
GitHub
Hugging Face
n8n

Integrations Supported

Databricks
DeepEval
Mem0
Model Context Protocol (MCP)
OpenAI
AgentOps
BlackBit VOID
Cognee
Discord
HoneyHive
Muse Wonder Full
Opik
SQL
Thordata

API Availability

Has API

API Availability

Has API

Pricing Information

Free
Open source (free); free Weaviate Cloud tier; paid Cloud plans from $45/mo.
Free Version

Pricing Information

Pricing not provided

Supported Platforms

SaaS
Windows
Mac
On-Prem
Linux

Supported Platforms

SaaS

Customer Service / Support

24 Hour Support
Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub
Webinars

Training Options

Documentation Hub

Company Facts

Organization Name

Weaviate

Date Founded

2019

Company Location

The Netherlands

Company Website

weaviate.io

Company Facts

Organization Name

LlamaIndex

Company Location

United States

Company Website

www.llamaindex.ai/

Categories and Features

AI Memory Layers

Not specified

Context Engineering

Not specified

Vector Databases

Not specified

Categories and Features

Agentic AI

Not specified

AI Agent Builders

Not specified

AI Agent Frameworks

Not specified

AI Agents

Not specified

AI Development

Not specified

AI Memory Layers

Not specified

AI SDKs

Not specified

Context Engineering

Not specified

Query Engines

Not specified

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