Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Deeplake is an AI data runtime and GPU database built for teams developing agents, RAG systems, multimodal applications, robotics workflows, and generative media products. It is designed to solve the gap between GPU-powered AI models and CPU-bound data systems by keeping data closer to where AI workloads execute. The platform supports serverless Postgres, vector search, multimodal data storage, analytical workloads, and AI-optimized data lake functionality. Deeplake helps agents remember, retrieve, and act in fast cycles, making it useful for systems that need repeated context retrieval across long-running tasks. It can manage complex data such as video, images, point clouds, sensors, PDFs, audio, embeddings, model weights, and structured records. Developers can use familiar database concepts while gaining support for GPU-speed retrieval and scalable AI data operations. The platform is positioned for production-grade AI use cases where agents may generate databases, query thousands of times, and require faster memory access. Deeplake also supports private deployment patterns, including VPC environments, so organizations can keep sensitive data within their own infrastructure. With open-source adoption, enterprise security credentials, and a focus on agentic workloads, Deeplake helps AI teams build faster and more efficient data systems.
Description
Oracle AI Vector Search is an innovative feature integrated into Oracle Database, specifically tailored for AI applications, which enables the querying of data based on its semantic meaning rather than relying solely on conventional keyword searches. This functionality empowers organizations to conduct similarity searches across both structured and unstructured datasets, allowing for retrieval of results that prioritize contextual relevance over precise matches. Employing vector embeddings to represent various forms of data—including text, images, and documents—it utilizes advanced vector indexing and distance metrics to quickly locate similar items. Moreover, it introduces a unique VECTOR data type along with SQL operators and syntax that enable developers to merge semantic searches with relational queries within a single database framework. As a result, this integration streamlines the data management process by negating the necessity for separate vector databases, ultimately minimizing data fragmentation and fostering a cohesive environment for both AI and operational data. The enhanced capability not only simplifies the architecture but also enhances the overall efficiency of data retrieval and analysis in complex AI workloads.
API Access
Has API
API Access
Has API
Integrations
Amazon SageMaker
Amazon Web Services (AWS)
ChatGPT
Google Cloud Platform
JSON
Jupyter Notebook
LangChain
My DSO Manager
OpenAI
Oracle Database
Integrations
Amazon SageMaker
Amazon Web Services (AWS)
ChatGPT
Google Cloud Platform
JSON
Jupyter Notebook
LangChain
My DSO Manager
OpenAI
Oracle Database
Pricing Details
$0
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Activeloop
Founded
2018
Country
United States
Website
deeplake.ai/
Vendor Details
Company Name
Oracle
Country
United States
Website
www.oracle.com/database/ai-vector-search/