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Description
Astra DB from DataStax is a real-time vector database as a service for developers that need to get accurate Generative AI applications into production, fast.
Astra DB gives you a set of elegant APIs supporting multiple languages and standards, powerful data pipelines and complete ecosystem integrations. Astra DB enables you to quickly build Gen AI applications on your real-time data for more accurate AI that you can deploy in production.
Built on Apache Cassandra, Astra DB is the only vector database that can make vector updates immediately available to applications and scale to the largest real-time data and streaming workloads, securely on any cloud.
Astra DB offers unprecedented serverless, pay as you go pricing and the flexibility of multi-cloud and open-source. You can store up to 80GB and/or perform 20 million operations per month. Securely connect to VPC peering and private links. Manage your encryption keys with your own key management. SAML SSO secure account accessibility. You can deploy on Amazon, Google Cloud, or Microsoft Azure while still compatible with open-source Apache Cassandra.
Description
While generative AI is a relatively recent development, our efforts over the last five years have paved the way for this moment. Deep Lake merges the strengths of data lakes and vector databases to craft and enhance enterprise-level solutions powered by large language models, allowing for continual refinement. However, vector search alone does not address retrieval challenges; a serverless query system is necessary for handling multi-modal data that includes embeddings and metadata. You can perform filtering, searching, and much more from either the cloud or your local machine. This platform enables you to visualize and comprehend your data alongside its embeddings, while also allowing you to monitor and compare different versions over time to enhance both your dataset and model. Successful enterprises are not solely reliant on OpenAI APIs, as it is essential to fine-tune your large language models using your own data. Streamlining data efficiently from remote storage to GPUs during model training is crucial. Additionally, Deep Lake datasets can be visualized directly in your web browser or within a Jupyter Notebook interface. You can quickly access various versions of your data, create new datasets through on-the-fly queries, and seamlessly stream them into frameworks like PyTorch or TensorFlow, thus enriching your data processing capabilities. This ensures that users have the flexibility and tools needed to optimize their AI-driven projects effectively.
API Access
Has API
API Access
Has API
Integrations
Amazon Web Services (AWS)
Google Cloud Platform
Amazon SageMaker
Apache Cassandra
ChatGPT
DataStax
Jupyter Notebook
LangChain
LangGraph
Microsoft Azure
Integrations
Amazon Web Services (AWS)
Google Cloud Platform
Amazon SageMaker
Apache Cassandra
ChatGPT
DataStax
Jupyter Notebook
LangChain
LangGraph
Microsoft Azure
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
$995 per month
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
DataStax
Country
United States
Website
www.datastax.com/products/datastax-astra
Vendor Details
Company Name
activeloop
Country
United States
Website
www.activeloop.ai/