> ## Documentation Index > Fetch the complete documentation index at: https://docs.pinecone.io/llms.txt > Use this file to discover all available pages before exploring further. # Context Data > Connect Pinecone and Context Data to ship vector search and RAG: embed, index, and query at scale with managed infrastructure. export const PrimarySecondaryCTA = ({primaryLabel, primaryHref, primaryTarget, secondaryLabel, secondaryHref, secondaryTarget}) =>
{primaryLabel && primaryHref &&
{primaryLabel}
} {secondaryLabel && secondaryHref &&
{secondaryLabel}
}
; Using [Context Data](https://contextdata.ai/), you can easily create end-to-end data flows by connecting to a myriad of data sources (PostgreSQL, MySQL, Amazon S3, Salesforce, etc.), seamlessly embedding and writing the results to Pinecone using Context Data's super simple no-code web interface. These flows can also be configured to be triggered and run on a user-defined schedule. Additionally, Context Data provides the ability to create transformations like aggregations, joins, and feature engineering using SQL common table expressions before writing to Pinecone. You also have the ability to "chat" with your Pinecone indexes directly from Context Data's privacy-focused Query Studio.