# How many Pinecone Pods needed for Large Number of documents?

**URL:** <https://community.pinecone.io/t/how-many-pinecone-pods-needed-for-large-number-of-documents/5656>\
**Category:** Support\
**Tags:** semantic-search, vector-database, embeddings\
**Created:** [May 21, 2024, 6:33am UTC](https://community.pinecone.io/t/how-many-pinecone-pods-needed-for-large-number-of-documents/5656 "2024-05-21T06:33:41Z")\
**Posts on this page:** 2\
**Page:** 1

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**Author:** ![zohaibramzan28](https://sea2.discourse-cdn.com/flex020/user_avatar/community.pinecone.io/zohaibramzan28/32/2663_2.png) [@zohaibramzan28](https://community.pinecone.io/u/zohaibramzan28)\
**Post date:** [May 21, 2024, 6:33am UTC](https://community.pinecone.io/t/how-many-pinecone-pods-needed-for-large-number-of-documents/5656/1 "2024-05-21T06:33:41Z")

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I have about 6000 documents that can be categorized into 6 categories. Some categories may have upto 1500 docs and some may have less number of documents. I will create multiple indexes(say 6) inside one namespace. I will also add meta data along with each record. We can consider One/Two Page pdf documents. The point I want to get cleared here is that how many pods will be used? Which POD type should I use for my RAG application? Which RAG technique can better serve my application

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**Author:** ![ZacharyProser](https://sea2.discourse-cdn.com/flex020/user_avatar/community.pinecone.io/zacharyproser/32/1146_2.png) [@ZacharyProser](https://community.pinecone.io/u/ZacharyProser)\
**Post date:** [May 21, 2024, 3:37pm UTC](https://community.pinecone.io/t/how-many-pinecone-pods-needed-for-large-number-of-documents/5656/2 "2024-05-21T15:37:55Z")

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Hi @zohaibramzan28, and welcome to the Pinecone forums!

Thanks for your question.

While you can certainly use pod-based indexes, and start small while learning more about your workloads, have you considered using [Pinecone serverless](https://www.pinecone.io/product/) instead?

Here’s [our quickstart guide](https://docs.pinecone.io/guides/get-started/quickstart) you can follow.

This way, you don’t need to worry about pre-configuring your workload size at all - you can simply upsert vectors and pay for what you use.

There’s also [a free tier](https://www.pinecone.io/pricing/) you could use to experiment and get started.

Here’s [a case-study about one of our customers who ingested 30 million documents into Pinecone](https://www.pinecone.io/customers/inpharmd/), which you may be interested in.

Hope that helps!

Best,  
Zack