Troubleshooting and FAQs

This section describes common issues and how to solve them.

Contacting Support

Contact us over email:

I cannot install pip

Version 3 of Python uses pip3. Use the following commands at the command line (the terminal):

pip3 install -U pinecone-client

How secure is Pinecone?

We work hard to earn and maintain that trust by treating security and reliability as a cornerstone of our company and product.

See the Trust & Security page for more information.

Minimizing latency

Pinecone Beta is deployed in the AWS us-west-2 US West (Oregon) region.

To minimize latency when you access Pinecone, consider deploying your application in the same US West (Oregon) region.

Contact us if you need a dedicated deployment in other regions. We currently support AWS and GCP.

How fast is Pinecone?

Pinecone supports very high throughput (10K+ vectors per second).

If you have slow uploads or high latencies

If you experience slow uploads or high query latencies, it may be because you are accessing Pinecone from your home network.

To improve the performance, switch to a cloud environment. For example: EC2, GCE, Google Colab, GCP AI Platform Notebook, or SageMaker Notebook.

How to increase throughput

To increase throughput (QPS), increase the number of replicas for your index. See performance tuning for more information.

curl -i -X PATCH \ \
  -H 'Content-Type: application/json' \
  -H 'Api-Key: YOUR_API_KEY_HERE' \
  -d '{
    "replicas": 2

How to upload >1GB of data

When you have more than 1GB of data, we recommend you use more than 1 shard.

As a general guideline, add 1 shard to your index for every additional GB of data.

See the Manage Indexes documentation for information on how to specify the number of shards for your index.

curl -i -X POST \ \
  -H 'Content-Type: application/json' \
  -H 'Api-Key: YOUR_API_KEY_HERE' \
  -d '{
    "name": "example-index-name",
    "dimension": 128,
    "index_type": "approximated",
    "metric": "cosine",
    "replicas": 1,
    "shards": 1,
    "index_config": {
      "k_bits": 512,
      "hybrid": False