diff --git a/docs/tools/vdb_table/data/pinecone.json b/docs/tools/vdb_table/data/pinecone.json
index e2fcfa3eb..70b3ac1c5 100644
--- a/docs/tools/vdb_table/data/pinecone.json
+++ b/docs/tools/vdb_table/data/pinecone.json
@@ -47,8 +47,8 @@
     "comment": ""
   },
   "multi_vec": {
-    "support": "none",
-    "source_url": "",
+    "support": "full",
+    "source_url": "https://community.pinecone.io/t/multiple-vector-representations-in-pinecone/362",
     "comment": ""
   },
   "sparse_vectors": {
@@ -57,23 +57,23 @@
     "comment": "Supports all sparse vectors, including BM25 and native support for SPLADE vectors"
   },
   "bm25": {
-    "support": "none",
-    "source_url": "",
+    "support": "full",
+    "source_url": "https://github.com/pinecone-io/pinecone-text",
     "comment": ""
   },
   "full_text": {
-    "support": "none",
-    "source_url": "",
+    "support": "full",
+    "source_url": "https://docs.pinecone.io/guides/search/lexical-search",
     "comment": ""
   },
   "embeddings_text": {
-    "support": "partial",
-    "source_url": "https://github.com/pinecone-io/canopy",
+    "support": "full",
+    "source_url": "https://docs.pinecone.io/models/overview",
     "comment": ""
   },
   "embeddings_image": {
-    "support": "none",
-    "source_url": "",
+    "support": "full",
+    "source_url": "https://docs.pinecone.io/models/overview",
     "comment": ""
   },
   "embeddings_structured": {
@@ -82,8 +82,8 @@
     "comment": ""
   },
   "rag": {
-    "support": "",
-    "source_url": "",
+    "support": "full",
+    "source_url": "https://www.pinecone.io/learn/retrieval-augmented-generation/",
     "comment": ""
   },
   "recsys": {
@@ -112,7 +112,7 @@
     "comment": "Includes free tier"
   },
   "in_process": {
-    "support": "none",
+    "support": "",
     "source_url": "",
     "comment": ""
   },
@@ -122,9 +122,9 @@
     "comment": "via namespaces"
   },
   "disk_index": {
-    "support": "",
-    "source_url": "",
-    "comment": ""
+    "support": "full",
+    "source_url": "https://www.pinecone.io/blog/evolving-pinecone-for-knowledgeable-ai/",
+    "comment": "Intelligent storage tiering between RAM, disk, and object storage"
   },
   "ephemeral": {
     "support": "none",
@@ -139,21 +139,22 @@
   "doc_size": {
     "bytes": 40000,
     "unlimited": false,
-    "source_url": "https://docs.pinecone.io/docs/limits",
-    "comment": ""
+    "source_url": "https://docs.pinecone.io/reference/api/database-limits#upsert-limits",
+    "comment": "This is the maximum metadata size per record; there is no limit on the size of documents from which you can create vectors."
   },
   "vector_dims": {
     "value": 20000,
     "unlimited": false,
-    "source_url": "https://docs.pinecone.io/docs/limits",
+    "source_url": "https://docs.pinecone.io/reference/api/database-limits#upsert-limits",
     "comment": ""
   },
   "index_types": {
     "value": [
-      "FreshDiskANN"
+      "Proprietary",
+      "IVF-PQ"
     ],
-    "source_url": "https://www.pinecone.io/blog/hnsw-not-enough/#:~:text=its%20similarities%20end.-,FreshDiskANN,-PGA%20is%20based",
-    "comment": "Proprietary variant of Microsoft's Vamana"
+    "source_url": "https://www.pinecone.io/blog/optimizing-pinecone/",
+    "comment": "Dynamic algorithm (IVFPQ + Proprietary) selection based on workload and data size"
   },
   "github_stars": {
     "value": 0,
@@ -168,8 +169,8 @@
     "value_90_days": 0
   },
   "pypi_downloads": {
-    "value": 51909059,
-    "source_url": "https://pypi.org/project/pinecone-client/",
+    "value": 47744166,
+    "source_url": "https://pypi.org/project/pinecone/",
     "comment": "",
     "value_90_days": 11477920
   },