Database / ChromaDB Interview Questions
How do you efficiently add large numbers of documents to ChromaDB using batching?
Adding tens of thousands of documents one at a time is slow because each call triggers embedding computation and index updates. The right approach is to batch documents into groups of 100–500 and add each batch with a single add() call — this amortises embedding overhead and index writes.
import chromadb from chromadb.utils import embedding_functions from typing import List client = chromadb.PersistentClient(path="./bulk_db") ef = embedding_functions.SentenceTransformerEmbeddingFunction( model_name="all-MiniLM-L6-v2" ) collection = client.get_or_create_collection( "large_corpus", embedding_function=ef ) # Simulate a large list of documents documents = [f"Article about topic {i}" for i in range(10_000)] ids = [f"doc-{i}" for i in range(10_000)] metadatas = [{"index": i, "batch": i // 500} for i in range(10_000)] # Efficient batch insertion BATCH_SIZE = 500 for start in range(0, len(documents), BATCH_SIZE): end = start + BATCH_SIZE collection.add( documents=documents[start:end], ids=ids[start:end], metadatas=metadatas[start:end], ) print(f"Added batch {start // BATCH_SIZE + 1}, total: {collection.count()}") print(f"Final count: {collection.count()}") # 10000 # Alternative: provide pre-computed embeddings to skip re-embedding # (useful when you already called the embedding API) from sentence_transformers import SentenceTransformer model = SentenceTransformer("all-MiniLM-L6-v2") docs_batch = documents[:500] vectors = model.encode(docs_batch, batch_size=64, show_progress_bar=True) collection.add( embeddings=vectors.tolist(), documents=docs_batch, ids=ids[:500], )
| Tip | Reason |
|---|---|
| Batch size 100–500 | Balances memory use and embedding throughput |
| Pre-compute embeddings externally | Avoid re-embedding if you already have vectors from an API call |
| Use GPU for local models | SentenceTransformer encodes ~100x faster on GPU |
| Upsert instead of add in loops | upsert() is safe to re-run; add() fails on duplicate IDs |
What is the main performance benefit of batching documents into groups before calling collection.add()?
What is a good batch size for bulk insertion into ChromaDB?
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