Weaviate Batch Import Errors and Failed Objects

How to fix it

Try these in order — the most common fix is first.

1. 1. Find the failures

   Copy steps
   1. Python: check collection.batch.failed_objects after the batch context closes
   2. Use batch.number_errors inside the loop and break past a threshold
   3. With data.ingest(), read the errors dict keyed by object index
   Did this fix it? Yes No

2. 2. Reduce rate-limit errors

   Copy steps
   1. Set requests_per_minute_embeddings or tokens_per_minute_embeddings via client.integrations.configure()
   2. Use server-side batching (v1.36+) or a fixed batch size such as 200
   Did this fix it? Yes No

3. 3. Make imports safe to retry

   Copy steps
   1. Use generate_uuid5 for deterministic IDs
   2. Stream large files instead of one insertMany call
   Did this fix it? Yes No

Symptoms

Import finishes but some objects are missing, or errors like 'Failed to send all objects in a batch' appear.

Why it happens

• Individual objects fail validation or vectorization
• Vectorizer provider rate limits (OpenAI, Cohere)
• Large single requests exceeding GRPC_MAX_MESSAGE_SIZE
• Duplicates from missing deterministic IDs

This guide also covers

• weaviate batch import error
• weaviate failed_objects
• weaviate import slow
• weaviate batch failed

The same problem in other apps

All not loading, error messages & connection guides →

• Qdrant "Wrong input: Vector dimension error: expected dim, got" (Qdrant)
• Pinecone 429 Too Many Requests Error (Pinecone)
• Milvus "collection not loaded" Error (Milvus)

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