Spice.ai Enterprise (BYOL)

Spice 1.6.0 upgrades DataFusion to v48, reducing expressions memory footprint by ~50% for faster planning and lower memory usage, eliminating unnecessary projections in queries, optimizing string functions like ascii and character_length for up to 3x speedup, and accelerating unbounded aggregate window functions by 5.6x. The release adds Kafka and MongoDB connectors for real-time streaming and NoSQL data acceleration, supports OpenAI Responses API for advanced model interactions including OpenAI-hosted tools like web_search and code_interpreter, improves the OpenAI Embeddings Connector with usage tier configuration for higher throughput via increased concurrent requests, introduces Model2Vec embeddings for ultra-low-latency encoding, and improves the Amazon S3 Vectors engine to support multi-column primary keys.

Spice.ai is built on the DataFusion query engine. The v48 release brings:

Performance & Size Improvements: Expressions memory footprint was reduced by ~50% resulting in faster planning and lower memory usage, with planning times improved by 10-20%. There are now fewer unnecessary projections in queries. The string functions, ascii and character_length were optimized for improved performance, with character_length achieving up to 3x speedup. Queries with unbounded aggregate window functions have improved performance by 5.6 times via avoided unnecessary computation for constant results across partitions. The Expr struct size was reduced from 272 to 144 bytes.

New Features & Enhancements: Support was added for ORDER BY ALL for easy ordering of all columns in a query.

See the Apache DataFusion 48.0.0 Blog  for details.

Amazon S3 Vectors Multi-Column Primary Keys: The Amazon S3 Vectors  engine now supports datasets with multi-column primary keys. This enables vector indexes for datasets where more than one column forms the primary key, such as those splitting documents into chunks for retrieval contexts. For multi-column keys, Spice serializes the keys using arrow-json format, storing them as single string keys in the vector index.

Model2Vec Embeddings: Spice now supports model2vec static embeddings  with a new model2vec embeddings provider, for sentence transformers up to 500x faster and 15x smaller, enabling scenarios requiring low latency and high-throughput encoding.

embeddings: - from: model2vec:minishlab/potion-base-8M # HuggingFace model name: potion - from: model2vec:path/to/my/local/model # local model name: local

Learn more in the Model2Dev Embeddings documentation .

Kafka Data Connector: Use from: kafka:<topic> to ingest data directly from Kafka topics for integration with existing Kafka-based event streaming infrastructure, providing real-time data acceleration and query without additional middleware.

Example Spicepod.yml:

- from: kafka:orders_events name: orders acceleration: enabled: true refresh_mode: append params: kafka_bootstrap_servers: server:9092

Learn more in the Kafka Data Connector documentation .

MongoDB Data Connector: Use from: mongodb:<dataset> to access and accelerate data stored in MongoDB, deployed on-premises or in the cloud.

Example spicepod.yml:

datasets: - from: mongodb:my_dataset name: my_dataset params: mongodb_host: localhost mongodb_db: my_database mongodb_user: my_user mongodb_pass: password

Learn more in the MongoDB Data Connector documentation .

OpenAI Responses API Support: The OpenAI Responses API (/v1/responses) is now supported, which is OpenAI's most advanced interface for generating model responses.

You can now make requests to any responses compatible model using the new /v1/responses endpoint.

Example curl request:

curl <http://localhost:8090/v1/responses> \ -H "Content-Type: application/json" \ -d '{ "model": "gpt-4.1", "input": "Tell me a three sentence bedtime story about Spice AI." }'

To use responses in spice chat, use the --responses flag.

Example:

spice chat --responses # Use the `/v1/responses` endpoint for all completions instead of `/v1/chat/completions`

Use OpenAI-hosted tools  supported by Open AI's Responses API by specifying the openai_responses_tools parameter:

Example spicepod.yml:

models: - name: test from: openai:gpt-4.1 params: openai_api_key: ${ secrets:SPICE_OPENAI_API_KEY } tools: sql, list_datasets openai_responses_tools: web_search, code_interpreter # 'code_interpreter' or 'web_search'

These OpenAI-specific tools are only available from the /v1/responses endpoint. Any other tools specified via the tools parameter are available from both the /v1/chat/completions and /v1/responses endpoints.

Learn more in the OpenAI Model Provider documentation .

OpenAI Embeddings & Models Connectors Usage Tier: The OpenAI Embeddings and Models Connectors now supports specifying account usage tier for embeddings and model requests, improving the performance of generating text embeddings or calling models during dataset load and search by increasing concurrent requests.

Example spicepod.yml:

embeddings: - from: openai:text-embedding-3-small name: openai_embed params: openai_usage_tier: tier1

By setting the usage tier to the matching usage tier for your OpenAI account, the Embeddings and Models Connector will increase the maximum number of concurrent requests to match the specified tier.

Learn more in the OpenAI Model Provider documentation .

• @Jeadie 
• @peasee 
• @sgrebnov 
• @Sevenannn 
• @kczimm 
• @phillipleblanc 
• @Advayp 
• @lukekim 
• @ewgenius 
• @mach-kernel 
• @krinart 

• @krinart made their first contribution in github.com/spiceai/spiceai/pull/6573 

No breaking changes.

• Added OpenAI Responses API  - Use OpenAI's Responses API with Spice
• Added Live Orders Analytics with Apache Kafka Data Connector  - Combine real-time data streaming from Kafka with other datasets
• Added MongoDB Data Connector  - Use MongoDB as a data source with Spice

The Spice Cookbook  includes 77 recipes to help you get started with Spice quickly and easily.

To upgrade to v1.6.0, use one of the following methods:

CLI:

spice upgrade

Homebrew:

brew upgrade spiceai/spiceai/spice

Docker:

Pull the spiceai/spiceai:1.6.0 image:

docker pull spiceai/spiceai:1.6.0

For available tags, see DockerHub .

Helm:

helm repo update helm upgrade spiceai spiceai/spiceai

• DataFusion: Upgraded to v48 
• Rust: Upgraded from 1.86.0 to 1.87.0