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    Spice.ai Enterprise (BYOL)

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    Sold by: Spice AI 
    Deployed on AWS
    Spice.ai Enterprise is a portable (<150MB) compute engine built in Rust for data-intensive and intelligent applications. Deployable as a container on AWS ECS, EKS, or hybrid cloud+edge, it includes Enterprise licensing, support, and SLA.

    Overview

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    Spice.ai Enterprise is a portable (<150MB) compute engine built in Rust for data-intensive and intelligent applications. It accelerates SQL queries across databases, data warehouses, and data lakes using Apache Arrow, DataFusion, DuckDB, or SQLite. Integrated and co-deployed with data-intensive applications, Spice materializes and accelerates data from object storage, ensuring sub-second query performance and resilient AI applications. Deployable as a container on AWS ECS, EKS, or hybrid cloud & edge, it includes enterprise licensing, support, and SLAs.

    Note: Spice.ai Enterprise requires an existing commercial license. For details, please contact sales@spice.ai .

    Highlights

    • Unified data query and AI engine accelerating SQL queries across databases, data warehouses, and data lakes. Delivers sub-second query performance while grounding mission-critical AI applications with real-time context to minimize errors and hallucinations.
    • Advanced AI and retrieval tools, featuring vector and hybrid search, text-to-SQL, and LLM memory, enabling data-grounded AI applications with more than 25 data connectors enabling federated queries and real-time applications.
    • Deployable as a container on AWS ECS, EKS, or on-premises, with dedicated support and SLAs for scalable, secure integration into any architecture.

    Details

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    Delivery method

    Supported services

    Delivery option
    Container Deployment
    Helm Deployment

    Latest version

    Operating system
    Linux

    Deployed on AWS
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    Pricing

    Spice.ai Enterprise (BYOL)

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    Pricing and entitlements for this product are managed through an external billing relationship between you and the vendor. You activate the product by supplying a license purchased outside of AWS Marketplace, while AWS provides the infrastructure required to launch the product. AWS Subscriptions have no end date and may be canceled any time. However, the cancellation won't affect the status of the external license.
    Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator  to estimate your infrastructure costs.

    Vendor refund policy

    Refunds for Spice.ai Enterprise container subscriptions are not available after activation, as usage begins immediately upon deployment. Ensure compatibility with AWS ECS, EKS, or on-premises setups before purchase. For billing inquiries, contact AWS Marketplace support or Spice AI directly at support@spice.ai  .

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    Legal

    Vendor terms and conditions

    Upon subscribing to this product, you must acknowledge and agree to the terms and conditions outlined in the vendor's End User License Agreement (EULA) .

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    Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.

    Usage information

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    Delivery details

    Container Deployment

    Supported services: Learn more 
    • Amazon ECS
    • Amazon EKS
    • Amazon ECS Anywhere
    • Amazon EKS Anywhere
    Container image

    Containers are lightweight, portable execution environments that wrap server application software in a filesystem that includes everything it needs to run. Container applications run on supported container runtimes and orchestration services, such as Amazon Elastic Container Service (Amazon ECS) or Amazon Elastic Kubernetes Service (Amazon EKS). Both eliminate the need for you to install and operate your own container orchestration software by managing and scheduling containers on a scalable cluster of virtual machines.

    Version release notes

    Spice v1.11.5-enterprise (Apr 1, 2026)

    Spice v1.11.5-enterprise is a patch release improving on_zero_results: use_source fallback performance, Delta Lake timestamp predicate data skipping, S3 Parquet read performance, PostgreSQL partitioned table support, Cayenne target file size handling, and preparing the CLI for v2.0 runtime upgrades.

    What's New in v1.11.5-enterprise

    on_zero_results: use_source Fallback Performance Improvement

    Improved the on_zero_results: use_source  fallback path to run DataFusion's physical optimizer on the federated scan plan (#9927 ). The fallback path now runs SessionState::physical_optimizers() rules on the federated scan plan before execution, enabling parallel file group scanning and other optimizations. This results in significantly faster fallback queries on multi-core machines, particularly for file-based data sources like Delta Lake.

    Delta Lake: Improved Data Skipping for >= Timestamp Predicates

    Delta Lake  table scans with >= timestamp filters now correctly prune files that do not match the predicate (#9932 ), improving query performance through more effective data skipping (file-level pruning).

    PostgreSQL: Partitioned Tables Support

    The PostgreSQL  data connector now supports partitioned tables  (#9997 ) for both federated and accelerated queries.

    S3 Parquet Read Performance Improvement

    Improved parquet read performance from S3  and other object stores (#10064 ), particularly for tables with many columns. Column data ranges are now coalesced into fewer, larger requests instead of being fetched individually, reducing the number of HTTP round-trips.

    Cayenne: Ensure Target File Size is Respected

    The Cayenne  accelerator now correctly respects the configured target file size (#10071 ). Previously, Cayenne could produce many small, fragmented Vortex files; with this fix, files are written at the expected target size, improving storage efficiency and query performance.

    CLI: Support for v2.0 Runtime Upgrades

    The Spice CLI can now upgrade to v2.0 runtime versions. This enables upgrading to v2.0 release candidates and, once released, the v2.0 stable runtime.

    spice upgrade v2.0.0-rc.1

    Running spice upgrade without a version will upgrade to the latest stable version, including v2.0 once released.

    Note: Native Windows runtime builds will no longer be provided in v2.0. Use WSL  for local development instead.

    Contributors

    Breaking Changes

    No breaking changes.

    Cookbook Updates

    No new cookbook recipes.

    The Spice Cookbook  includes 86 recipes to help you get started with Spice quickly and easily.

    Upgrading

    To upgrade to v1.11.5-enterprise, use one of the following methods:

    CLI:

    spice upgrade

    Homebrew:

    brew upgrade spiceai/spiceai/spice

    Docker:

    Pull the spiceai/spiceai:1.11.5 image:

    docker pull spiceai/spiceai:1.11.5

    For available tags, see DockerHub .

    Helm:

    helm repo update helm upgrade spiceai spiceai/spiceai --version 1.11.5

    Additional details

    Usage instructions

    Prerequisites

    Ensure the following tools and resources are ready before starting:

    • Docker: Install from https://docs.docker.com/get-docker/ .
    • AWS CLI: Install from https://docs.aws.amazon.com/cli/latest/userguide/getting-started-install.html .
    • AWS ECR Access: Authenticate to the AWS Marketplace registry: aws ecr get-login-password --region us-east-1 | docker login --username AWS --password-stdin 709825985650.dkr.ecr.us-east-1.amazonaws.com
    • Spicepod Configuration: Prepare a spicepod.yaml file in your working directory. A spicepod is a YAML manifest file that configures which components (i.e. datasets) are loaded. Refer to https://spiceai.org/docs/getting-started/spicepods  for details.
    • AWS ECS Prerequisites (for ECS deployment): An ECS cluster (Fargate or EC2) configured in your AWS account. An IAM role for ECS task execution (e.g., ecsTaskExecutionRole) with permissions for ECR, CloudWatch, and other required services. A VPC with subnets and a security group allowing inbound traffic on ports 8090 (HTTP) and 50051 (Flight).

    Running the Container

    1. Ensure the spicepod.yaml is in the current directory (e.g., ./spicepod.yaml).
    2. Launch the container, mounting the current directory to /app and exposing HTTP and Flight endpoints externally:

    docker run --name spiceai-enterprise
    -v $(pwd):/app
    -p 50051:50051
    -p 8090:8090
    709825985650.dkr.ecr.us-east-1.amazonaws.com/spice-ai/spiceai-enterprise-byol:1.11.1-enterprise-models
    --http 0.0.0.0:8090
    --flight 0.0.0.0:50051

    • The -v $(pwd):/app mounts the current directory to /app, where spicepod.yaml is expected.
    • The --http and --flight flags set endpoints to listen on 0.0.0.0, allowing external access (default is 127.0.0.1).
    • Ports 8090 (HTTP) and 50051 (Flight) are mapped for external access.

    Verify and Monitor the Container

    1. Confirm the container is running:

    docker ps

    Look for spiceai-enterprise with a STATUS of Up.

    1. Inspect logs for troubleshooting:

    docker logs spiceai-enterprise

    Deploying to AWS ECS Create an ECS Task Definition and use this value for the image: 709825985650.dkr.ecr.us-east-1.amazonaws.com/spice-ai/spiceai-enterprise-byol:1.11.1-enterprise-models. Configure the port mappings for the HTTP and Flight ports (i.e. 8090 and 50051).

    Override the command to expose the HTTP and Flight ports publically and link to the Spicepod configuration hosted on S3:

    "command": [ "--http", "0.0.0.0:8090", "--flight", "0.0.0.0:50051", "s3://your_bucket/path/to/spicepod.yaml" ]

    Register the task definition in your AWS account, i.e. aws ecs register-task-definition --cli-input-json file://spiceai-task-definition.json --region us-east-1

    Then run the task as you normally would in ECS.

    Resources

    Vendor resources

    Support

    Vendor support

    Spice.ai Enterprise includes 24/7 dedicated support with a dedicated Slack/Team channel, priority email and ticketing, ensuring critical issues are addressed per the Enterprise SLA.

    Detailed enterprise support information is available in the Support Policy & SLA document provided at onboarding.

    For general support, please email support@spice.ai .

    AWS infrastructure support

    AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.

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