spice-accelerators

Original：🇺🇸 English

Translated

Configure data accelerators for local materialization and caching in Spice (Arrow, DuckDB, SQLite, Cayenne, PostgreSQL, Turso). Use when asked to "accelerate data", "enable caching", "materialize dataset", "configure refresh", "set up local storage", "improve query performance", "choose an accelerator", or "configure snapshots".

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Sourcespiceai/skills

Added on2026-02-18

NPX Install

npx skill4agent add spiceai/skills spice-accelerators

SKILL.md Content

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Spice Data Accelerators

Accelerators materialize data locally from connected sources for faster queries and reduced load on source systems.

Basic Configuration

yaml

datasets:
  - from: postgres:my_table
    name: my_table
    acceleration:
      enabled: true
      engine: duckdb # arrow, duckdb, sqlite, cayenne, postgres, turso
      mode: memory # memory or file
      refresh_check_interval: 1h

Choosing an Accelerator

Use Case	Engine	Why
Small datasets (<1 GB), max speed	`arrow`	In-memory, lowest latency
Medium datasets (1-100 GB), complex SQL	`duckdb`	Mature SQL, memory management
Large datasets (100 GB-1+ TB), analytics	`cayenne`	Built on Vortex (Linux Foundation), 10-20x faster scans
Point lookups on large datasets	`cayenne`	100x faster random access vs Parquet
Simple queries, low resource usage	`sqlite`	Lightweight, minimal overhead
Async operations, concurrent workloads	`turso`	Native async, modern connection pooling
External database integration	`postgres`	Leverage existing PostgreSQL infra

Cayenne vs DuckDB

Choose Cayenne when datasets exceed ~1 TB, multi-file ingestion is needed, or point lookups are common. Choose DuckDB when datasets are under ~1 TB, complex SQL (window functions, CTEs) is needed, or DuckDB tooling is beneficial.

Supported Engines

Engine	Mode	Status
`arrow`	memory	Stable
`duckdb`	memory, file	Stable
`sqlite`	memory, file	Release Candidate
`cayenne`	file	Beta
`postgres`	N/A (attached)	Release Candidate
`turso`	memory, file	Beta

Refresh Modes

Mode	Description	Use Case
`full`	Complete dataset replacement on each refresh	Small, slowly-changing datasets
`append` (batch)	Adds new records based on a `time_column`	Append-only logs, time-series data
`append` (stream)	Continuous streaming without time column	Real-time event streams (Kafka, Debezium)
`changes`	CDC-based incremental updates via Debezium or DynamoDB Streams	Frequently updated transactional data
`caching`	Request-based row-level caching	API responses, HTTP endpoints

yaml

# Full refresh every 8 hours
acceleration:
  refresh_mode: full
  refresh_check_interval: 8h

# Append mode: check for new records from the last day every 10 minutes
acceleration:
  refresh_mode: append
  time_column: created_at
  refresh_check_interval: 10m
  refresh_data_window: 1d

# Continuous ingestion using Kafka
acceleration:
  refresh_mode: append

# CDC with Debezium or DynamoDB Streams
acceleration:
  refresh_mode: changes

Common Configurations

In-Memory with Interval Refresh

yaml

acceleration:
  enabled: true
  engine: arrow
  refresh_check_interval: 5m

File-Based with Append and Time Window

yaml

datasets:
  - from: postgres:events
    name: events
    time_column: created_at
    acceleration:
      enabled: true
      engine: duckdb
      mode: file
      refresh_mode: append
      refresh_check_interval: 1h
      refresh_data_window: 7d

With Retention Policy

Retention policies prevent unbounded growth of accelerated datasets. Spice supports time-based and custom SQL-based retention strategies:

yaml

datasets:
  - from: postgres:events
    name: events
    time_column: created_at
    acceleration:
      enabled: true
      engine: duckdb
      retention_check_enabled: true
      retention_period: 30d
      retention_check_interval: 1h

With SQL-Based Retention

yaml

acceleration:
  retention_check_enabled: true
  retention_check_interval: 1h
  retention_sql: "DELETE FROM logs WHERE status = 'archived'"

With Indexes (DuckDB, SQLite, Turso)

yaml

acceleration:
  enabled: true
  engine: sqlite
  indexes:
    user_id: enabled
    '(created_at, status)': unique
  primary_key: id

Engine-Specific Parameters

DuckDB

yaml

acceleration:
  engine: duckdb
  mode: file
  params:
    duckdb_file: ./data/cache.db

SQLite

yaml

acceleration:
  engine: sqlite
  mode: file
  params:
    sqlite_file: ./data/cache.sqlite

Constraints and Indexes

Accelerated datasets support primary key constraints and indexes:

yaml

acceleration:
  enabled: true
  engine: duckdb
  primary_key: order_id # Creates non-null unique index
  indexes:
    customer_id: enabled # Single column index
    '(created_at, status)': unique # Multi-column unique index

Snapshots (DuckDB, SQLite & Cayenne file mode)

Bootstrap file-based accelerations from S3 or filesystem snapshots on startup. This dramatically reduces cold-start latency in distributed deployments.

Snapshot triggers vary by refresh mode:

```
refresh_complete
```
: Creates snapshots after each refresh (full and batch-append modes)
```
time_interval
```
: Creates snapshots on a fixed schedule (all refresh modes)
```
stream_batches
```
: Creates snapshots after every N batches (streaming modes: Kafka, Debezium, DynamoDB Streams)

yaml

snapshots:
  enabled: true
  location: s3://my_bucket/snapshots/
  bootstrap_on_failure_behavior: warn # warn | retry | fallback
  params:
    s3_auth: iam_role

Per-dataset opt-in:

yaml

acceleration:
  enabled: true
  engine: duckdb
  mode: file
  snapshots:
    enabled: true

Memory Considerations

When using

mode: memory

(default), the dataset is loaded into RAM. Ensure sufficient memory including overhead for queries and the runtime. Mitigate with

mode: file

for duckdb, sqlite, turso, or cayenne accelerators.

spice-accelerators

NPX Install

Tags

SKILL.md Content

Spice Data Accelerators

Basic Configuration

Choosing an Accelerator

Cayenne vs DuckDB

Supported Engines

Refresh Modes

Common Configurations

In-Memory with Interval Refresh

File-Based with Append and Time Window

With Retention Policy

With SQL-Based Retention

With Indexes (DuckDB, SQLite, Turso)

Engine-Specific Parameters

DuckDB

SQLite

Constraints and Indexes

Snapshots (DuckDB, SQLite & Cayenne file mode)

Memory Considerations

Documentation