date: 2025-10-07 title: 'Spice v1.8.0 (Oct 6, 2025)' type: blog authors: [phillipleblanc] tags: [release, iceberg, snapshots, amazon-s3-vectors, vector-search, llm-tools, sql]

Announcing the release of Spice v1.8.0! 🧊

Spice v1.8.0 delivers major advances in data writes, scalable vector search, and now in preview—managed acceleration snapshots for fast cold starts. This release introduces write support for Iceberg tables using standard SQL INSERT INTO, partitioned S3 Vector indexes for petabyte-scale vector search, and preview of the AI SQL function for direct LLM integration in SQL. Additional improvements include improved reliability, and the v3.0.3 release of the Spice.js Node.js SDK.

What's New in v1.8.0

Iceberg Table Write Support (Preview)

Append Data to Iceberg Tables with SQL INSERT INTO: Spice now supports writing to Iceberg tables and catalogs using standard SQL INSERT INTO statements. This enables data ingestion, transformation, and pipeline use cases—no Spark or external writer required.

• Append-only: Initial version targets appends; no overwrite or delete.
• Schema validation: Inserted data must match the target table schema.
• Secure by default: Writes are only enabled for datasets or catalogs explicitly marked with access: read_write.

Example Spicepod configuration:

catalogs:
  - from: iceberg:https://glue.ap-northeast-3.amazonaws.com/iceberg/v1/catalogs/111111/namespaces
    name: ice
    access: read_write

datasets:
  - from: iceberg:https://iceberg-catalog-host.com/v1/namespaces/my_namespace/tables/my_table
    name: iceberg_table
    access: read_write

catalogs:
  - from: iceberg:https://glue.ap-northeast-3.amazonaws.com/iceberg/v1/catalogs/111111/namespaces
    name: ice
    access: read_write

datasets:
  - from: iceberg:https://iceberg-catalog-host.com/v1/namespaces/my_namespace/tables/my_table
    name: iceberg_table
    access: read_write

Example SQL usage:

-- Insert from another table
INSERT INTO iceberg_table
SELECT * FROM existing_table;

-- Insert with values
INSERT INTO iceberg_table (id, name, amount)
VALUES (1, 'John', 100.0), (2, 'Jane', 200.0);

-- Insert into catalog table
INSERT INTO ice.sales.transactions
VALUES (1001, '2025-01-15', 299.99, 'completed');

-- Insert from another table
INSERT INTO iceberg_table
SELECT * FROM existing_table;

-- Insert with values
INSERT INTO iceberg_table (id, name, amount)
VALUES (1, 'John', 100.0), (2, 'Jane', 200.0);

-- Insert into catalog table
INSERT INTO ice.sales.transactions
VALUES (1001, '2025-01-15', 299.99, 'completed');

Note: Only Iceberg datasets and catalogs with access: read_write support writes. Internal Spice tables and other connectors remain read-only.

Learn more in the Iceberg Data Connector documentation (opens in a new tab).

Acceleration Snapshots for Fast Cold Starts (Preview)

Bootstrap Managed Accelerations from Object Storage: Spice now supports managed acceleration snapshots in preview, enabling datasets accelerated with file-based engines (DuckDB or SQLite) to bootstrap from a snapshot stored in object storage (such as S3) if the local acceleration file does not exist on startup. This dramatically reduces cold start times and enables ephemeral storage for accelerations with persistent recovery.

Key features:

• Rapid readiness: Datasets can become ready in seconds by downloading a pre-built snapshot, skipping lengthy initial acceleration.
• Hive-style partitioning: Snapshots are organized by month, day, and dataset for easy retention and management.
• Flexible bootstrapping: Configurable fallback and retry behavior if a snapshot is missing or corrupted.

Example Spicepod configuration:

snapshots:
  enabled: true
  location: s3://some_bucket/some_folder/ # Folder for storing snapshots
  bootstrap_on_failure_behavior: warn # Options: warn, retry, fallback
  params:
    s3_auth: iam_role # All S3 dataset params accepted here

datasets:
  - from: s3://some_bucket/some_table/
    name: some_table
    params:
      file_format: parquet
      s3_auth: iam_role
    acceleration:
      enabled: true
      snapshots: enabled # Options: enabled, disabled, bootstrap_only, create_only
      engine: duckdb
      mode: file
      params:
        duckdb_file: /nvme/some_table.db

snapshots:
  enabled: true
  location: s3://some_bucket/some_folder/ # Folder for storing snapshots
  bootstrap_on_failure_behavior: warn # Options: warn, retry, fallback
  params:
    s3_auth: iam_role # All S3 dataset params accepted here

datasets:
  - from: s3://some_bucket/some_table/
    name: some_table
    params:
      file_format: parquet
      s3_auth: iam_role
    acceleration:
      enabled: true
      snapshots: enabled # Options: enabled, disabled, bootstrap_only, create_only
      engine: duckdb
      mode: file
      params:
        duckdb_file: /nvme/some_table.db

How it works:

• On startup, if the acceleration file does not exist, Spice checks the snapshot location for the latest snapshot and downloads it.
• Snapshots are stored as: s3://some_bucket/some_folder/month=2025-09/day=2025-09-30/dataset=some_table/some_table_<timestamp>.db
• If no snapshot is found, a new acceleration file is created as usual.
• Snapshots are written after each refresh (unless configured otherwise).

Supported snapshot modes:

• enabled: Download and write snapshots.
• bootstrap_only: Only download on startup, do not write new snapshots.
• create_only: Only write snapshots, do not download on startup.
• disabled: No snapshotting.

Note: This feature is only supported for file-based accelerations (DuckDB or SQLite) with dedicated files.

Why use acceleration snapshots?

• Faster cold starts: Skip waiting for full acceleration on startup.
• Ephemeral storage: Use fast local disks (e.g., NVMe) for acceleration, with persistent recovery from object storage.
• Disaster recovery: Recover from federated source outages by bootstrapping from the latest snapshot.

Partitioned S3 Vector Indexes

Efficient, Scalable Vector Search with Partitioning: Spice now supports partitioning Amazon S3 Vector indexes and scatter-gather queries using a partition_by expression in the dataset vector engine configuration. Partitioned indexes enable faster ingestion, lower query latency, and scale to billions of vectors.

Example Spicepod configuration:

datasets:
  - name: reviews
    vectors:
      enabled: true
      engine: s3_vectors
      params:
        s3_vectors_bucket: my-bucket
        s3_vectors_index: base-embeddings
      partition_by:
        - 'bucket(50, PULocationID)'
    columns:
      - name: body
        embeddings:
          from: bedrock_titan
      - name: title
        embeddings:
          from: bedrock_titan

datasets:
  - name: reviews
    vectors:
      enabled: true
      engine: s3_vectors
      params:
        s3_vectors_bucket: my-bucket
        s3_vectors_index: base-embeddings
      partition_by:
        - 'bucket(50, PULocationID)'
    columns:
      - name: body
        embeddings:
          from: bedrock_titan
      - name: title
        embeddings:
          from: bedrock_titan

See the Amazon S3 Vectors documentation (opens in a new tab) for details.

AI SQL function for LLM Integration (Preview)

LLMs Directly In SQL: A new asynchronous ai SQL function enables direct calls to LLMs from SQL queries for text generation, translation, classification, and more. This feature is released in preview and supports both default and model-specific invocation.

Example Spicepod model configuration:

models:
  - name: gpt-4o
    from: openai:gpt-4o
    params:
      openai_api_key: ${secrets:openai_key}

models:
  - name: gpt-4o
    from: openai:gpt-4o
    params:
      openai_api_key: ${secrets:openai_key}

Example SQL usage:

-- basic usage with default model
SELECT ai('hi, this prompt is directly from SQL.');

-- basic usage with default model
SELECT ai('hi, this prompt is directly from SQL.');

-- basic usage with specified model
SELECT ai('hi, this prompt is directly from SQL.', 'gpt-4o');

-- basic usage with specified model
SELECT ai('hi, this prompt is directly from SQL.', 'gpt-4o');

-- Using row data as input to the prompt
SELECT ai(concat_ws(' ', 'Categorize the zone', Zone, 'in a single word. Only return the word.')) AS category
FROM taxi_zones
LIMIT 10;

-- Using row data as input to the prompt
SELECT ai(concat_ws(' ', 'Categorize the zone', Zone, 'in a single word. Only return the word.')) AS category
FROM taxi_zones
LIMIT 10;

Learn more in the SQL Reference AI documentation (opens in a new tab).

Remote Endpoint Support for Spice CLI

Run CLI Commands Remotely: The Spice CLI now supports connecting to remote Spice instances, enabling you to run spice sql, spice search, and spice chat commands from your local machine against a remote spiced daemon or to Spice Cloud. Previously, these commands required running on the same machine as the runtime. Now, new flags allow remote execution:

• --cloud: Connect to a Spice Cloud instance (requires --api-key).
• --endpoint <endpoint>: Connect to a remote Spice instance via HTTP or Arrow Flight SQL (gRPC). Supports http://, https://, grpc://, or grpc+tls:// schemes.

Examples:

# Run SQL queries against a remote Spice instance
spice sql --endpoint http://remote-host:8090

# Use Spice Cloud for chat or search
spice chat --cloud --api-key <your-api-key>
spice search --cloud --api-key <your-api-key>

# Run SQL queries against a remote Spice instance
spice sql --endpoint http://remote-host:8090

# Use Spice Cloud for chat or search
spice chat --cloud --api-key <your-api-key>
spice search --cloud --api-key <your-api-key>

Supported CLI Commands:

• spice sql --cloud / spice sql --endpoint <endpoint>
• spice search --cloud / spice search --endpoint <endpoint>
• spice chat --cloud / spice chat --endpoint <endpoint>

Additional Flags:

• --headers: Pass custom HTTP headers to the remote endpoint.
• --tls-root-certificate-file: Specify a root certificate for TLS verification.
• --user-agent: Set a custom user agent for requests.

For more details, see the Spice CLI Command Reference (opens in a new tab).

Spice.js v3.0.3 SDK

Spice.js v3.0.3 Released: The official Spice.ai Node.js/JavaScript SDK (opens in a new tab) has been updated to v3.0.3, bringing cross-platform support, new APIs, and improved reliability for both Node.js and browser environments.

• Modern Query Methods: Use sql(), sqlJson(), and nsql() for flexible querying, streaming, and natural language to SQL.
• Browser Support: SDK now works in browsers and web applications, automatically selecting the optimal transport (gRPC or HTTP).
• Health Checks & Dataset Refresh: Easily monitor Spice runtime health and trigger dataset refreshes on demand.
• Automatic HTTP Fallback: If gRPC/Flight is unavailable, the SDK falls back to HTTP automatically.
• Migration Guidance: v3 requires Node.js 20+, uses camelCase parameters, and introduces a new package structure.

Example usage:

import { SpiceClient } from '@spiceai/spice'

const client = new SpiceClient(apiKey)
const table = await client.sql('SELECT * FROM my_table LIMIT 10')
console.table(table.toArray())

import { SpiceClient } from '@spiceai/spice'

const client = new SpiceClient(apiKey)
const table = await client.sql('SELECT * FROM my_table LIMIT 10')
console.table(table.toArray())

See Spice.js SDK documentation (opens in a new tab) for full details, migration tips, and advanced usage.

Additional Improvements

• Reliability: Improved logging, error handling, and network readiness checks across connectors (Iceberg, Databricks, etc.).
• Vector search durability and scale: Refined logging, stricter default limits, safeguards against index-only scans and duplicate results, and always-accessible metadata for robust queryability at scale.
• Cache behavior: Tightened cache logic for modification queries.
• Full-Text Search: FTS metadata columns now usable in projections; max search results increased to 1000.
• RRF Hybrid Search: Reciprocal Rank Fusion (RRF) UDTF enhancements for advanced hybrid search scenarios.

Contributors

• @Jeadie (opens in a new tab)
• @mach-kernel (opens in a new tab)
• @lukekim (opens in a new tab)
• @phillipleblanc (opens in a new tab)
• @sgrebnov (opens in a new tab)
• @kczimm (opens in a new tab)
• @krinart (opens in a new tab)
• @peasee (opens in a new tab)
• @ewgenius (opens in a new tab)

Breaking Changes

This release introduces two breaking changes associated with the search observability and tooling.

Firstly, the document_similarity (opens in a new tab) tool has been renamed to search. This has the equivalent change to tracing of these tool calls:

## Old: v1.7.1
>> spice trace tool_use::document_similarity
>> curl -XPOST http://localhost:8090/v1/tools/document_similarity \
  -d '{
    "datasets": ["my_tbl"],
    "text": "Welcome to another Spice release"
  }'

## New: v1.8.0
>> spice trace tool_use::search
>> curl -XPOST http://localhost:8090/v1/tools/search \
  -d '{
    "datasets": ["my_tbl"],
    "text": "Welcome to another Spice release"
  }'

## Old: v1.7.1
>> spice trace tool_use::document_similarity
>> curl -XPOST http://localhost:8090/v1/tools/document_similarity \
  -d '{
    "datasets": ["my_tbl"],
    "text": "Welcome to another Spice release"
  }'

## New: v1.8.0
>> spice trace tool_use::search
>> curl -XPOST http://localhost:8090/v1/tools/search \
  -d '{
    "datasets": ["my_tbl"],
    "text": "Welcome to another Spice release"
  }'

Secondly, the vector_search task in runtime.task_history has been renamed to search.

Cookbook Updates

• Added new AI SQL function (opens in a new tab) recipe for invoking LLMs within SQL queries.
• Updated Iceberg Catalog Connector (opens in a new tab) recipe for Iceberg Writes.
• Updated Spice.js JavaScript (Node.js) SDK (opens in a new tab) for v3.0.3 with examples and v2 to v3 migration guide.

The Spice Cookbook (opens in a new tab) now includes 80 recipes to help you get started with Spice quickly and easily.

Upgrading

To upgrade to v1.8.0, use one of the following methods:

CLI:

spice upgrade

spice upgrade

Homebrew:

brew upgrade spiceai/spiceai/spice

brew upgrade spiceai/spiceai/spice

Docker:

Pull the spiceai/spiceai:1.8.0 image:

docker pull spiceai/spiceai:1.8.0

docker pull spiceai/spiceai:1.8.0

For available tags, see DockerHub (opens in a new tab).

Helm:

helm repo update
helm upgrade spiceai spiceai/spiceai

helm repo update
helm upgrade spiceai spiceai/spiceai

AWS Marketplace:

🎉 Spice is now available in the AWS Marketplace (opens in a new tab)!

What's Changed

Dependencies

• iceberg-rust: Upgraded to v0.7.0-rc.1 (opens in a new tab)
• mimalloc: Upgraded from 0.1.47 to 0.1.48
• azure_core: Upgraded from 0.27.0 to 0.28.0
• Jimver/cuda-toolkit: Upgraded from 0.2.27 to 0.2.28

Changelog

• Add #[cfg(feature = "postgres")] to acceleration refresh tests by @Jeadie (opens in a new tab) in #7241 (opens in a new tab)
• fix: Update benchmark snapshots by @github-actions[bot] (opens in a new tab) in #7267 (opens in a new tab)
• fix: Update benchmark snapshots by @github-actions[bot] (opens in a new tab) in #7268 (opens in a new tab)
• fix: Update benchmark snapshots by @github-actions[bot] (opens in a new tab) in #7269 (opens in a new tab)
• Update the tpch benchmark snapshots for: federated/databricks[sql_warehouse].yaml by @github-actions[bot] (opens in a new tab) in #7270 (opens in a new tab)
• EmbeddingInput cache keys to include model name by @mach-kernel (opens in a new tab) in #7275 (opens in a new tab)
• ensure FTS metadata columns can be used in projection by @Jeadie (opens in a new tab) in #7282 (opens in a new tab)
• Use 8-core runners for Windows CUDA builds by @sgrebnov (opens in a new tab) in #7284 (opens in a new tab)
• Make search test more robust by @krinart (opens in a new tab) in #7283 (opens in a new tab)
• Post-release housekeeping by @sgrebnov (opens in a new tab) in #7272 (opens in a new tab)
• fix: Use median cached response duration for test search cache by @peasee (opens in a new tab) in #7286 (opens in a new tab)
• Bump dirs from 5.0.1 to 6.0.0 by @dependabot[bot] (opens in a new tab) in #7244 (opens in a new tab)
• Bump indexmap from 2.11.0 to 2.11.4 by @dependabot[bot] (opens in a new tab) in #7248 (opens in a new tab)
• Fix JOIN level filters not having columns in schema by @Jeadie (opens in a new tab) in #7287 (opens in a new tab)
• use SessionContext::new_empty in RRF by @kczimm (opens in a new tab) in #7291 (opens in a new tab)
• Use rust:1.89-slim-bookworm for build, more places to bump rust version by @sgrebnov (opens in a new tab) in #7293 (opens in a new tab)
• Update openapi.json by @github-actions[bot] (opens in a new tab) in #7290 (opens in a new tab)
• Enable chunking in SearchIndex by @Jeadie (opens in a new tab) in #7143 (opens in a new tab)
• Add index name and remove duplicate records string to S3 Vectors log by @lukekim (opens in a new tab) in #7260 (opens in a new tab)
• Use file-based fts index by @Jeadie (opens in a new tab) in #7024 (opens in a new tab)
• Remove 'PostApplyCandidateGeneration' by @Jeadie (opens in a new tab) in #7288 (opens in a new tab)
• RRF: Rank and recency boosting by @mach-kernel (opens in a new tab) in #7294 (opens in a new tab)
• Update ROADMAP.md by removing v1.7 milestone by @sgrebnov (opens in a new tab) in #7297 (opens in a new tab)
• RRF: Preserve base ranking when results differ -> FULL OUTER JOIN does not produce time column by @mach-kernel (opens in a new tab) in #7300 (opens in a new tab)
• chore: remove unused Dataset methods by @kczimm (opens in a new tab) in #7295 (opens in a new tab)
• fix removing embedding column by @Jeadie (opens in a new tab) in #7302 (opens in a new tab)
• fix: Add feature flag for using object store in spicepod by @peasee (opens in a new tab) in #7303 (opens in a new tab)
• Upgrade to iceberg-rust v0.7.0-rc1 by @sgrebnov (opens in a new tab) in #7296 (opens in a new tab)
• Enable DML Update SQL operations for datasets configured as access: read_write by @sgrebnov (opens in a new tab) in #7304 (opens in a new tab)
• Create and parse partitioned S3 vector index names by @kczimm (opens in a new tab) in #7198 (opens in a new tab)
• RRF: Fix decay for disjoint result sets by @mach-kernel (opens in a new tab) in #7305 (opens in a new tab)
• RRF: Project top scores, do not yield duplicate results by @mach-kernel (opens in a new tab) in #7306 (opens in a new tab)
• RRF: Case sensitive column/ident handling by @mach-kernel (opens in a new tab) in #7309 (opens in a new tab) in #7309 (opens in a new tab)
• For vector_search, use a default limit of 1000 if no limit specified by @lukekim (opens in a new tab) in #7311 (opens in a new tab)
• Don’t cache modification queries (DDL, DML, COPY) by @sgrebnov (opens in a new tab) in #7316 (opens in a new tab)
• Fix Anthropic model regex and add validation tests by @ewgenius (opens in a new tab) in #7319 (opens in a new tab)
• Enhancement: Implement before/after/lag metrics for acceleration refresh by @krinart (opens in a new tab) in #7310 (opens in a new tab)
• Refactor chat model health check to lower tokens usage for reasoning models by @ewgenius (opens in a new tab) in #7317 (opens in a new tab)
• Add support for writing into Iceberg tables by @sgrebnov (opens in a new tab) in #7315 (opens in a new tab)
• Fix lint warnings by @lukekim (opens in a new tab) in #7327 (opens in a new tab)
• Use logical plan in SearchQueryProvider by @Jeadie (opens in a new tab) in #7314 (opens in a new tab)
• FTS max search results 100 -> 1000 by @Jeadie (opens in a new tab) in #7331 (opens in a new tab)
• Improve Databricks SQL Warehouse Error Handling by @sgrebnov (opens in a new tab) in #7332 (opens in a new tab)
• Use spicepod embedding model name for model_name() by @Jeadie (opens in a new tab) in #7333 (opens in a new tab)
• Handle async queries for Databricks SQL Warehouse API by @phillipleblanc (opens in a new tab) in #7335 (opens in a new tab)
• Enable DML (INSERT INTO) operations for catalogs configured as access:read_write by @sgrebnov (opens in a new tab) in #7330 (opens in a new tab)
• Bump regex from 1.11.2 to 1.11.3 by @dependabot[bot] (opens in a new tab) in #7336 (opens in a new tab)
• Update qa_analytics.csv with 1.7.0 release data by @sgrebnov (opens in a new tab) in #7337 (opens in a new tab)
• RRF: Fix ident resolution for struct fields, autohashed join key for varying types by @mach-kernel (opens in a new tab) in #7339 (opens in a new tab)
• v1.7.1 release notes by @kczimm (opens in a new tab) in #7348 (opens in a new tab)
• Bump Jimver/cuda-toolkit from 0.2.27 to 0.2.28 by @dependabot[bot] (opens in a new tab) in #7343 (opens in a new tab)
• Add support for writing into Glue (Iceberg) tables and catalogs by @sgrebnov (opens in a new tab) in #7355 (opens in a new tab)
• Bump mimalloc from 0.1.47 to 0.1.48 by @dependabot[bot] (opens in a new tab) in #7342 (opens in a new tab)
• Add ai async UDF by @lukekim (opens in a new tab) in #7328 (opens in a new tab)
• Use self-hosted and spiceai-macos runners for workflows where possible by @lukekim (opens in a new tab) in #7371 (opens in a new tab)
• Several updates for improved search testing by @Jeadie (opens in a new tab) in #7358 (opens in a new tab)
• Update supported versions in SECURITY.md by @Jeadie (opens in a new tab) in #7377 (opens in a new tab)
• 1.7.1 release analytics by @mach-kernel (opens in a new tab) in #7380 (opens in a new tab)
• Add acceleration_file_path helper and refactor spice_sys to use Snafu errors by @phillipleblanc (opens in a new tab) in #7376 (opens in a new tab) in #7376 (opens in a new tab)
• fix: Update benchmark snapshots by @github-actions[bot] (opens in a new tab) in #7353 (opens in a new tab)
• Robust search test by @Jeadie (opens in a new tab) in #7381 (opens in a new tab)
• [bug] Fix ai UDF bug of mismatched column length by @lukekim (opens in a new tab) in #7383 (opens in a new tab)
• Add OpenOption to spice_sys acceleration tables by @phillipleblanc (opens in a new tab) in #7379 (opens in a new tab)
• Add new snapshots Spicepod configuration by @phillipleblanc (opens in a new tab) in #7384 (opens in a new tab)
• Update naming of tool_use::document_similarity and vector_search spans by @Jeadie (opens in a new tab) in #7273 (opens in a new tab)
• fix: Update benchmark snapshots by @github-actions[bot] (opens in a new tab) in #7354 (opens in a new tab)
• Make ai UDF a models only feature by @lukekim (opens in a new tab) in #7387 (opens in a new tab)
• Add new runtime_acceleration crate; create SnapshotManager; implement SnapshotManager::download_latest_snapshot by @phillipleblanc (opens in a new tab) in #7386 (opens in a new tab)
• Refactor 'VectorScanTableProvider' to use just 'VectorIndex::list_table_provider' by @Jeadie (opens in a new tab) in #7318 (opens in a new tab)
• Fix embed logs by @Jeadie (opens in a new tab) in #7382 (opens in a new tab)
• Enable spicepod dependencies in testoperator by @Jeadie (opens in a new tab) in #7334 (opens in a new tab)
• ai UDF security and performance optimizations by @lukekim (opens in a new tab) in #7392 (opens in a new tab)
• Wire up the snapshot download on dataset startup by @phillipleblanc (opens in a new tab) in #7389 (opens in a new tab)
• Implement initial snapshot creation logic in SnapshotManager by @phillipleblanc (opens in a new tab) in #7391 (opens in a new tab)
• Make tool_use::table_schema output model-friendly by @krinart (opens in a new tab) in #7393 (opens in a new tab)
• Fix minor lint warnings by @lukekim (opens in a new tab) in #7395 (opens in a new tab)
• Enable metadata columns in document-based object store datasets by @Jeadie (opens in a new tab) in #7397 (opens in a new tab)
• Core dependencies of financebench by @Jeadie (opens in a new tab) in #7400 (opens in a new tab)
• Add S3vector variant to financebench by @Jeadie (opens in a new tab) in #7399 (opens in a new tab)
• Set PostgreSQL unsupported_spice_action=string by default by @lukekim (opens in a new tab) in #7398 (opens in a new tab)
• Use non-blocking connection check for verify_ns_lookup_and_tcp_connect by @phillipleblanc (opens in a new tab) in #7401 (opens in a new tab)
• Bump moka from 0.12.10 to 0.12.11 by @dependabot[bot] (opens in a new tab) in #7340 (opens in a new tab)
• Bump tokio-postgres from 0.7.13 to 0.7.14 by @dependabot[bot] (opens in a new tab) in #7344 (opens in a new tab)
• Bump azure_core from 0.27.0 to 0.28.0 by @dependabot[bot] (opens in a new tab) in #7338 (opens in a new tab)
• Forbid INSERT OVERWRITE DML operations by @sgrebnov (opens in a new tab) in #7402 (opens in a new tab)
• Make database connection pool sizes consistent by @lukekim (opens in a new tab) in #7403 (opens in a new tab)
• Disable vector index only scans by @Jeadie (opens in a new tab) in #7405 (opens in a new tab)
• Make CLI --endpoint and --cloud args & table output consistent by @lukekim (opens in a new tab) in #7396 (opens in a new tab)
• Write new snapshots at the end of an accelerated refresh by @phillipleblanc (opens in a new tab) in #7410 (opens in a new tab)
• Read and write partitioned S3 indexes by @kczimm (opens in a new tab) in #7313 (opens in a new tab)
• Fix partial data writes in Iceberg data connector by @sgrebnov (opens in a new tab) in #7411 (opens in a new tab)
• Remove nix by @phillipleblanc (opens in a new tab) in #7414 (opens in a new tab)
• Use DataFusion JoinSetTracer for async context propagation by @lukekim (opens in a new tab) in #7416 (opens in a new tab)
• Implement cache invalidation for DML (INSERT INTO) operations by @sgrebnov (opens in a new tab) in #7394 (opens in a new tab)
• Make cleanup disk GH action; use in integration tests by @Jeadie (opens in a new tab) in #7418 (opens in a new tab)
• Move S3Vector to 'search' crate by @Jeadie (opens in a new tab) in #7373 (opens in a new tab)
• Use LogicalPlan builder API for LogicalPlans by @Jeadie (opens in a new tab) in #7408 (opens in a new tab)
• Use hive-style partitioned paths for DB snapshots by @phillipleblanc (opens in a new tab) in #7422 (opens in a new tab)
• Limit results from SearchIndex::query_table_provider by @Jeadie (opens in a new tab) in #7421 (opens in a new tab)
• Delay initial readiness if snapshots are enabled with an append-mode refresh by @phillipleblanc (opens in a new tab) in #7425 (opens in a new tab)
• Disable snapshots by default by @phillipleblanc (opens in a new tab) in #7426 (opens in a new tab)
• Rewrite ChunkedNonIndexVectorGeneration to use LogicalPlanBuilder (instead of string formatting) by @Jeadie (opens in a new tab) in #7413 (opens in a new tab)
• Fix for search field as metadata for chunked search indexes by @Jeadie (opens in a new tab) in #7429 (opens in a new tab)
• Add feature is currently in preview warning for read_write access mode by @sgrebnov (opens in a new tab) in #7440 (opens in a new tab)
• Add feature is currently in preview warning for snapshots by @sgrebnov (opens in a new tab) in #7442 (opens in a new tab)
• Fix tracing so that ai_completions are parented under sql_query by @lukekim (opens in a new tab) in #7415 (opens in a new tab)
• Disable acceleration refresh metrics by @krinart (opens in a new tab) in #7450 (opens in a new tab)
• Enable snapshot acceleration by default by @phillipleblanc (opens in a new tab) in #7451 (opens in a new tab)
• fix: partition name validation by @kczimm (opens in a new tab) in #7452 (opens in a new tab)