3 posts tagged with "odbc"

The v0.15.1-alpha minor release focuses on enhancing stability, performance, and usability. Memory usage has been significantly improved for the postgres and duckdb acceleration engines which now use stream processing. A new Delta Lake Data Connector has been added, sharing a delta-kernel-rs based implementation with the Databricks Data Connector supporting deletion vectors.

Highlights​

Improved memory usage for PostgreSQL and DuckDB acceleration engines: Large dataset acceleration with PostgreSQL and DuckDB engines has reduced memory consumption by streaming data directly to the accelerated table as it is read from the source.

Delta Lake Data Connector: A new Delta Lake Data Connector has been added for using Delta Lake outside of Databricks.

ODBC Data Connector Streaming: The ODBC Data Connector now streams results, reducing memory usage, and improving performance.

GraphQL Object Unnesting: The GraphQL Data Connector can automatically unnest objects from GraphQL queries using the unnest_depth parameter.

The v0.12.2-alpha release introduces data streaming and key-pair authentication for the Snowflake data connector, enables general append mode data refreshes for time-series data, improves connectivity error messages, adds nested folders support for the S3 data connector, and exposes nodeSelector and affinity keys in the Helm chart for better Kubernetes management.

Highlights​

• Improved Connectivity Error Messages: Error messages provide clearer, actionable guidance for misconfigured settings or unreachable data connectors.

• Snowflake Data Connector Improvements: Enables data streaming by default and adds support for key-pair authentication in addition to passwords.

• API for Refresh SQL Updates: Update dataset Refresh SQL via API.

• Append Data Refresh: Append mode data refreshes for time-series data are now supported for all data connectors. Specify a dataset time_column with refresh_mode: append to only fetch data more recent than the latest local data.

• Docker Image Update: The spiceai/spiceai:latest Docker image now includes the ODBC data connector. For a smaller footprint, use spiceai/spiceai:latest-slim.

• Helm Chart Improvements: nodeSelector and affinity keys are now supported in the Helm chart for improved Kubernetes deployment management.

The v0.12-alpha release introduces Clickhouse and Apache Spark data connectors, adds support for limiting refresh data periods for temporal datasets, and includes upgraded Spice Client SDKs compatible with Spice OSS.

Highlights​

• Clickhouse data connector: Use Clickhouse as a data source with the clickhouse: scheme.

• Apache Spark Connect data connector: Use Apache Spark Connect connections as a data source using the spark: scheme.

• Refresh data window: Limit accelerated dataset data refreshes to the specified window, as a duration from now configuration setting, for faster and more efficient refreshes.

• ODBC data connector: Use ODBC connections as a data source using the odbc: scheme. The ODBC data connector is currently optional and not included in default builds. It can be conditionally compiled using the odbc cargo feature when building from source.

• Spice Client SDK Support: The official Spice SDKs have been upgraded with support for Spice OSS.

  • spice-rs v2.0.0
  • spice.js v2.0.0
  • gospice v6.0.0
  • spicepy v2.0.0