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2025 Releases

Complete overview of Tacnode releases throughout 2025, including new features and improvements

This page documents all Tacnode releases for 2025, organized chronologically with the latest releases first.

Engine Release V1.3

This engine release introduces user-defined functions, enhanced data lake integration, advanced analytical capabilities, and improved PostgreSQL compatibility.

User-Defined Functions (UDF)

SQL, PL/pgSQL, and PL/Python support: Execute complex computation logic directly within the database
Vectorized execution: PL/Python includes vectorized execution capabilities for improved batch processing performance
Session-scoped temporary functions: Create ad hoc functions that are automatically cleaned up on disconnect
Learn more: UDF Management, Developing UDFs with PL/pgSQL, Writing UDFs with PL/Python

External Tables & Data Ingestion

IMPORT SCHEMA support: Automatic discovery of directory structures in S3 and object storage
Bulk import capabilities: Import Parquet and ORC external tables with directory-level filtering
Reduced maintenance overhead: Simplifies external table definition for data lake workloads
Learn more: file_fdw

Analytical Capabilities

CUBE, ROLLUP, and GROUPING SETS: More expressive multidimensional aggregations
Simplified analytical SQL: Improves query readability and development efficiency for analytical workloads
Learn more: Grouping Sets

Spatial Data Support

PostGIS data types: Geometry and geography type support for geospatial analysis
Spatial relationships: ST_Contains, ST_Intersects, ST_Within
Spatial measurements: ST_Distance, ST_Area
Geometric operations: Foundational geospatial analysis capabilities
Learn more: PostGIS Spatial Queries

Materialized Views

Schema evolution support: Structural changes via CREATE OR REPLACE MATERIALIZED VIEW
Reduced maintenance overhead: Flexibility when upstream schemas change
Learn more: ALTER MATERIALIZED VIEW, Materialized Views

Vector & AI Capabilities

Product Quantizer (PQ) support: Vector compression for optimized index storage and retrieval efficiency
Large-scale vector search: Improved performance and resource utilization for vector similarity search workloads
Learn more: Vector Search

PostgreSQL Compatibility

Session-scoped temporary functions: Create functions in the pg_temp schema visible only within the current session
Automatic cleanup: Temporary functions are cleaned up on disconnect
Improved tool compatibility: Enhanced compatibility with PostgreSQL tools and workflows

Observability & Operations

Database and table size functions: pg_database_size, pg_table_size, pg_relation_size
Storage visibility: Improved capacity management for operational and administrative use cases
Learn more: System Administration Functions

Query Performance Improvements

Enhanced query performance: Improved performance for point queries, analytical queries, and JSON query workloads
System stability: Enhanced overall execution efficiency under mixed workloads

2025.5 Engine Release V1.2

Release Date: May 2025

This major engine release focuses on performance optimization, enhanced SQL capabilities, and improved data lake integration.

SQL Engine Enhancements

Runtime Filter Optimization

Query optimizer support for efficient runtime filters: Dynamically generates and applies filter conditions during query execution
Performance benefits: Significantly reduces data scan volumes, I/O operations, and network overheads
Best use case: Particularly effective for large table join small table scenarios

Stability & Scalability

Improved SQL engine spill capability: Supports adaptive spill to enhance stability for large workloads
Enhanced partitioned table usability:
- Support for truncating parent tables
- Setting different storage formats per partition (hot/cold tiering)
- CDC subscription at the partitioned parent level
- Learn more: Partitioned Tables

Query Optimization

Enhanced pg_hint_plan support: Runtime query behavior can be dynamically adjusted via the hint_table configuration
Learn more: SQL Hints

Incremental Materialized View Enhancements

Performance Improvements

Improved refresh process: Reduced need for table-level locks and better parallel refresh efficiency

New Aggregate Functions

string_agg(DISTINCT) for distinct string aggregation
approx_count_distinct for approximate distinct counting
approx_percentile for approximate percentile calculations
Learn more: Approximate Computing

Dynamic Configuration

Storage format modification: Support for dynamic modification of materialized view storage format
```
ALTER MATERIALIZED VIEW mv_name SET ACCESS METHOD columnar/row/hybrid;
```
Dynamic index creation: Full support for runtime index management
Learn more: Materialized Views

Vector Search Optimization

HNSW index improvements: Now supports vector quantization including int8/fp16 types
Memory efficiency: Converts original float vectors into more compact types to reduce memory footprint
Performance gains: Significant improvement in vector search performance
Learn more: Vector Search

Feature Store Optimization

Extended window functions support in incremental materialized views:
- Ranking functions: ROW_NUMBER, RANK, DENSE_RANK, NTILE
- Window aggregations: SUM OVER, AVG OVER, COUNT OVER, MIN OVER, MAX OVER
- Distribution functions: PERCENT_RANK, CUME_DIST
- Position functions: FIRST_VALUE, LAST_VALUE
- Lag/Lead functions: LAG, LEAD
- Statistical functions: stddev_pop, stddev_samp, var_pop, var_samp

Geospatial Capabilities

PostGIS extension: Added support for geospatial queries in SQL
Capabilities: Spatial relationships, measurement, and geometry operations
Learn more: PostGIS Geospatial Query

Search Improvements

Full-text search: Optimized relevance ranking for full-text search scenarios
Learn more: Full Text Search
JSON support enhancements:
- More JSON PATH query push-down optimizations
- Index acceleration for CAST filter scenarios
- Partial indexes for sparse JSON fields

Context Lake Enhancements

New Table Format Support

Iceberg Tables: Full support with Iceberg REST API Catalog integration
Learn more: Iceberg Foreign Table
Delta Lake: Complete support with Databricks Unity Catalog integration
Learn more: Unity Catalog Foreign Table

Enhanced Data Type Support

Array types: Parquet and ORC now support Array types
Learn more: External Table Type Mapping

2025.4 Platform Release: Cache & Auto Suspend

Release Date: April 2025

This platform release introduces intelligent caching and resource management features.

Cache System

Cold storage acceleration: Dramatically improves access speed to cold storage and data lakes
Performance benefits: Reduces latency for frequently accessed data
Learn more: Cache

Nodegroup Auto Suspend

Intelligent resource management: Automatically suspends Nodegroup instances that are idle for extended periods
Cost optimization: Significantly reduces compute resource costs
Seamless operation: Automatic resume when activity is detected

2025.3 Platform Release: Catalog & Isolation

Release Date: March 2025

This release focuses on enterprise-grade isolation and multi-tenancy capabilities.

Enhanced Nodegroup Isolation

Shared storage architecture: Implements flexible isolation using shared storage
Isolation types:
- Read/Write isolation: Complete separation of read and write operations
- Write/Write isolation: Multiple independent write workloads
- Read/Read isolation: Isolated read-only access patterns
Multi-team support: Perfect for multiple teams sharing a database while maintaining operational independence
Learn more: Nodegroup Isolation

2025.1 Engine Release V1.1

Release Date: January 2025

The first major engine release of 2025, introducing groundbreaking features for real-time analytics and advanced data management.

Incremental Materialized Views

Real-time Analytics Revolution

Near-real-time updates: Incremental refresh provides substantially fresher data with lower resource cost
Comprehensive aggregation support:
- Basic aggregations: COUNT, SUM, MIN, MAX
- Advanced functions: COUNT DISTINCT, variance, standard deviation
Advanced SQL features:
- HAVING expressions support
- WITH clauses (CTEs)
- All join types: INNER, LEFT OUTER, RIGHT OUTER, FULL OUTER
Learn more: Materialized Views

Advanced Table Management

Partitioned Table Enhancements

Flexible partition management: ATTACH/DETACH operations for partitions
Direct data import: Import data directly to parent tables
Improved maintenance: Streamlined partition operations
Learn more: Partitioned Tables

Hot/Cold Tiered Storage

Cost optimization: Balance performance and cost by automatically moving data between tiers
Reduced storage expenses: Significant cost savings for large datasets
Intelligent tiering: Automatic data movement based on access patterns
Learn more: Tiered Storage

Security Enhancements

Column-level Permissions

Fine-grained access control: Control SELECT and UPDATE access at the column level
Enhanced security: Protect sensitive data with precision
Compliance ready: Meet strict data governance requirements
Learn more: Column-level Security

Advanced Search & Analytics

Vector Search Improvements

HNSW vector index: Dramatically improved recall accuracy and performance
Billion-scale support: Handle massive vector datasets efficiently
Enhanced performance: Optimized for large-scale vector operations
Learn more: Vector Search