What is AlloyDB?
AlloyDB for PostgreSQL is Google’s fully managed, PostgreSQL-compatible database for enterprise workloads with up to 4x higher performance and an integrated analytics engine.
AlloyDB is a PostgreSQL-compatible database developed for business-critical applications. Unlike standard PostgreSQL, AlloyDB uses Google’s distributed storage architecture and offers drastically higher performance with full PostgreSQL compatibility.
The architecture completely separates compute and storage. This enables independent scaling of both components and higher availability through distributed storage. Transactional data is automatically mirrored in a columnar engine for ultra-fast analytics without ETL.
Core Features
- Up to 4x faster transaction performance than standard PostgreSQL
- Integrated columnar engine for OLAP queries up to 100x faster
- Full wire compatibility with PostgreSQL 14 and 15
- Automatic multi-zone high availability
- Point-in-time recovery up to 35 days
Typical Use Cases
Enterprise Applications: High-performance transactional workloads with demanding SLAs benefit from AlloyDB’s optimized architecture. Up to 5000 concurrent connections without performance degradation.
Hybrid OLTP/OLAP: The columnar engine enables real-time analytics on production data without separate data warehouses or ETL pipelines. Dashboards query live transactional data.
PostgreSQL Migration: AlloyDB simplifies migration from on-premise PostgreSQL with Database Migration Service. Applications work without code changes due to wire compatibility.
Benefits
- Significant performance improvement over standard PostgreSQL
- No ETL required for analytics workloads
- Familiar PostgreSQL tools and extensions
- AlloyDB Omni for hybrid and multi-cloud deployments
Integration with innFactory
As a Google Cloud partner, innFactory supports you with AlloyDB: migration from on-premise or Cloud SQL, performance tuning, HA/DR setup, and hybrid deployments with AlloyDB Omni.
Available Tiers & Options
AlloyDB Primary
- Up to 4x faster than standard PostgreSQL
- Columnar engine for analytics
- Automatic backups and point-in-time recovery
- Full PostgreSQL compatibility
- Higher cost than Cloud SQL
- Regional only (no multi-region)
AlloyDB Omni
- On-premises or other clouds
- Kubernetes-based
- Identical API as Cloud AlloyDB
- Self-management required
- No Google Cloud integrations
Typical Use Cases
Technical Specifications
Frequently Asked Questions
What is AlloyDB and how does it differ from Cloud SQL PostgreSQL?
AlloyDB is a fully managed PostgreSQL-compatible database specifically optimized for enterprise workloads. Compared to Cloud SQL PostgreSQL, AlloyDB offers up to 4x higher transaction performance and 100x faster analytics through the integrated columnar engine. AlloyDB uses Google's distributed storage architecture for higher availability and scalability.
What is the AlloyDB Columnar Engine?
The columnar engine is an integrated analytics engine that automatically replicates transactional data in a column-oriented format. This enables OLAP queries (analytics) up to 100x faster than standard PostgreSQL without ETL processes or separate data warehouses. Transactional and analytical workloads run on the same database without performance impact.
Is AlloyDB truly PostgreSQL-compatible?
Yes, AlloyDB is wire-compatible with PostgreSQL 14 and 15. Existing PostgreSQL applications work without code changes. Extensions like PostGIS, pgvector for vector search, and standard PostgreSQL tools are supported. Compatibility enables easy migration from on-premise PostgreSQL or Cloud SQL.
When should I use AlloyDB instead of Cloud SQL PostgreSQL?
Use AlloyDB for business-critical applications with high performance requirements, hybrid OLTP/OLAP workloads, or large data volumes over 1 TB. Cloud SQL PostgreSQL is better for smaller workloads, development environments, or when multi-region deployments are needed. AlloyDB offers higher performance, Cloud SQL more flexibility with regions.
Does AlloyDB support vector search for AI applications?
Yes, AlloyDB supports the pgvector extension for vector embeddings and similarity search. This enables storing and querying ML embeddings directly in the database for RAG (Retrieval-Augmented Generation), recommendation engines, or semantic search. Performance is optimized for billions of vectors.
