Timescale, the leading PostgreSQL database platform, expanded its PostgreSQL AI offerings with the launch of a groundbreaking tool, pgai Vectorizer, available open-source and hosted in the cloud. Pgai Vectorizer unlocks the ability for any developer to build advanced AI applications without the need for external tools or specialized expertise. This release, along with the pgai suite of PostgreSQL extensions— pgai and pgvectorscale—slashes infrastructure costs by 75%.
PostgreSQL is the world’s most popular database, used by 49% of developers worldwide. To truly democratize AI, it needs to be put in the hands of these developers. Timescale is dedicated to this mission, bringing cutting-edge technology to the PostgreSQL community, without needing specialized tooling or knowledge. Timescale did this first by extending PostgreSQL for real-time analytics, now, Timescale brings AI to PostgreSQL with the pgai suite and the launch of pgai Vectorizer – putting AI development in every developer’s hands.
Developers are under growing pressure to deliver AI systems such as search engines, retrieval-augmented generation (RAG), and AI agents. However, this often involves managing complex workflows across multiple tools: embedding creation, data processing, and real-time synchronization. New specialized tools emerge daily, adding infrastructure overhead and demanding new expertise, but few have the operational maturity or flexibility required for production.
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Pgai Vectorizer integrates the entire embedding process into PostgreSQL, allowing developers to create, store, and manage vector embeddings alongside relational data without external tools or added infrastructure. Together with the full pgai suite, it integrates the entire AI workflow into PostgreSQL, simplifying complex workflows into a single system. This enables developers to build state-of-the-art AI applications quickly, more reliably, and with fewer resources—all using familiar SQL commands.
“pgai Vectorizer is a game-changer. It promises to streamline our entire AI workflow, from embedding creation to real-time synchronization, allowing us to deliver AI applications faster and more efficiently,” said Web Begole, CTO at MarketReader. “By integrating everything directly into PostgreSQL, pgai Vectorizer removes the need for external tools and expertise, making it easier for our team to focus on innovation rather than infrastructure.”
Thousands of developers are already using the pgai suite of AI tools, and with pgai Vectorizer now in early access, they now have even greater power to streamline workflows and accelerate AI development.
Key differentiating capabilities of pgai Vectorizer:
- Unified AI and Data Platform: Manage all data for AI apps—vectors, metadata, event data—while seamlessly handling the embedding process on the same trusted PostgreSQL database platform, with no external systems needed.
- Real-Time Synchronization: Automatically synchronize vector embeddings with the latest data changes, avoiding staleness and conflicting sources of truth.
- Seamless Experimentation: Easily switch between embedding models for rapid testing and experimentation without modifying application code or creating custom data pipelines.
- Version Tracking and Compatibility: Track model versions and ensure backward compatibility during rollouts for smooth transitions.
While specialized vector databases or bolted-on systems require complex setups and specialized expertise, pgai Vectorizer delivers a seamless, high-performance experience that goes beyond vector search, built entirely on PostgreSQL. By fusing the simplicity developers rely on with the cutting-edge AI capabilities they need, pgai Vectorizer not only sets itself apart—it redefines what’s possible with PostgreSQL—extending it into the ultimate platform for any developer building the next-generation AI application.
SOURCE: PRNewsWire