Towards AI Publishes Comprehensive Database Guide for AI Engineers
Towards AI released a guide comparing relational, NoSQL, vector, time series, graph, and NewSQL databases for AI workloads.
Towards AI published a technical guide breaking down six major database categories — relational, NoSQL, vector, time series, graph, and NewSQL — with a focus on how each serves modern AI and agentic system architectures.
As AI applications grow more complex, choosing the right data layer has become a critical engineering decision. Vector databases power semantic search and RAG pipelines, time series stores handle streaming telemetry from model monitoring, and graph databases map the relationships that agentic workflows need to reason over. The guide, part of Towards AI's practitioner-focused Academy content, walks engineers through the trade-offs of each category rather than advocating for a single solution. With the Academy now reaching over 100,000 AI practitioners, the resource reflects growing demand for foundational infrastructure knowledge as teams move beyond prototypes into production AI systems.