“Translytical” databases emerge as essential infrastructure for AI applications

Translytical databases are emerging as essential infrastructure for AI-driven applications, offering a unified platform that combines transactional and analytical capabilities. This integration solves a critical challenge for modern AI systems that require real-time, consistent data access—particularly for applications like conversational AI, customer service chatbots, and personalization engines that depend on contextually accurate information to function effectively.

The big picture: Forrester Research identifies translytical databases as a key technology enabling modern AI applications by merging previously siloed transactional and analytical systems into a single platform.

• Traditional data architectures that separate these functions create inefficiencies and delay insights, limiting AI application performance.
• The integration of real-time processing with analytical capabilities provides AI systems with consistent, current data needed for accurate operation.

Why this matters: Translytical databases are becoming foundational infrastructure for organizations implementing advanced AI use cases that require both immediate data access and analytical depth.

• As AI applications become more sophisticated and mission-critical, the underlying data infrastructure must evolve to support both operational and intelligence needs.
• The consolidation of data platforms simplifies architecture while improving data quality and accessibility for AI systems.

Key benefits: Translytical databases offer three primary advantages for AI-powered applications beyond just providing real-time data access.

• Real-time data ensures contextual accuracy for AI agents, LLMs, and RAG systems, which is essential for applications like customer service chatbots requiring up-to-date account information.
• Optimized data integration streamlines RAG systems’ ability to pull contextual data from multiple sources, with many platforms now incorporating vector capabilities to enhance retrieval.
• Centralized data governance provides robust controls for data access and regulatory compliance, protecting sensitive information while making it available to AI systems.

Industry guidance: Forrester’s recently published Wave™ report evaluates the top 15 vendors in the translytical database market to help organizations select suitable providers.

• Organizations still using separate systems for transactional and analytical workloads should consider transitioning to translytical databases.
• The report suggests that translytical platforms can reduce AI application issues like hallucinations by ensuring data consistency, reliability, and real-time accessibility.

Reading between the lines: The rise of translytical databases signals a fundamental shift in how organizations architect their data infrastructure to support AI initiatives.

• As AI becomes more deeply integrated into business operations, the technical constraints of legacy data systems are becoming competitive disadvantages.
• Organizations that fail to modernize their data architecture may struggle to implement advanced AI use cases that their competitors can deploy.