Artificial intelligence is a popular topic right now across organizations and industries. And it’s more than just a hot buzzword. According to Gartner’s recent research, 55% of organizations are in piloting or production mode with generative AI, and more than half have increased their generative AI investment in the last 10 months.
It’s clear that building AI applications is a priority for companies today. But before creating and launching AI applications, organizations need to step back and look at where and how all their data is being stored.
In other words, it’s the hour of the database.
AI workloads are data workloads. They start with data, run on data, and produce data. So it only makes sense that achieving enterprise-level results for your AI projects calls for storing your data in an enterprise data management environment.
This even applies to chatbots. Called the John Doe of generative AI applications, chatbots use conversational AI techniques to interact with users, and it seems like practically every company has one. But what happens when a chatbot becomes successful, and even mission critical for a business?
In order to support chatbots and other AI applications for the long term, a plan for operationalizing sustainability is needed, with an enterprise-level database. But not just any database will do.
These are table stakes for enterprise solutions:
- Always on architecture with in-place updates and no planned downtime
- Responsive nature with SLAs for interactive queries and automatic index maintenance
- A dynamic ecosystem with stable, well established APIs and a large, vital user community
- High availability, data redundancy, and SLAs for recovery point and recovery time objective
- Scalability with flexible scale-up and -out capabilities
- Ability to integrate with existing business data and perform hybrid searches
- Built-in security with state-of-the-art authentication methods, data encryption and data governance
- Enterprise support with first response time and turnaround time SLAs
- The ability for business transactions to be digested in real time
Hear from our experts at Postgres Conference 2024
Used and trusted by developers more than any other database, EDB Postgres meets all these requirements and more. It’s the ideal database for mission-critical enterprise AI workloads. Coming up on April 19, Patrick Mottram, EDB’s VP of Product Management for Analytics and AI, will delve into the use of EDB Postgres for AI applications during his talk at the Postgres Conference 2024 in San Jose.
Along with all the intelligent features already built into Postgres, there are over 1,000 extensions available today that can be added to deliver additional capabilities for your AI applications, from handling geospatial data to transforming PostgreSQL to a vector database and more. If the extension isn’t available, it can be created and added due to Postgres’ open source architecture.
With continuous innovation, community-driven enhancements like pgvector, high availability, dedicated enterprise support and more, Postgres and EDB are ready for the future of AI applications. We can help ensure you’re ready, too.
Heading to Postgres Conference 2024? We would love to see you there.
Talk to an EDB expert about using Postgres for your AI projects