The AI ​​Revolution: Agent AI, Serverless Postgres, and Databricks Paving the Way

Building the future of AI! What are Agent AI, Serverless Postgres, and Databricks? A comprehensive guide for beginners

Hello, I'm John, your AI technology expert! Have you been hearing more and more about "agent AI," "serverless Postgres," and "Databricks" lately? They may sound difficult, but they're actually very exciting technologies that have the potential to change our future. In particular, there was big news recently that Databricks, a giant in AI and data analytics, will acquire Neon, a rising star in serverless Postgres. What does this mean, and how will these technologies work together to lead to a future where "AI creates AI"? Today, I'll explain it in detail, in an easy-to-understand way even for beginners!

Introduction: A future where AI agents play an active role and the new technologies that will support it

AI technology is evolving day by day and is poised to fundamentally change the way we live and work.Agent AI" This is an AI that can handle complex tasks, just like a butler who can think and act autonomously. For this agent AI to be truly effective, an IT platform that can instantly process huge amounts of data and respond flexibly is essential. This is where "Serverless Postgres" and " , which integrates new database technologies to accelerate AI development.Databricks" It's a platform like this. Let's take a look at what's happening at the forefront of AI development with these three keywords as the axis!

Basic Information: What is Agent AI, Serverless Postgres, and Databricks?

First, let's start by understanding the basics of what each technology is.

What is Agent AI?

What is Agent AI?An AI system capable of setting goals, making plans, acting, and learning on its ownThis is what we mean. While conventional AI is a "tool" that performs tasks based on specific instructions, Agent AI aims to be more proactive and behave like a human. For example, if you ask "Make the best plan for my trip to Okinawa next week and make reservations," it will autonomously handle everything from selecting and booking flights, hotels, rental cars, and tourist spots. This is expected to allow humans to focus on more creative activities.

The problem this solves isAutomating complex, multi-step tasksIn conventional workflows, human judgment and operation were required at each step, but Agent AI seamlessly connects these steps, achieving significant efficiency improvements.

What is Serverless Postgres?

Postgres (officially known as PostgreSQL) is a very popular open source relational database. And "serverless" means:Developers do not need to be concerned with server management and operationIn other words, Serverless Postgres is a highly efficient database service that has the powerful features of PostgreSQL, but automatically allocates resources (computing power and storage capacity) only when and as needed, and you only pay for what you use.

The problems this solves are particularly problematic for agent AI.The complexity and cost of managing databases for applications with unpredictable access patternsIn the past, it was necessary to always have a large server ready to handle peak access, but with serverless there is no waste. You can instantly scale up (increase capacity) when needed, and scale down or even to zero (zero resource consumption) when not needed.

What is Databricks?

DatabricksA company that provides a platform that comprehensively supports data engineering, data science, machine learning, and AI developmentAs they call themselves a "data and AI company," they provide a one-stop shop for tools and services to build innovative AI applications by leveraging the vast amounts of data that companies hold. Their platform is called the "Data Intelligence Platform" and covers the entire life cycle of AI development, from data collection, analysis, and training to deployment of AI models.

Main topic: Databricks' shocking acquisition of Neon

And what happened at the intersection of these technologies was the "Databricks agrees to acquire Neon" Neon is a leading company in this "serverless Postgres" technology. This acquisition is seen as a strategic move by Databricks to strengthen its foundation for agent AI development and enable developers to build AI agents more quickly and efficiently. This news has become a hot topic in the AI ​​industry, especially among those involved in data infrastructure.

Why it matters: Why "Serverless Postgres" is the key to developing agent AI

So why is Databricks acquiring Neon and integrating serverless Postgres into its platform? It has to do with the nature of agent AI.

• Speed ​​and flexibility to meet the exploding demands of agent AI: To process tasks, agent AI frequently accesses the database to search for information and store intermediate results. Moreover, in many cases, these processes may be performed in a very short time and simultaneously by many agents. With conventional databases, it can take several minutes to start up a new database instance (individual database environment), which becomes a bottleneck (a point of processing delay) that significantly slows down the response speed of agent AI. Neon's serverless PostgresYou can spin up a new database instance in under 500 milliseconds (0.5 seconds!)This allows it to keep up with the "agentic speed" of agent AI.
• Cost-effective (Pay-as-you-go): The database usage of agent AI is very volatile. At times there may be a large amount of access, and at other times there may be almost no access. Serverless architecture isPay-as-you-go: You only pay for the resources you useThis allows companies to optimize infrastructure costs and reduce unnecessary spending, especially for agent AI workloads that spin up and shut down many ephemeral databases quickly.
• Simplified development and scalability: Serverless Postgres like Neon uses an architecture that separates storage (where data is stored) and compute (computing power). This greatly simplifies infrastructure management by eliminating the need for developers to scale storage and compute separately and simultaneously. It also allows for instantaneous creation of separate database copies per agent, accelerating experimentation and development while preventing performance bottlenecks.

Databricks CEO Ali Ghotshi also stated, "By incorporating Neon into Databricks, we provide developers with serverless Postgres that can handle agent-like speeds, the economics of pay-per-use, and the openness of the Postgres community." This is truly an essential database infrastructure in the era of agent AI.

Technical details: how does it work?

Let's take a closer look at how these technologies work together.

Behind the Scenes of Agent AI in Action

When an agent AI performs a task, it often goes through the following steps:

1. Understanding goals and planning: Interprets given instructions and goals and plans steps to achieve them.
2. Information gathering: Information required for executing the plan is collected from websites, internal databases, documents, etc. During this process, database access occurs frequently.
3. Tool usage: Tasks are accomplished using a variety of tools, including calculations, calling external APIs (a mechanism for calling functions in other software), and code execution.
4. State management and learning: It remembers the current progress and the information gained (often stored in a database), evaluates the results, and improves the next action.

During this process, particularly in "information gathering" and "state management," fast and flexible database access is required. When multiple agents work in their own contexts, they each need an independent, yet quickly available, database environment.

Strengths of Neon’s Serverless Postgres Architecture

The reason Neon's technology is well suited for agent AI is its unique architecture.

• Separation of storage and compute: In traditional databases, the storage in which data is stored and the compute (CPU and memory) that processes that data are tightly coupled. Neon separates these and allows each to be scaled independently. This allows for flexible response, for example, when you want to increase only the computational processing or only the data storage capacity.
• Branching: Just like in Git (a version control system), you can easily "branch" the state of your database. This makes it easy to test new features on a copy of your data without affecting your production environment, or have different agents work on different data sets. And this branching happens almost instantly.
• Instant instantiation: As mentioned before, a new Postgres instance can be spun up in under half a second. This is extremely powerful when your agent AI needs temporary databases for each task. Neon's internal data shows that 0.5% of databases on the Neon platform are created automatically by AI agents, not by humans. That's an amazing number!
• Scale-to-zero: When idle, computing resources scale down to zero to minimize costs, and when agents resume activity, resources are instantly allocated.

Integration with Databricks Data Intelligence Platform

By integrating Neon’s powerful serverless Postgres architecture into the Databricks Data Intelligence Platform, developers can benefit from:

• Accelerating AI agent development: The combination of Databricks' AI model development tools (such as MosaicML technology) and Neon's fast database provisioning makes it much faster to go from idea to working AI agents.
• Seamless Data Integration: Open data lakehouse formats (structures for efficiently managing and analyzing large amounts of diverse data) such as Delta Lake and Apache Iceberg, promoted by Databricks, will be more closely integrated with Postgres, which handles transactional data (such as frequently updated business data), making it easier for AI agents to access all the data they need.
• Eliminate performance bottlenecks: Neon's technology efficiently handles the large number of database requests generated by AI agents, maintaining overall system performance.

Indeed, a next-generation application development environment in which "AI builds AI" is becoming a reality.

Development team and community: reliability and vitality

Databricks: A leading data and AI company

Databricks was founded by some of the original developers of Apache Spark (a large-scale data processing framework) and has a long history and a strong reputation in the data and AI fields, and has been strengthening its platform through strategic acquisitions.

• 2023: Acquires MosaicML (approximately $13 billion): An open source large-scale language model (LLM) learning platform that empowers enterprises to build their own generative AI models.
• 2024: Acquire Tabular ($10 billion+): The data storage company that led the development of the Apache Iceberg format, demonstrating its commitment to open data formats.

These acquisitions demonstrate Databricks' clear vision to build a comprehensive platform for AI development, and the Neon acquisition is part of this strategy.

Neon: A revolutionary serverless Postgres engine

Neon is a relatively new company that went public in 2022, but has grown rapidly and gained a reputation in the developer community for its innovative architecture. Their founding team says they aimed to "disrupt the database industry" and fundamentally rethought Postgres for the modern cloud-native era. Rather than simply providing a Postgres wrapper or managed hosting, Neon was an ambitious effort to separate storage and compute and introduce a branchable, version-controlled storage system. Its customer list includes leading technology companies such as Replit, Retool, Vercel, and Cloudflare.

Open source aspects and future expectations

Neon's platform is100% Postgres compatibleMany common extensions work as is. In addition, some parts are provided under the Apache 2.0 license (a very liberal open source license), and they also value cooperation with the open source community. This openness is expected to be maintained even after the acquisition by Databricks. This will allow developers to continue to benefit from the extensive Postgres ecosystem (related tools and communities) without being locked in to a specific vendor.

Use cases and future prospects: What does the future hold?

How will the combination of Databricks and Neon change AI development?

• Accelerating AI development with AI (AI building AI): AI agents will automatically generate database instances and execute tasks, bringing us to a future where the development process itself will be made more efficient by AI.
• Real-time decision support: Developing advanced AI applications that process and analyze large amounts of data in real time to support business decision-making.
• Improving your personalized experience: An AI agent that provides more detailed and personalized services and information tailored to the behavior and preferences of each individual user.
• Improving R&D efficiency: In fields such as scientific research and drug discovery, AI agents will support complex simulations and data analysis, speeding up discovery.
• Transforming the Database Industry: As Neon's founding team envisioned, this could fundamentally change the way traditional databases work, making more flexible and cost-effective data management the norm.

We expect to see an increasing number of tools and services added to the Databricks platform to help realize these use cases.

Comparison with competitors: What makes Databricks + Neon different?

The AI ​​data infrastructure market is highly competitive, but this acquisition gives Databricks several advantages.

• Versus Traditional Database Systems: Traditional database systems can have difficulty keeping up with dynamic, scalable workloads like agent AI, and Neon's serverless architecture has a distinct advantage in this regard.
• Versus competitors like Snowflake: Scott Bickley of Info-Tech Research Group points out that "this move allows Databricks to strengthen its AI infrastructure capabilities, particularly in areas such as AI-driven database provisioning and AI agent development, which are notable gaps currently lacking in competitor Snowflake." In other words, integrating database capabilities specific to agent AI could put Databricks ahead of its competitors.
• Strengths of an integrated platform: Databricks provides a platform that can handle everything from data ingestion to analysis, model development, and deployment. The addition of Neon's technology to this platform will further seamlessly integrate the elements necessary for AI agent development, allowing developers to focus on more essential tasks.

Robert Kramer of Moor Insights and Strategy noted that "Neon's serverless Postgres model, when integrated with the Databricks platform, provides instant provisioning, compute and storage decoupling, and API-first management, enabling organizations to reduce infrastructure costs, shorten deployment cycles, and improve experimentation without disrupting production."

Risks and Cautions: What you need to know

It's a great technology, but there are some precautions to take into account when implementing it.

• Integration with existing systems: Integrating the Neon model into existing legacy systems and rethinking database governance to fit an agent-driven architecture takes time and careful planning.
• The importance of cost control: Pay-per-use is efficient, but if not properly managed and monitored, it can lead to unexpected high bills. Scott Bickley warns that "while consumption-based subscription models can offer cost efficiencies, if not properly managed or contract structures are inappropriate, they can put a strain on a company's budget with uncontrollable costs." However, Neon's "scale to zero" feature is said to help with cost management.
• Market differentiation and reliability: The AI ​​data infrastructure market is highly competitive, and Databricks needs to prove that Neon's technology can scale, be integrated into enterprise environments, and gain a proven track record.
• Absorbing technology and maintaining an open source culture: It is important to the community that the Neon team and technology are smoothly integrated into Databricks and that the open source culture and Apache 2.0 license that Neon has cultivated are respected.

"The real test will be whether customers can effectively leverage these new capabilities at scale without introducing additional complexity," said Robert Kramer.

Expert opinion and analysis: What do the experts think?

Experts have generally expressed a positive view of this acquisition and technology combination.

Info-Tech Research GroupScott Bickley"Databricks has been aggressive in acquiring companies that accelerate its core technology platform," he said, citing MosaicML's generative AI model building capabilities and its integration with Apache Iceberg/Delta Lake formats as strong enhancements. "This acquisition enhances Databrick's comprehensive capabilities and provides buyers with a streamlined vendor option in the data management space as they build out their data management suite. Introducing best-in-class serverless database capabilities and expanding their use via AI agents is what sets Databricks apart right now," he concluded.

Moor Insights and StrategyRobert Kramer"Traditional database systems cannot handle the scale and variability of agent-driven architectures, where thousands of ephemeral databases are quickly launched and shut down," they point out, acknowledging that Neon's technology can solve this challenge, but adding that "Neon needs to reliably scale, integrate with enterprise environments, and prove its track record."

Latest News and Roadmap: What's Next for Databricks

The biggest news at the moment isDatabricks agrees to acquire Neon(Announced on May 2025, 5). Once this transaction is completed, many of the Neon team will join Databricks. The following points are noteworthy in the future roadmap:

• Neon technology is fully integrated into the Databricks Platform: How serverless Postgres capabilities are integrated with Databricks services and provided to users.
• Enhancements to AI agent development tools: Introducing a more advanced and easy-to-use AI agent development tool that utilizes Neon's database functions.
• Synergy with MosaicML and Tabular technologies: What new value will be created by combining the technologies acquired through previous acquisitions with Neon's technology?
• Continuing to collaborate with the open source community: How can we contribute to the community while maintaining the openness of Postgres?

Databricks continues to evolve from a data lakehouse pioneer to a full-stack platform for AI development, and this acquisition will further accelerate that strategy.

FAQ: Frequently Asked Questions

Q1: What exactly can agent AI do?

A1: For example, they are expected to perform a wide range of tasks autonomously, such as proposing and booking travel plans for individuals, analyzing complex market data to develop investment strategies, and automatically generating software code. They will have the ability to understand human instructions, make plans, use multiple tools, and learn and improve.

Q2: What is “less” about serverless?

A2: It means that developers do not need to be aware of management tasks such as provisioning, maintenance, and scaling of physical and virtual servers. Cloud providers handle these tasks automatically in the background, so developers can focus on writing application code.

Q3: Why did Databricks acquire Neon?

A3: The main purpose is to strengthen the fast and scalable database infrastructure required for agent AI development. Neon's serverless Postgres technology meets the needs of AI agents, such as "instant database startup," "elastic scaling," and "cost efficiency," and is expected to significantly strengthen Databricks' AI platform.

Q4: What benefits does this technology bring to us developers?

A4: It will enable you to develop and deploy advanced applications such as AI agents more quickly and at lower cost. It will free you from the complexities of database management, allowing you to focus on innovation without worrying about infrastructure. And because it is based on the proven open source database Postgres, it will be easier to use your existing knowledge and tools.

Q5: Is Neon technology open source?

A5: Part of Neon's core technology is open source under the Apache 2.0 license and is 100% Postgres compatible. This open aspect is expected to be maintained after the acquisition by Databricks, but some parts may be offered as commercial products, such as managed services.

Conclusion: Don't miss out on the new wave of AI development

This time, we have explained the very important keywords in shaping the future of AI: "agent AI," "serverless Postgres," and "Databricks," as well as the major movements at their intersection. Databricks' acquisition of Neon will accelerate the arrival of an era in which AI can perform more autonomously and more advanced tasks. These technologies represent both new challenges and great opportunities for developers.

Of course, with any new technology there are always unknowns and things to be careful about. But the potential is immeasurable. We'll have to keep an eye on developments in this field!

I hope this article will help you deepen your understanding of AI technology. Technology is evolving quickly, but make sure you have a firm grasp of the basics so you don't get left behind in the new wave!

Disclaimer:This article is for informational purposes only and does not recommend investing in any particular product or service. Any technology adoption or investment decisions should be made at your own discretion and risk.

Related links collection

• Databricks official website
• Neon official website
• Databricks acquisition of Neon press release
• Neon blog post: Neon and Databricks

Agent AI, Serverless Postgres, Databricks, Neon, AI Development