The importance of databases for contemporary AI operations can’t be overestimated.
Data help to coach and construct AIAnd several research reports show that the AI efforts are likely to fail without proper data. With trends akin to vibe coding and agent AI, additionally it is becoming increasingly necessary to have database technology that might be expressed as needed within the event of a serverless approach to modern development efforts.
In this environment, it shouldn’t surprise that databases are particularly precious goods.
This weekThis fact was to be seen database'Acquisition of a privately held serverless postgreSQL startups NeonWhat was founded in 2022. According to the deal, the deal is rated with astonishing $ 1 billion, which is shocking, for the reason that company collected 46 million US dollars almost two years ago in a financing round of the series B.
What can be particularly interesting is This database itself is a knowledge provider with its data -Lakehouse platform. At various points within the history of the corporate, it has positioned itself as an alternative choice to conventional databases and provided a knowledge Lake structure wherein users can querge. So what was missing and why needed to have databases? spend a billion dollars? What does and say what Enterprise Ki really needs?
Functionally, it’s about fulfilling the needs of the developers to create agents -ai applications. According to Neon, over 80% of the databases created on its platform were created by AI agents.
What is serverless postgreSQL and why is it necessary?
While Neon is a startup, the core database technology on which it relies will not be latest.
Postgresql is certainly one of the oldest and most established open source database platforms. from 1996. It is a relational database technology, ie it has tables and contours along with extremely stable functions that corporations have trusted for a long time. The Core Open Source Postgresql database is now updated in an annual release cadence. The latest stable update was PostgreSQL 17, that Debut in September 2024.
As an open source technology, PostgreSQL has a broad acceptance and contributions. At one point it was often in comparison with other proprietary relational database options, including Oracle as a substitute option. In 2025, nonetheless, Postgresql stands for itself.
DB engine currently Ranks Postgresql because the fourth hottest database that’s used today, behind Microsoft SQL Server, MySQL and oracle. The report on Postgresql 2024 of Timescale identifies the increasing awareness of the open source database as a database of selection for AI applications. The well -established and understood nature of the database A large availability is certainly one of the various aspects that make it attractive.
PostgreSQL alone, nonetheless, is simply the database. Executing as a serverless offer is an operating and provision activity. The promise of a serverless database is straightforward operation. Instead of requiring a dedicated database provision that’s repeatedly carried out with dedicated resources, server is expressed if essential. This is a provision option that is especially attractive for developers to quickly create applications. The AI-based development is much more appealing, since databases might be created and provided program-controlled.
The serverless PostgreSQL landscape has many providers
Each cloud hyperscaler has a type of the PostgreSQL service and for years.
Google has several offers, including AlloydB, Microsoft, has an Azure database for PostgreSQL, while AWS Amazon RDS for PostgreSQL and Amazon Aurora has. Each of them also offered a certain taste of serverless, ie a database that is offered on need.
There are quite a few smaller providers, including time scale, EDB and NetApp Installust. In fact, databases received serverless postgresql providers almost two years ago bit.io, That was also an early rival from Neon.
As it seems, Bit.io's goals and skills differ from neon.
“Together with the neon team, we look ahead to constructing essentially the most developers and AI-agent-friendly database platform,” Phil Shin, Senior Director of Corporate Development and Ventures at DataBricks, told Venturebeat. “In contrast, the Bit.io acquisition was probably not about postgren, but about developer experiences, especially within the experiments and the self-service process.”
Shin added that the acquisition of Bit.io had a serious impact on the seamless registration of Databricks.
How serverless PostgreSQL matches into the Enterprise database landscape
While Neon has only been giving its serverless PostgreSQL implementation for several years, the industrial provider of EDB has been in business since 2004. EDB has plenty of his own commercially supported PostgreSQL offers.
Matt Yonkovit, VP of products for EDB, EDB, said Venturebeat that the acquisition of neon is a powerful vote of trust in postgres as a basic technology for AI and evaluation.
“It increases what now we have believed in an extended time: Postgre is increasingly central to modern data stacks,” said Yonkovit. “Serleless matches perfectly with DEV/Test environments and for quick start of AI projects -but as these applications, corporations need the performance, compliance and control of a sovereign platform.”
Yonkovit found that serverless is well fitted to short burdens and smaller workloads. It can quickly be scaled up and down or switched off completely in idling, which significantly reduces the prices related to calculation, electricity and storage. In his view, nonetheless, there are compromises.
“A major challenge for serverless is that the sovereign data management can turn into messy because you can not control where the info is processed, unless you’ve got a well -limited resource pool,” said Yonkovit.
The performance of serverless postgreSQL for Agentic Ai
The serverless postgreSQL approach from Neon separates memory and calculation, which makes it developer friendliness and ai-native company. It also enables automated scaling and branching in an approach that is comparable to the functionality of the GIT version control system for code.
The CEO and chief analyst from Amalgam Insights, Hyoun Park, found that databases were a pioneer for the availability and scaling of AI projects.
“One of the most important challenges within the AI is the management of the storage and calculation connected to the info,” Park told Venturebeat. “Each of those needs shall be predicted in an acting world wherein end users demand, and inquiries may quickly predict unexpected requirements for storing or calculating the issue.
Park explained that the serverless autoscaling approach from Neon for PostgreSQL is significant for AI, since agents and AI projects can grow as needed without artificial storage and calculation being linked and calculated. He added that this is beneficial for databases for each agent use cases and for the support of the user -defined models, which they’ve built up lately in keeping with their mosaic -KI acquisition.
What it means for company leaders for corporations
For corporations which can be the pioneer in AI, this acquisition signals a shift in infrastructure requirements for successful AI implementation.
Data is of crucial importance for AI. This isn’t any surprise. However, it is especially revealing that the power to quickly spin databases is of essential importance for the success of the agent -KI. The deal confirms that even expanded data corporations need special serverless database functions to support AI agents that create and manage databases programmatically.
Organizations should recognize that traditional database approaches can restrict their AI initiatives, while flexible, immediately scalable serverless solutions enable the dynamic resource project that require modern AI applications.
For corporations which can be still planning their AI roadmap, this acquisition signals that the choices for database infrastructure should prioritize the serverless functions that may quickly adapt to unpredictable AI workloads. This would change the database strategy from a technical consideration to a competitive advantage when providing response -fast and efficient AI solutions.
