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The importance of databases for modern Enterprise AI operations cannot be overestimated.
Help data to train and groundAnd multiple research reports show that without correct data AI efforts have a tendency to fail. With trends such as atmospheric coding and agent AI, it is also increasingly important to have database technology that can be spun if needed in a serious approach to modern development efforts.
In that environment it should not be a surprise that databases are a particularly valuable goods.
This weekThat fact could be seen with Databricks‘Acquisition of the private serial post -free -start startup NeonIt was founded in 2022. The deal is reportedly appreciated at a stunning $ 1 billion, which is shocking, since the company picked up $ 46 million in a financing round barely two years ago.
What is also particularly interesting is Those Databricks itself is a data supplier, with his data Lakehouse platform. At various points in the history of the company, it has positioned itself as an alternative to traditional databases, which provides a data take structure where users can do questions. So what was missing, and why had data tabricks spend a billion dollar? What does it mean and says it about what Enterprise AI really needs?
Functionally, it is all about complying with the needs of developers to build Agentic AI applications. According to Neon, more than 80% of the databases made on his platform are made by AI agents.
What is serverless Postgreesql and why does it matter?
Although Neon is a startup, the core database technology on which it is based is not new.
PostGresQL is one of the oldest and most established open-source database platforms, Dating from 1996. It is a relational database technology, which means that tables and rows have in addition to extremely stable functions that organizations have been familiar with for decades. The Core Open-source PostGresQL database is now being updated in an annual release cadence. The most recent stable update was PostGresql 17, which debuted in September 2024.
As an open-source technology, PostGresQL has enjoyed broad adoption and contributions. At a certain point it was often compared to other own relational database options, including Oracle as an alternative option. In 2025, however, PostGresql stands on its own.
DB Engines currently rank Postgresql as the fourth most popular database used today, behind Microsoft SQL Server, MySQL And Oracle. The State of PostgresQL 2024 report from TimeScale identifies the increasing fame of the open-source database as the favorite database for AI applications. The established and understood nature of the database and Wide availability is one of the many factors that make it attractive.
However, PostGresql is only the database. Performing it as a server -free range is an operational and implementation activity. The promise of each serverless database is the convenience of operations. Instead of requiring a special database implementation that is constantly performed with special sources, the demand is seriously spun when needed. It is an implementation option that is particularly attractive for developers as a way to quickly build applications. AI -based development is even more attractive because databases can be built and implemented programmatically.
The serverless Postgreesql landscape has many suppliers
Every Cloud -Hyperscaler has a form of PostgreesQL -Service and has had for years.
Google has several offers, including Alloydb, Microsoft has Azure database for PostgresQL, while AWS Amazon has RDS for Postgresql and Amazon Aurora. Each of them also has a taste of server -free offer, that is, a database that is available on request.
There are countless smaller suppliers, including timetable, EDB and Netapp Instaclustr. In fact, almost two years ago, Databricks Serveress PostGresQL supplier took over bit.io, who was also an early rival of neon.
It appears that the goals and possibilities of Bit.io are very different from neon.
“Together with the Neon team we look forward to building the most developer and AI-agent-friendly database platform,” Phil Shin, senior director of business development and companies at Databricks, told Venturebeat. “The Bit.io acquisition, on the other hand, was not actually about Postgres, but focused on developer experiences, especially in the processes and self-service process.”
Shin added that the Bit.io -acquisition had a major impact on the seamless registration experience of Databricks.
How serverless postgresql fits in the landscape of the Enterprise database
Although Neon exists for only a few years with its serverless PostgreesQL implementation, the commercial supplier EDB has been in business since 2004. EDB has a series of his own commercially supported PostgresQL offers.
Matt Yonkovit, VP of Product for Edb, Venturebeat said that Neon’s acquisition is a strong voice of trust in Postgres as a fundamental technology for AI and analysis.
“It reinforces what we have long believed: Postgres is increasingly central to modern data packs,” said Yonkovit. “Serfeless is well suited for dev/test environments and for quickly starting AI projects – but because those use cases scale, companies must have the performance, compliance and control of a sovereign platform.”
Yonkovit noted that it is seriously suitable for short bursts and smaller workload. It can be quickly up and down or completely switched off when it is inactive, which considerably lowers the costs related to calculation, electricity and storage. In his opinion, however, there are considerations.
“An important challenge with serless is that sovereign data management can become messy because you cannot determine where the data is processed, unless you have a well -limited pool of sources,” said Yonkovit.
The power of serverless Postgreesql for agent AI
Neon’s serverless PostgreesQL approach separates storage and calculations, making it developer-friendly and AI-Native. It also makes automated scaling possible and branching in an approach that is comparable to how the GIT -version management system works for code.
Amalgam Insights CEO and main analyst Hyoun Park noted that Databricks was a pioneer in the use and scaling up of AI projects.
“One of the major challenges in AI is to manage the storage and calculating that is related to the data,” Park told Venturebeat. “Each of these needs will be increasingly difficult to predict in an agent world where end user prompts and requests can quickly lead to unexpected requirements in storage or calculate to solve the problem.
Park explained that Neon’s server -free car scaling approach from PostGresQL is important for AI, because this allows agents and AI projects to grow if necessary without storing artificial linking and putting together the needs. He added that this is useful for Databricks for both agent use cases and for supporting the adapted models that they have built in recent years after the Mosaic AI acquisition.
What it means for AI leaders from Enterprise
For companies that want to lead in AI, this acquisition means a shift in infrastructure requirements for successful AI implementation.
Data is crucial for AI; That is no surprise. What is especially insightful is that the ability to spin databases quickly is essential for agent AI success. The deal validates that even advanced data companies need specialized serverless database options to support AI agents who make and manage databases programmatically.
Organizations must acknowledge that traditional database treatments can limit their AI initiatives, while flexible, directly scalable server solutions make the dynamic resource allocation possible that demand modern AI applications.
For companies that are still planning their AI route map, these acquisition companies indicate that database infrastructure decisions must give priority to serious possibilities that can quickly adapt to unpredictable AI -Desfloads. This would transform the database strategy from a technical consideration into a competitive advantage when delivering responsive, efficient AI solutions.