dbInsights

In 2024, the elephant in the room was how generative artificial intelligence seized the conversation. In 2025, the dialog shifted to agents and the question of whether there’s an AI bubble happening in our midst. But as we noted, AI’s taking of the limelight shined a new spotlight on the importance of having good data, and so last year, we forecast that data would have a renaissance.

With Q2 ending in a whirlwind, we’re unleashing a monster: our biggest research drop ever covering Databricks, Google, IBM, Oracle, SAP, and Snowflake. Agents headlined. But up there was Data for AI: It needs the right data & the lakehouse is emerging as the nexus for analytics & AI. Now let’s dive in. Data reclaimed the spotlight at Databricks, which unveiled its agentic dev framework last year. The headline was acquisition of Neon, a PostgreSQL database, leading to release of v1 of Lakebase.

It’s time once more for the annual sticking out of our neck ritual where we predict will happen in the year ahead for data. The verdict? 2025 will be the year of The Renaissance of Data. But this data “boom” will be different from that of the Big Data 2010s.

It’s time for another quarterly research drop. Here’s what we’ve been working on in Q4. Of course, being the end of the year, the coda where it all comes together is AWS Re:Invent. But there’s more. We’re releasing our takeaways from AWS, IBM, Oracle, Teradata, and probably the most established database player you’re never heard of, InterSystems.

Time for another quarterly research drop from a busy spring conference season. We're releasing our takeaways from Databricks, Google, IBM, Oracle, and Snowflake with the meta themes being AI (of course), multicloud, data sharing, and chess moves in the data landscape. Databricks turns the Lakehouse tablesFor attention-grabbers, there was Databricks' bombshell acquisition of Tabular (now part of Databricks) that dropped right as Benoit Dageville was firing up his SnowflakeSummit2024 keynote.

Digesting our thoughts on the flight back from Amazon Web Services (AWS) hashtag#reinvent24, one of our first impressions was that Matt Garman's keynote did not start with all AI all the time, but began with the infrastructure and data that must support it. Yes, AWS is upping its game in hashtag#genAI foundation models with Nova, which Garman said was such a major step beyond Titan that it merited a new identity.

The year ends now. We and only about 50,000 of our closest friends are about to hop the plane for Amazon Web Services (AWS) hashtag#reInvent2024 tomorrow. With AWS kicking in another $4 billion to Anthropic, there's little doubt that we'll be hearing lots about hashtag#genAI and agents. And we're likely wondering what we're going to be hearing about multicloud and, in an era where national borders are hardening, sovereign cloud. What other themes are we going to hearing about?

At the beginning of last year, who knew that Generative AI (Gen AI) and ChatGPT would seize the moment? A year ago, we forecast that data, analytics, and AI providers would finally get around to simplifying and rethinking the Modern Data Stack, a topic that's been near and dear to us for a while. There was also much discussion and angst over data mesh as the answer to data governance in a distributed enterprise. We also forecast the rise of data lakehouses.

By Tony Baer, dbinsight and Merv Adrian, IT Market Strategy It’s been barely six months since IBM unveiled the new watsonx family of products targeting enterprise clients, AI builders, data scientists, and data professionals.

What a difference a year makes. At the beginning of the year, if you asked anyone outside the AI research community about Generative AI, you would have gotten a blank stare. Our first quarter briefings with data and analytics vendors barely made notice of Large Language Models (LLMs) or vector storage. But in the meantime, ChatGPT, unleashed by OpenAI late last year, gradually became viral.