Regatta

AI winners won't be decided by models; They'll be decided by data.

[Regatta @Regatta_Data]

Most database servers run at 25% utilization. The other 75% sits idle, reserved per node, unavailable to anyone else. RegattaDB shares peak buffer across the cluster. Same hardware, 4x the workload.
https://t.co/BuTdKlvmMr

[Regatta @Regatta_Data]

Everyone's adding "for AI" to their database tagline.

We actually rethought the database for AI and pushed out a new website to talk about it. We wrote a post about it here: https://t.co/gWfbafNwPJ

[Regatta @Regatta_Data]

Legacy data architectures can’t keep up with Agents. Replication lag. Consistency bugs. You can't optimize out of it, it's structural.

We redesigned the DB to eliminate pain. Here are 9 agent use cases that show what’s possible. https://t.co/htTNdAzjTu

#RegattaDB #AgenticAI

[Regatta @Regatta_Data]

Jensen Huang and @nvidia want $120B in new data infra for agentic AI.

The bottleneck isn't GPUs. It's databases that can't do OLTP and OLAP at the same time.

Thread on why this matters for agent systems ↓
https://t.co/lgSrPX8pS8

#AgenticAI #NVIDIA #GTC2026 @nvidia

[Regatta @Regatta_Data]

Performance numbers are easy to publish & hard to interpret. RegattaDB is efficient at scale.

This post shows TPC-C at 1.5M warehouses across a 50-node GCP cluster. We sustained over 750,000 transactions per second at 98% tpmC efficiency. https://t.co/93FYyP7YrR

[Regatta @Regatta_Data]

RegattaDB joins 20B rows across a 50‑node cluster while sustaining 50,000 serializable updates/sec, without indexes or data locality advantages.

A clear look at how OLTP and OLAP can run together in one distributed system.

Full blog post → https://t.co/W8j4aq3gAw

[Regatta @Regatta_Data]

If agents need to both think and act, they’ll need a database they can both query live data (think) AND execute transactions (act) at same time. They need complete, current business context. RegattaDB is “right” for #AgenticAI #OLTP and #OLAP

https://t.co/5G00XkkvUC

[Regatta @Regatta_Data]

The updated https://t.co/MhoHvt4Dtl is live. ✨

Check it out!

One distributed database for:

🚀 High-performance transactions

⚡️ Real-time analytics on up-to-the-second data

🛠️ Massive data ingress with Kafka

🎯 Semantic search

Ready to dive in? 👉 click “Start Coding”.

[Chad Sakac @sakacc]

Love @springboot and wanting a better database? Have a look at this blog by a colleague at @Regatta_Data: https://t.co/4wNp3iihW9

[Chris_Mellor @Chris_Mellor]

Flash-centric Regatta OLxP database working on faster access for AI agents - https://t.co/JJXghA8idx

[Regatta @Regatta_Data]

A new blog by @Regatta_Data's CTO and co-founder, @ErezWebman.

Regatta’s Architecture: A Bird’s Eye View https://t.co/H2EhnVfqXM

[Boaz Palgi @bpalgi]

@egaltheflyer knows his data products!

[Regatta @Regatta_Data]

@nodejs or @nestframework dev that is frustrated with a rigid data layer? Join episode 3 of "Getting Things Done" with Regatta - starting in 90 mins. Register here: https://t.co/9LGZZ2r0L0 @bpalgi

[Regatta @Regatta_Data]

A brief view into the Dirty Little Secrets of Scale-out Sharding.

https://t.co/CHJQSoKjWP

[Regatta @Regatta_Data]

As more and more customers are using @Regatta_Data integrations continue to accelerate. Here's a HOWTO for Python: https://t.co/A7twC8FInL and Node.js: https://t.co/FELkZr3nWN. Simple and easy. More integrations coming, stay tuned!

[Boaz Palgi @bpalgi]

We of course agree. @Regatta_Data offers the world's first scale-out OLxP database: Real-time data analytics (OLAP) on 100% up-to-data transactional (OLTP) data, at any scale, at high performance + SQL.

[Regatta @Regatta_Data]

@sakacc Wait till people see how we've done it 😉

[Chad Sakac @sakacc]

We're holding our second public Regatta webcast on June 5th, and you're invited! 😀 The first was an intro and some demos, this one is a practical hands-on tutorial for folks interested in trying out the world's first OLxP database. Register: https://t.co/4kEfFDZC1F

[Regatta @Regatta_Data]

Everything you wanted to know about Regatta (fka Paramount Data).
https://t.co/oZIdW8yyxk