# RegattaDB - The Database for Agentic AI

> RegattaDB is the database built specifically for AI agents. It converges transactional processing (OLTP), analytical queries (OLAP), and vector search into a single engine - a category RegattaDB calls OLxP - so agents can transact, analyze, and reason over meaning simultaneously, on live data, with serializable consistency at fleet scale. No ETL pipelines. No replication lag. No fragmented stack.

The full text of every RegattaDB article is available in a single file at https://regatta.dev/llms-full.txt

## The problem RegattaDB solves

AI agents are a fundamentally different class of database workload. Unlike humans making occasional queries, agents operate at massive concurrency - hundreds or thousands of instances reading, writing, and reasoning simultaneously. They require three things at once that no conventional database architecture provides together:

1. Live transactional state (OLTP) - agents need to know what is happening right now, not what happened before a pipeline ran
2. Real-time analytical patterns (OLAP) - agents need to reason over historical data without waiting for data to land in a separate warehouse
3. Semantic meaning (Vector) - agents need to understand context and similarity, not just match on exact values

RegattaDB eliminates this architecture entirely. OLTP, OLAP, and vector search run in a single engine against the same live data, in the same transaction, with no pipelines connecting separate systems.

## Key performance benchmarks

- 750,000+ TPS at 98% tpmC efficiency across a 50-node GCP cluster at 1.5 million TPC-C warehouses.
- 20 billion row JOIN plus 50,000 ACID-compliant writes per second against the same data.
- 3-4x infrastructure density by sharing compute across OLTP, OLAP, and vector workloads.
- 50-70% infrastructure footprint reduction, 50-60% license cost reduction, and 25-50% operational overhead reduction versus fragmented stacks.

## Technical capabilities

- OLTP: serializable consistency across thousands of concurrent agents with no eventual consistency tradeoffs
- OLAP: real-time analytical queries over live operational data, no replication lag, no batch delay
- Vector search: first-class semantic search natively in the core engine, not a bolt-on or extension
- MCP support: native integration with any MCP-compatible AI agent
- Natural language queries: people and agents can query live data in natural language through the native MCP server
- PostgreSQL compatible: works with existing Postgres drivers, ORMs, and tooling
- Linear horizontal scale: add nodes without changing the application architecture
- Fast ingest: massive data ingress runs concurrently with live transactions and analytics

## Website

- Homepage: https://regatta.dev
- Use cases and workloads: https://regatta.dev/use-cases
- About the company and team: https://regatta.dev/about-us
- Talk to the team / demo requests: https://regatta.dev/contact-us
- Start a free Regatta Cloud account: https://regatta.dev/get-started
- Blog: https://regatta.dev/blog
- Resources: https://regatta.dev/resources
- Press and analyst coverage: https://regatta.dev/press-analysts

## Documentation

- Documentation home: https://docs.regatta.dev/home
- Quickstart: https://docs.regatta.dev/getting-started/getting-started-using-regatta-cloud
- Drivers and clients: https://docs.regatta.dev/drivers-and-clients/connecting-applications-to-regatta
- Regatta Cloud: https://docs.regatta.dev/regatta-cloud/regatta-cloud/regatta-cloud
- SQL reference: https://docs.regatta.dev/sql/introduction
- Tuning performance: https://docs.regatta.dev/tuning-performance/introduction/introduction
- MCP endpoint for AI agents: https://docs.regatta.dev/mcp

## Site pages

- About Us - We are a team of storage, database and distributed systems veterans who've spent careers building infrastructure that powers the world's...: https://regatta.dev/about-us
- Connectors - RegattaDB integrates with popular programming languages, frameworks, and data platforms, making it easy to connect your applications and workflows.: https://regatta.dev/connectors
- Contact us - Submit your details and our team will get back to you. Contact us: https://regatta.dev/contact-us
- RegattaDB Developer License Agreement - IMPORTANT – READ CAREFULLY BEFORE DOWNLOADING, INSTALLING OR USING REGATTADB (THE “SOFTWARE”). NOTE THE TERM “SOFTWARE” AS USED HEREIN SHALL...: https://regatta.dev/dla
- Regatta End-User License Agreement - IMPORTANT – READ CAREFULLY BEFORE DOWNLOADING, INSTALLING OR USING THE REGATTA DATABASE SOFTWARE (THE “SOFTWARE“). NOTE THE TERM “SOFTWARE” AS...: https://regatta.dev/eula
- Get Started for [[Free]] - Please send us a message and our team will get back to you.: https://regatta.dev/get-started
- Regatta 2026 Homepage - The distributed database for high-performance transactional, analytical, and agentic AI workloads.: https://regatta.dev/
- Press & Analysts - RegattaDB press coverage and analyst reports on its scale-out architecture and unified OLTP, OLAP, and vector database for AI agents.: https://regatta.dev/press-analysts
- Privacy Policy - This privacy policy describes how we, at Regatta (“Regatta”, “we”, “our” or “us”), collect and process personal information related to...: https://regatta.dev/privacy-policy
- Terms of Service - We, Regatta (“Regatta”, “we”, “our”, “us”), own and operate the Regatta website available at: (“Website”). Please read carefully the following...: https://regatta.dev/terms-of-service
- Use Cases - Workloads where OLTP, OLAP, and vector must operate together within a single transaction or agent loop. Separating them across systems...: https://regatta.dev/use-cases

## Blog posts

- When Rows Outgrow the Page: RegattaDB vs. PostgreSQL TOAST - TL;DR Agentic AI workloads often push row size and update volume into this territory as a matter of course. That's where slotted pages start...: https://regatta.dev/blog/pvr-toast
- Under the Hood of RegattaDB's Vector Index - Retrieval-augmented generation (RAG), recommendation engines, image matchers, and semantic search all use a vector database to identify similarity in a high-dimensional space. To do...: https://regatta.dev/blog/under-the-hood-of-regatta-s-vector-index
- Databricks LTAP Revisited: The Compute Cost of Bridging Two Engines - A few weeks ago we published an analysis of Databricks LTAP and the architectural questions it left open. One question in particular stood out:...: https://regatta.dev/blog/databricks-ltap-union-read-compute-cost
- Press Release: RegattaDB Launches as the Database Built for AI Agents - RegattaDB Launches as the Database Built for AI Agents — Unifying OLTP, OLAP, and Vectors RegattaDB unifies transactions, analytics, and vector search in one...: https://regatta.dev/blog/press-release-regattadb-launches-as-the-database-built-for-ai-agents
- Databricks LTAP and the Unfinished Problem of Unified Data - Databricks made a significant announcement at Data + AI Summit this week. LTAP, or Lake Transactional/Analytical Processing, is their answer to a problem the...: https://regatta.dev/blog/databricks-ltap-storage-unification-is-not-enough
- We Rebuilt Our Website, Because We Rethought the Database - Things are moving fast. The market has shifted from "should we build agents" to "we are building and will need to deploy them at...: https://regatta.dev/blog/new-database-new-website
- The Case for a Single, Distributed Database Under Growing Infrastructure Constraints - TL;DR - RegattaDB runs four applications on the hardware you'd normally use for one, without pipelines, without extra licenses, and without replacing what you...: https://regatta.dev/blog/database-infrastructure-efficiency-ai-workloads
- What workloads can you converge with RegattaDB? - The legacy data stack can’t keep up Databases are architected for one thing. You pick Postgres for transactions, Snowflake for analytics, Pinecone for vector...: https://regatta.dev/blog/converged-workloads-regattadb
- NVIDIA’s Agentic Era: The Bottleneck Isn't GPUs, It’s Your Database - SUMMARY: The Shift to Agentic AI is real: Moving beyond basic LLMs, the Agentic Era focuses on AI systems that can reason, coordinate, and...: https://regatta.dev/blog/nvidia-s-agentic-era-the-bottleneck-isn-t-gpus-it-s-your-database
- RegattaDB TPC-C Benchmark: 750,000 TPS - This post documents a TPC-C benchmark for RegattaDB at 1.5 million warehouses across 50 GCP nodes, sustaining over 750,000 transactions per second at 98%...: https://regatta.dev/blog/regattadb-tpc-c-benchmark-750k-tps-1-5m-warehouses
- File under “now possible”: A 20B row JOIN and 50,000 UPDATES/second in a single distributed database - Distributed joins are among the most demanding operations in large‑scale data systems. Trying to do this at the same time as transactions are being...: https://regatta.dev/blog/20b-row-join
- The Shift to Agentic AI and a Modern Database - Agents need to both think and act The core objective of Agentic AI is to deliver systems capable of executing functions that are generally...: https://regatta.dev/blog/the-shift-to-agentic-ai-and-a-modern-database
- RegattaDB: Concurrency Control - Serializable Isolation Without Locks, Snapshots or Clock Sync - Introduction In this post, we’ll cover how RegattaDB’s concurrency-control protocols (CCPs) enable full serializable isolation in a distributed database — without distributed locks, without...: https://regatta.dev/blog/regattadb-concurrency-control-serializable-isolation-without-locks-snapshots-or-clock-sync
- Connect Your Spring Boot Application to Regatta - In this tutorial, we'll show you just how simple it is to deploy a Spring Boot application that interacts with Regatta using JDBC. By...: https://regatta.dev/blog/connect-your-spring-boot-application-to-regatta
- Regatta’s Architecture: A Bird’s Eye View - In this blog I will provide a high level overview of Regatta’s design and architectural principles. While I keep this introduction still relatively high-level,...: https://regatta.dev/blog/regatta-s-architecture-a-bird-s-eye-view
- Sharding - some dirty little secrets - A few years ago, Erez Webman and I wrote a white paper describing the dirty little secrets of scale-out sharding. Scale-out sharding as a...: https://regatta.dev/blog/sharding-some-dirty-little-secrets
- Simple beats complex – more detail - While feature-rich, scale-out products may sound complex to manage, when designed right and with architectural simplicity at the core - the opposite is true....: https://regatta.dev/blog/simple-beats-complex-more-detail
- Regatta linear scaling & no-compromise ACID in more detail - Regatta clusters scale from a single node to tens of thousands of nodes with hundreds of petabytes of data. Unlike traditional scale-out sharding, all...: https://regatta.dev/blog/regatta-linear-scaling-and-no-compromise-acid-in-more-detail

## Resources

- Private Company Spotlight (Whitepapers) - Published by William Blair’s Technology Group and built around a Q&A with Regatta Data's cofounder and CEO Boaz Palgi, this...: https://regatta.dev/resources/whitepapers/private-company-spotlight-william-blair
- Real-Time Stock Trading Analytics Demo with AI Agent (Demos) - This demo shows a real-time stock trading platform on a 10-node RegattaDB system. Trading applications stream millions of transactions while...: https://regatta.dev/resources/demos/real-time-stock-trading-analytics-demo-with-ai-agent
- Dirty Secrets of Sharding Whitepaper (Whitepapers) - Sharding single-node databases has trade-offs, often breaking developer expectations around ACID. This adds complexity to application code, forcing developers to...: https://regatta.dev/resources/whitepapers/dirty-secrets-of-sharding-whitepaper
- Creating a Table and Inserting Data (How-To) - A quick example on how to create a table in Regatta and insert data.: https://regatta.dev/resources/how-to/creating-a-table-and-inserting-data
- Creating a Regatta Cluster (How-To) - Create a Regatta database using Regatta Cloud.: https://regatta.dev/resources/how-to/creating-a-regatta-cluster
- CRUD Operations (How-To) - Simple select, update and delete in a Regatta Database.: https://regatta.dev/resources/how-to/crud-operations
- Linear Scaling Demo (Demos) - A simple demonstration of the Regatta performance linear scaling.: https://regatta.dev/resources/demos/linear-scaling-demo
- Python Integration with Regatta (How-To) - Example on deploying and using a Python driver.: https://regatta.dev/resources/how-to/python-integration-with-regatta
- Node.js Integration with Regatta (How-To) - Learn how to deploy and use a Node.js driver with Regatta: https://regatta.dev/resources/how-to/node-js-integration-with-regatta
- Kafka Integration with Regatta (How-To) - Ingress Data into Regatta using Kafka Sink Connector.: https://regatta.dev/resources/how-to/kafka-integration-with-regatta
- Build your JavaScript application with Regatta (Demos) - Build your own JavaScript application using Regatta's custom drivers and connectors.: https://regatta.dev/resources/demos/build-your-javascript-application-with-regatta
- Demonstration: Regatta Linear Scaling Part II (Demos) - Regatta is a scale-out distributed SQL database that guarantees strong ACID with high, linearly scalable performance. Regatta uniquely enables long,...: https://regatta.dev/resources/demos/demonstration-regatta-linear-scaling-part-ii
- Demonstration: Regatta Linear Scaling Part I (Demos) - Regatta is a scale-out distributed SQL database that guarantees strong ACID with high, linearly scalable performance. Regatta uniquely enables long,...: https://regatta.dev/resources/demos/demonstration-regatta-linear-scaling-part-i
- Demonstration: Integrating Regatta with Streaming/Event Data (Demos) - Streaming and event use cases are all around us, and great solutions like Kafka for event data exist and are...: https://regatta.dev/resources/demos/demonstration-integrating-regatta-with-streaming-event-data

## Press and analyst coverage

- Private Company Spotlight - What kind of infrastructure does it actually take to run fleets of autonomous AI agents? A new William Blair Spotlight...: https://regatta.dev/resources/whitepapers/private-company-spotlight-william-blair
- Unifying Data Stacks, Open-Weight Controversies & Google's Anti-Gravity CLI - “The reason why it works is this funky, unique, what is it called, concurrency control mechanism, So basically, how you...: https://agentsofdev.podbean.com/e/unifying-data-stacks-open-weight-controversies-googles-anti-gravity-cli-agents-of-dev-episode-32/
- RegattaDB Arrives: A Unified Engine Built for the Era of Read-Write AI - "Regatta’s pure scale-out architecture is an interesting technical differentiator for RegattaDB.": https://futurumgroup.com/insights/regattadb-arrives-a-unified-engine-built-for-the-era-of-read-write-ai/
- Regatta Data Launches RegattaDB for AI Agent Workloads - "The platform combines capabilities for transaction processing, analytics, and vector search, aiming to give AI agents a unified view of...: https://dailyaibrief.com/news/regatta-data-launches-regattadb-for-ai-agent-workloads-xMsdhNn4
- AI Database War Begins: Is RegattaDB the Breakthrough That Could Finally Replace Legacy Data Systems? - "RegattaDB launches at a time when enterprises are racing to deploy AI agents capable of reasoning, analyzing, and making decisions.": https://thesiliconreview.com/2026/07/ai-database-regattadb-vector-database-ai-agents
- Regatta Data launches unified base for AI with RegattaDB - "For organizations deploying AI agents at scale, this means they can finally support the massive concurrency and real-time demands of...: https://www.techtarget.com/data-technologies/news/366645786/Regatta-Data-launches-unified-base-for-AI-with-RegattaDB
- Regatta launches its unified OLTP, OLAP and vector database - "The same fundamental data-layer challenges that we saw years ago still exist today and agents are only magnifying them.": https://www.blocksandfiles.com/data-management/2026/07/15/regatta-launches-its-unified-oltp-olap-and-vector-database/5271769
- RegattaDB Launches as the Database Built for AI Agents - Unifying OLTP, OLAP, and Vectors - "Agents need to think, reason, and act on live data simultaneously, which means they need real-time execution of transactions (OLTP),...: https://finance.yahoo.com/technology/ai/articles/regattadb-launches-database-built-ai-123300321.html
- Dell PowerFlex/Regatta database combo overcomes trad database limitations - "Regatta produces its eponymous, scale-out, transactional (OLTP), analytic (OLAP) relational (OLxP) and vector database, with extensibility to semi-structured and unstructured...: https://www.blocksandfiles.com/data-management/2025/11/06/dell-powerflex/regatta-database-combo-overcomes-trad-database-limitations/1616674
- Flash-centric Regatta OLxP database working on faster access for AI agents - “Regatta is mainly a scale-out shared-nothing clustered architecture where heterogeneous nodes cooperate and can perform lengthy SQL statements in a...: https://www.blocksandfiles.com/ai-ml/2025/02/04/flash-centric-regatta-olxp-database-working-on-faster-access-for-ai-agents/1605631
- Database startup Regatta emerges from stealth mode - “Regatta can store multiple types of data as well as perform transactional, analytical, and high-ingress workloads – and it can...: https://www.blocksandfiles.com/data-management/2024/03/21/database-startup-regatta-emerges-from-stealth-mode/1608172

## Contact

- Website: https://regatta.dev
- Demo requests and enquiries: https://regatta.dev/contact-us
- Start free: https://regatta.dev/get-started
- Documentation: https://docs.regatta.dev
- LinkedIn: https://www.linkedin.com/company/regatta-data
- Email: info@regatta.dev