From the team
PhoenixAI Blog
Engineering deep-dives, product updates, and perspectives on real-time analytics and AI from the PhoenixAI team.
When Agents Write the SQL, Precomputation Stops Working
Materialized views work because dashboards ask the same questions every day. Agents do not. Here is what an analytical engine has to do when the query shape is decided at runtime.
- Product
Meet Agent Fawkes — Your AI Copilot Inside PhoenixAI Cloud
Talk to your PhoenixAI data in plain English. Generate, fix, and optimize SQL without leaving the editor. Keep every byte of customer data inside your VPC.
Aug 15, 20265 min - Product
Talk to your PhoenixAI Clusters Right From Claude: Introducing the PhoenixAI MCP Connector
Query your data, manage your clusters, and get cost insights conversationally — without ever leaving Claude Console. The PhoenixAI MCP connector for Claude is now available.
Aug 15, 20267 min - Product
Introducing PhoenixAI Anywhere — Self-Managed Real-time and AI Agent Analytics for private environments
The PhoenixAI database and the Anywhere Console that manages it.
Aug 15, 20267 min - Product
Smarter Scaling in PhoenixAI Cloud BYOC
Spikes in concurrency, mixed workloads, and bursty traffic break traditional scaling. Smarter Scaling in PhoenixAI Cloud BYOC adjusts compute to match real-time demand.
Aug 15, 20266 min - AI & Agents
When Real-Time Meets Agents: Why We've Been on This Path All Along
Real-time workloads are moving from the specialized systems of a few teams to a shared expectation across the entire industry.
Jun 19, 20267 min - AI & Agents
2026 Is When Open Data, Real-Time Analytics and AI Agents Converge
2026 is when open data, real-time analytics, and AI agents converge — driven by production-ready agents, "boring" Iceberg ops, and product-embedded analytics that users actually feel.
Nov 24, 20256 min - AI & Agents
Analytical Agents — New Challenges for the Underlying Data Infrastructure
AI agents need more than BI. Open formats, sub-second latency, MCP, and a feedback-driven execution engine — what agent-native analytics actually demands.
Nov 24, 20258 min - AI & Agents
How we made high-frequency upserts queryable in under a second on columnar storage
Analytical databases are columnar engines built for append-mostly data and large scans.
Nov 24, 202514 min - Tutorial
Data Skew in Customer-Facing Analytics: The Hidden Cost Behind Latency
What data skew really is, why it's especially dangerous in multi-tenant customer-facing applications, and how to solve it with a practical, production-ready approach.
Sep 12, 20256 min - Engineering
5 Brilliant Lakehouse Architectures from Tencent, WeChat, and More
Slow lakehouse queries forced enterprises to copy data into proprietary warehouses. Modern query engines change that. Here are five lakehouse architectures from the field.
Jan 30, 20246 min