Designing Disaster Recovery with OceanBase: A Failure-Domain Playbook
How to choose the right OceanBase disaster recovery architecture by failure domain - Server, Zone/IDC, Region, or full cluster - with a decision matrix.
Why Your Vector Database Benchmark Is Wrong for AI Agents
Under streaming AI workloads, vector databases see high P99 jitter (1.1×–10.3×) under concurrency. seekdb v1.3.0’s fixed delta+snapshot HNSW avoids this, delivering 22× QPS and 19× P99 gains over prior version.
What Mission-Critical SaaS Really Demands From a Database
Multi-tenancy, elastic scaling, always-on uptime — SaaS workloads have a very specific database profile. Here's how six SaaS requirements translate into concrete database capabilities, and where most platforms fall short.
Why Critical Workloads Need a New Architecture
Centralized databases, manual sharding, and middleware-based scaling are reaching their limits. Here's why mission-critical workloads now demand native distributed SQL — and what that architecture actually looks like.
Inside OceanBase's High Availability Architecture: A Kernel-Level Walkthrough
A kernel-level look at OceanBase's three HA mechanisms — multi-replica Paxos, arbitration-based recovery, and tenant-level physical standby — and where each fits.
5 Minutes to a Working AI Prototype: A Developer's Guide to seekdb D0
A hands-on guide to seekdb D0, the free trial entry point for OceanBase's AI-native hybrid search database. Spin up a MySQL-compatible instance with vector, full-text, and data branching in one curl command — no signup, no credit card.
Dynamic AI-to-Database Queries with Claude, MCP, and OceanBase
Learn how to connect Claude to OceanBase using the Model Context Protocol (MCP) and enable dynamic schema discovery and natural-language SQL without brittle prompt engineering.
Beyond Memorization: How seekdb M0 Teaches Agents to Learn
seekdb M0 splits accumulated agent knowledge into Experience (strategy) and Skill (operations), connected by progressive loading. On AppWorld, GPT-4o + M0 hits 39% pass rate vs 24% baseline, with −35% steps and −32% tokens.
What FinTech Infrastructure Demands in the AI Era
OceanBase has spent years working alongside leading fintech companies like AliPay, GCash, and DANA. Here's what we've learned about what fintech data infrastructure really needs, and how AI is raising the bar, and how OceanBase addresses the needs with an unified architecture.
Beyond HTAP: What a Unified Data Platform Actually Requires
OceanBase has evolved from an OLTP-first database into a unified platform that handles transactions, real-time analytics, and AI inference on a single engine — no separate warehouses, no ETL pipelines, no vector database add-ons.
OceanBase Blog
Product insights, engineering deep dives, and real-world use cases from the OceanBase team.
OceanBase has spent years working alongside leading fintech companies like AliPay, GCash, and DANA. Here's what we've learned about what fintech data infrastructure really needs, and how AI is raising the bar, and how OceanBase addresses the needs with an unified architecture.
Designing Disaster Recovery with OceanBase: A Failure-Domain Playbook
How to choose the right OceanBase disaster recovery architecture by failure domain - Server, Zone/IDC, Region, or full cluster - with a decision matrix.
Why Your Vector Database Benchmark Is Wrong for AI Agents
Under streaming AI workloads, vector databases see high P99 jitter (1.1×–10.3×) under concurrency. seekdb v1.3.0’s fixed delta+snapshot HNSW avoids this, delivering 22× QPS and 19× P99 gains over prior version.
What Mission-Critical SaaS Really Demands From a Database
Multi-tenancy, elastic scaling, always-on uptime — SaaS workloads have a very specific database profile. Here's how six SaaS requirements translate into concrete database capabilities, and where most platforms fall short.
Why Critical Workloads Need a New Architecture
Centralized databases, manual sharding, and middleware-based scaling are reaching their limits. Here's why mission-critical workloads now demand native distributed SQL — and what that architecture actually looks like.
Inside OceanBase's High Availability Architecture: A Kernel-Level Walkthrough
A kernel-level look at OceanBase's three HA mechanisms — multi-replica Paxos, arbitration-based recovery, and tenant-level physical standby — and where each fits.
5 Minutes to a Working AI Prototype: A Developer's Guide to seekdb D0
A hands-on guide to seekdb D0, the free trial entry point for OceanBase's AI-native hybrid search database. Spin up a MySQL-compatible instance with vector, full-text, and data branching in one curl command — no signup, no credit card.
Dynamic AI-to-Database Queries with Claude, MCP, and OceanBase
Learn how to connect Claude to OceanBase using the Model Context Protocol (MCP) and enable dynamic schema discovery and natural-language SQL without brittle prompt engineering.
Beyond Memorization: How seekdb M0 Teaches Agents to Learn
seekdb M0 splits accumulated agent knowledge into Experience (strategy) and Skill (operations), connected by progressive loading. On AppWorld, GPT-4o + M0 hits 39% pass rate vs 24% baseline, with −35% steps and −32% tokens.
What FinTech Infrastructure Demands in the AI Era
OceanBase has spent years working alongside leading fintech companies like AliPay, GCash, and DANA. Here's what we've learned about what fintech data infrastructure really needs, and how AI is raising the bar, and how OceanBase addresses the needs with an unified architecture.
Beyond HTAP: What a Unified Data Platform Actually Requires
OceanBase has evolved from an OLTP-first database into a unified platform that handles transactions, real-time analytics, and AI inference on a single engine — no separate warehouses, no ETL pipelines, no vector database add-ons.
RPO and RTO Explained: A Decision Framework for Database DR Architecture
Learn how to calculate RTO and RPO requirements for your database, avoid common sizing mistakes, and map your targets to the right disaster recovery architecture.
Cross-Cloud DR Networking: Sync Methods & Paths
In this post, we’ll break down the sync methods, network paths, latency factors, and cost trade-offs that shape whether a cross-cloud deployment is viable in practice.
