
PowerContext 1.2.0 connects project memory to decision models and adds native code understanding, helping coding agents make evidence-based changes.


OceanBase HTAP runs TP and AP workloads in one cluster using row, column, or hybrid storage, cutting analytics latency from T+1 to near real time.


OceanBase's Data Agent scored 90.62% on the Data Agent Benchmark (DAB), the first to break 90%, outscoring GPT- and Claude-based agents by running on open-source GLM-5.2 with a full model + agent + data-system stack.


OceanBase multi-tenancy consolidates many business systems into one cluster with tenant-level CPU, memory, and IOPS quotas — without the interference of a shared instance.


Fifteen years ago, OceanBase had just been born and proven its amazing ability during the 11.11 Global Shopping Festival. In those days, we spent every waking moment researching emerging technologies and envisioning an exciting new future. Then, a particular quote left a deep impression on me. Marc ...


The author moderated a roundtable with technology and data leaders on what it truly means to be "AI-ready" from a data perspective. The conversation went beyond expected topics (vector databases, RAG, data quality) into a more fundamental rethinking of data architecture assumptions.


This is the third article in OceanBase's Elastic Scaling series, covering vertical scaling — replacing existing nodes with higher-spec machines while keeping the cluster's logical topology (node count) unchanged, making the process nearly transparent to applications.


How distributed architecture changes the design of payment, commerce, healthcare, telecom, logistics, SaaS and intelligent application workloads.


Charlie Yang explains the five architectural shifts that take a unified distributed database to an AI Lakebase: from relational tables to multimodal tables, lookup to hybrid search, human-friendly to agent-friendly, SQL compute to open compute, and schema to semantics.


Enterprise AI Agents need more than NL2SQL — they need a governed capability surface. Learn how OceanBase DataPilot builds Ontology bottom-up, turning validated analyses into reusable, governed Actions inspired by Palantir AIP.

Product insights, engineering deep dives, and real-world use cases from the OceanBase team.

Fifteen years ago, OceanBase had just been born and proven its amazing ability during the 11.11 Global Shopping Festival. In those days, we spent every waking moment researching emerging technologies and envisioning an exciting new future. Then, a particular quote left a deep impression on me. Marc ...


PowerContext 1.2.0 connects project memory to decision models and adds native code understanding, helping coding agents make evidence-based changes.


OceanBase HTAP runs TP and AP workloads in one cluster using row, column, or hybrid storage, cutting analytics latency from T+1 to near real time.


OceanBase's Data Agent scored 90.62% on the Data Agent Benchmark (DAB), the first to break 90%, outscoring GPT- and Claude-based agents by running on open-source GLM-5.2 with a full model + agent + data-system stack.


OceanBase multi-tenancy consolidates many business systems into one cluster with tenant-level CPU, memory, and IOPS quotas — without the interference of a shared instance.


Fifteen years ago, OceanBase had just been born and proven its amazing ability during the 11.11 Global Shopping Festival. In those days, we spent every waking moment researching emerging technologies and envisioning an exciting new future. Then, a particular quote left a deep impression on me. Marc ...


The author moderated a roundtable with technology and data leaders on what it truly means to be "AI-ready" from a data perspective. The conversation went beyond expected topics (vector databases, RAG, data quality) into a more fundamental rethinking of data architecture assumptions.


This is the third article in OceanBase's Elastic Scaling series, covering vertical scaling — replacing existing nodes with higher-spec machines while keeping the cluster's logical topology (node count) unchanged, making the process nearly transparent to applications.


How distributed architecture changes the design of payment, commerce, healthcare, telecom, logistics, SaaS and intelligent application workloads.


Charlie Yang explains the five architectural shifts that take a unified distributed database to an AI Lakebase: from relational tables to multimodal tables, lookup to hybrid search, human-friendly to agent-friendly, SQL compute to open compute, and schema to semantics.


Enterprise AI Agents need more than NL2SQL — they need a governed capability surface. Learn how OceanBase DataPilot builds Ontology bottom-up, turning validated analyses into reusable, governed Actions inspired by Palantir AIP.


Learn how OceanBase achieves zero-downtime horizontal scaling through automatic data rebalancing, Multi-Paxos consensus, and transparent routing via ODP. Add nodes with a single parameter change.


Ontology vs. semantic layer: two different problems in the AI data stack. Why you need both, what breaks with only one, and how OceanBase unifies them.
