Database · OceanBase
One database.
Transactions, analytics and AI together.
OceanBase is a 100% self-developed, natively distributed database. Transactional, real-time analytical and AI workloads run on the same system — not three stacks stitched together.
Gartner® Peer Insights™ Voice of the Customer for Cloud Database Management Systems — Asia/Pacific Customers' Choice (2024 & 2025, two consecutive years) · Strong Performer per OceanBase public material
You used to buy three things. Now it's one.
OLTP database, data warehouse, vector store — three teams, three copies of data, three reconciliation exercises.
High concurrency, low latency, financial-grade availability
Natively distributed with transparent linear scaling; compatible with MySQL 5.7 and Oracle, so application change stays small. Runs on a single node or a cluster — small workloads don't have to start big.
Near-PB scale, second-level analysis
Row and column stores on the same data, so analytics doesn't require copying data out. One less ETL chain, one less warehouse, one less overnight batch window.
Multi-modal data and hybrid search
Vector, full-text, scalar and spatial in a single query; structured and unstructured data stored together. The context RAG and agents need, without assembling three systems first.
One copy of data, four kinds of search.
Structured, semi-structured and unstructured data stop living in separate silos.
Vector
Semantic retrieval and similarity matching, feeding RAG and recommendations.
Full-text
Keyword and phrase search across documents, contracts and support records.
Scalar
Existing structured filters, permissions and business rules.
Spatial
Geofencing, distance calculation and regional analysis.
Give your agents a sandbox they can break.
AI can only move fast if its mistakes don't reach production data.
Millisecond data sandbox
Clone the data, let agents test, alter schemas and rehearse flows. Throw it away afterwards; production is untouched.
Same data, same permissions
The sandbox isn't a different world — the permission model and audit trail match production, so what passes there means something.
Change the database, not the application.
Compatible with MySQL 5.7 and Oracle. Four steps, each one reversible.
Compatibility & performance assessment
The vendor's OMA tooling produces a report listing incompatible syntax, objects and performance risks before anything moves.
Test and production environments
Deployment form and zone layout fit the workload; full business flows validated in test first.
Data migration & validation
OMS handles schema and full load plus incremental sync; zero drift before cutover.
Production cutover
Switch the connection string, keep a reverse incremental channel, and you can fail back.
Three cost lines, coming down together.
Actual figures depend on a PoC — we don't promise numbers we haven't measured.
Many databases, one cluster
Multi-tenancy lets several applications share one cluster: utilisation moves from a typical 5–10% to 40–50%, and both hardware and licence footprint shrink.
1/5–1/4 after compression
Proprietary row/column encoding shrinks data first, then general compression. Compaction happens during off-peak merges, so read/write performance is unaffected.
One less system to run
Transactions and analytics share one copy of data: one less ETL, one less warehouse, one less on-call rota and backup policy.
Five industries, one set of criteria.
Industries and scenarios drawn from the vendor's published references — not an IUClouds customer list.
Financial services
Core ledgers, cards and insurance cores moving to distributed architectures — strong consistency and auditability required.
Telco & public sector
B/M/O domain upgrades, multi-tenant consolidation and cross-region resilience.
Retail & consumer
Peak-season traffic, elastic membership and order systems.
Manufacturing
Multi-plant data consolidation, one database layer under MES/ERP, zero-failure operation.
Internet
Global multi-infrastructure, breaking single-node limits, one operations stack.
Open source
2M+ downloads, 100k+ clusters, 2,000+ enterprises in production (vendor-published).
Four things. All of them.
We don't do licence-only deals — a database starts paying back after go-live.
Implementation
Deployment form, zone planning, parameter tuning, pre-launch load testing.
Migration
Compatibility assessment, data movement, dual-write validation, cutover and rollback.
Operations
Monitoring, backup drills, upgrades, capacity and performance governance.
Licence resale
Licensing sized to the actual deployment, including renewals and expansion.
We'll tell you when not to migrate.
Good fit
Data volume or concurrency beyond a single node's comfort zone; sharding that has become unmaintainable; rising licence and hardware costs; transaction and analytics needing one copy of data; an AI roadmap that needs a trustworthy data foundation; hard resilience or data-residency requirements.
Wait a while
Data fits comfortably on one node, no dedicated DBA, and no test environment to rehearse a cutover. Cleaning up the current architecture usually pays back faster than swapping the database.
Start with a compatibility assessment.
The report lists risk, remediation effort and estimated hours — with no obligation to buy.