oceanbase

The Fastest Distributed Database for Transactional, Analytical, and AI Workloads.

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💡 Why It Matters

OceanBase addresses the need for a high-performance distributed database that can handle both transactional and analytical workloads, making it particularly valuable for ML/AI teams. With its robust architecture, it supports complex queries and large-scale data processing, ensuring that engineers can derive insights quickly and efficiently. This production-ready solution has matured significantly, making it a reliable choice for mission-critical applications. However, it may not be the best fit for teams requiring a simple, lightweight database or those with minimal data processing needs.

🎯 When to Use

OceanBase is a strong choice for teams needing a scalable, high-speed database capable of handling diverse workloads, especially in AI and machine learning contexts. Teams should consider alternatives if they require a simpler setup or are working with smaller datasets.

👥 Team Fit & Use Cases

This open source tool for engineering teams is ideal for data engineers, machine learning engineers, and database administrators. It is commonly integrated into data analytics platforms, AI-driven applications, and large-scale data processing systems.

🎭 Best For

Machine Learning and AI Engineer

🏷️ Topics & Ecosystem

analytics cloud-native database distributed-database fulltext fulltext-search fulltext-support hacktoberfest htap mysql mysql-compatibility oceanbase olap oltp paxos scalable vector vector-database vector-search vectors

📊 Activity

Latest commit: 2026-02-14. Over the past 96 days, this repository gained 313 stars (+3.2% growth). Activity data is based on daily RepoPi snapshots of the GitHub repository.