This feature supports integrating SQL audit data from OceanBase Database with external storage systems (SLS and ElasticSearch). It aims to simplify the user configuration process, provide necessary monitoring mechanisms to ensure timely and reliable data transmission, and enhance the visibility and security of database operations.
Background information
In an enterprise-level database management environment, retaining SQL audit data is not only a technical and managerial requirement but also essential for addressing increasingly complex security challenges and strict compliance requirements. SQL audit provides comprehensive operational transparency, serving as a critical foundation for ensuring data security, optimizing operational efficiency, supporting compliance audits, and enabling rapid problem resolution.
By scientifically managing and analyzing SQL audit data, enterprises can maintain higher security and operational efficiency in the competitive landscape while reducing potential legal and business risks.
Concept introduction
SQL Audit
SQL audit refers to the feature that records audits on SQL statements executed in a database, including related metadata such as execution time, user information, and client IP address.
Service Log Service (SLS)
Service Log Service (SLS) is a cloud-native observability and analytics platform that provides large-scale, low-cost, real-time platform services for data such as logs, metrics, and traces.
SLS offers integrated capabilities including data collection, processing, query and analysis, visualization, alerting, consumption, and delivery, comprehensively enhancing digital capabilities in development, operations, maintenance, security, and other scenarios.
ElasticSearch
- ElasticSearch is a distributed search and analytics engine based on Lucene, supporting real-time data storage, retrieval, and complex analysis. It is highly scalable, allowing you to easily build clusters to handle massive data volumes, and provides flexible querying through its RESTful API.
- ElasticSearch is widely used in log analysis, full-text search, real-time data monitoring, and other scenarios, rapidly processing structured and unstructured data to help enterprises achieve data insights and decision optimization.
Application scenarios
Security and compliance auditing
Meet industry regulatory requirements by providing complete audit records of SQL operations.
Performance analysis and optimization
Identify performance bottlenecks and optimize them through analysis of historical SQL execution records.
Troubleshooting and root cause analysis
Quickly locate abnormal database operations and improve troubleshooting efficiency.