HTAP

HTAP Solution Enables Business Analysis System Integration

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Challenges of Traditional Enterprise Software

Weak Hybrid Query Capability

Traditional enterprise software systems like ERP, CRM, and OA typically rely on standalone database systems. However, as data volume increases or when confronted with new intelligent applications such as advertisement recommendation or risk monitoring, these systems often struggle to handle high-concurrency OLTP queries and complex, large-volume OLAP queries simultaneously.

Poor Flexibility

In traditional database solutions, maintaining real-time performance often involves scheduling operations like backup archiving, report analysis, and complex queries during off-peak periods to prevent disruptions to the business database's performance. This approach limits flexibility due to the necessity of avoiding impacts on business operations during high-load periods.

Complex Traditional TP + ETL + AP Architecture

To address the high-concurrency business requirements and large data volumes in mixed-query analysis scenarios, many enterprises resort to deploying both OLTP and OLAP databases. Additionally, they implement an Extract, Transform, Load (ETL) process to synchronize data from OLTP to OLAP databases. While this architecture can meet the demands, it introduces complexity and maintenance challenges.

分析时效性差

When using separate databases to address TP and AP issues independently, real-time data synchronization from the original OLTP system to the OLAP system becomes a challenge. This can significantly delay the timeliness of analysis, making it difficult to meet user requirements in scenarios where timeliness is crucial, such as fraud detection and product recommendations.

Solution

MatrixOne offers a comprehensive HTAP data solution to tackle the challenges faced by traditional enterprise applications like ERP/CRM in handling both process-oriented OLTP and analytic OLAP workloads. By providing a user experience similar to standalone relational databases while significantly boosting support for large-scale analytical business operations, MatrixOne enables users to seamlessly enjoy a real-time, integrated experience for business analysis.

One-stop Experience
MatrixOne provides a comprehensive solution catering to both TP and AP needs. It provides robust support for business applications involving CRUD operations, as well as the ability to manage extensive data analysis and reporting tasks. MatrixOne simplifies intermediate data transformation and aggregation processes in real-time streaming scenarios, providing users with a seamless experience akin to using a standalone MySQL instance for integrating business analytics systems.
High Real-time Capability
MatrixOne's HTAP solution is designed to handle the entire process from data writing to querying. This includes efficient completion of data access, pre-processing, storage, analysis, and result feedback within the same data engine in a short timeframe. Such integration greatly streamlines the data processing process, enhances data processing efficiency, and enables true end-to-end real-time data processing.
Efficiency
MatrixOne adopts a single storage engine approach to implement HTAP, distinguishing itself from traditional multi-engine approaches. Users only need to maintain a single cluster and store a single set of data, resulting in reduced maintenance and storage costs. Furthermore, MatrixOne leverages mature and cost-effective object storage as its primary storage solution, providing users with a highly cost-effective option.
Infinite Scalability
MatrixOne follows a containerized architecture where storage, computation, and transactions are completely separated, allowing for independent scalability. In HTAP scenarios, users have the flexibility to configure resources independently for OLTP and OLAP workloads by grouping resources. This enables rapid scaling in environments with fluctuating mixed workloads while maintaining relative isolation between the two. Such an architecture provides users with the ability to achieve flexible and efficient resource allocation in their HTAP deployments.