MatrixOne

SaaS Applications

Simple, Fast, Cost-Effective Data Service for SaaS

Problems with SaaS Architecture

Difficulty in Multi-tenant Architecture

In traditional SaaS architecture design, multi-tenancy often involves deciding between sharing one database instance or isolating database instances. Sharing one database instance can simplify O&M tasks but may lead to data isolation issues. Isolating database instances ensures workload isolation across tenants but comes with a significant administrative burden. Architecture design frequently involves striking a balance between these considerations.

Limited Scalability

SaaS applications rely on the public cloud to deliver services and are capable of rapidly scaling their user base. However, this poses the challenge of maintaining data processing capabilities that can keep up with the demands of business expansion. Sharding and partitioning in traditional databases have notable limitations, which hinder the optimization of scaling. As a result, users are often required to manage a substantial amount of expansion logic at the business application layer.

Complex Data Architecture

As SaaS applications mature, a single MySQL database may no longer suffice to meet the requirements of analytics, monitoring, ML/AI, and other new data loading types. To address these needs, SaaS applications often have to incorporate additional database components like ClickHouse, ElasticSearch, and Hadoop, which adds to the operational burden.

Inefficient Use of Cloud Resources

In the traditional cloud usage model, SaaS applications typically acquire cloud resources, including databases, based on estimated peak demands. However, in reality, the utilization rate during regular business operations is often lower than anticipated, resulting in significant resource wastage. This issue becomes particularly pronounced during business downturns when releasing resources is not feasible, leading to ongoing costs for idle resources.

Solution

MatrixOne offers a comprehensive suite of highly scalable data processing engines, an infinitely flexible elasticity solution, and a robust multi-tenant management system. This effectively resolves the challenges of isolation and scalability encountered by SaaS providers when implementing conventional database solutions.
By leveraging MatrixOne, SaaS providers can achieve real-time responsiveness to unpredictable workloads, simplifying the construction of data processing platforms that utilize multiple databases. This enhances the resource utilization and cost-effectiveness of SaaS applications.

  • Multi-tenancy Capabilities

    MatrixOne inherently possesses multi-tenancy capabilities, automatically guaranteeing data and workload isolation. This simplifies the alignment of application layer tenants with database tenants for SaaS applications. Additionally, MatrixOne's autoscaling and API management functionalities enable effortless management of a vast number of tenants for users.

  • Infinite Scalability

    MatrixOne's cloud-native storage-compute separation architecture offers limitless scalability. It efficiently gathers real-time usage data, enabling the automatic allocation of additional storage and compute resources based on workload demands. This eliminates the need for users to intervene operationally, ensuring an optimal user experience.

  • Hyper-Coveraged Architecture

    As a newly developed HSTAP database, MatrixOne is capable of handling diverse data types and business workloads such as OLTP, OLAP, time series, vectors, and more all within a unified database. This enables SaaS applications to maintain a straightforward single-database architecture even when faced with a range of data processing needs. This design simplifies the setup and maintenance of multiple dataflow pipelines, reducing complexity for users.

  • Pay-as-you-Go Based on SQL Usage

    MatrixOne's Serverless service operates on a comprehensive pay-as-you-go model, allowing users to only pay for the compute and storage resources they actively utilize. During periods of low application loads or when there is no load at all, users are only required to pay a minimal cost to maintain the application's availability.

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