数据流风格Data Flow Architecture是一种软件架构风格,它强调数据在系统各个组件之间的流动。数据流风格通常用于那些数据处理过程可以被分解为一系列顺序或并行执行的步骤的系统。这种风格适用于需要处理大量数据的应用,特别是那些数据处理过程可以被模块化为独立的步骤的情况,如信号处理、数据分析、编译器设计和流式计算等...
Maximize efficiency with simplified architecture, side-stepping data lock-in while reducing the proliferation of tools and duplicative data movement. Reach the next level of agility by enabling no-code developer self-service across all phases of the data pipeline lifecycle. ...
Figure 16: A stream processing system must process data in-stream, with a separate pipeline for storage, if needed, which does not lie on the "critical path." The flow of data in the lambda architecture is represented in the figure. The steps are as follows: ...
Figure 16: A stream processing system must process data in-stream, with a separate pipeline for storage, if needed, which does not lie on the "critical path."The flow of data in the lambda architecture is represented in the figure. The steps are as follows:...
Connecting your integrations to your architecture enables your team to understand the business impact and needs of the integrations they own. Optimization Reduce the time to identifying root causes, the time to implement integration platforms, and the time to maintain an overview. ...
In our daily programming and development process, we can also try to use the concept of pipeline data to optimize our program architecture to make the data flow of our program clearer and make us like a pipeline, each pipeline is specialized Responsible for their respective work to perform a ...
Use DataArts Studio DataArts Architecture to create entity-relationship (ER) models and dimensional models to standardize and visualize data development and output data g
Process Control Architecture It is a type of data flow architecture where data is neither batched sequential nor pipelined stream. The flow of data comes from a set of variables, which controls the execution of process. It decomposes the entire system into subsystems or modules and connects them...
Maximize efficiency with simplified architecture, side-stepping data lock-in while reducing the proliferation of tools and duplicative data movement. Reach the next level of agility by enabling no-code developer self-service across all phases of the data pipeline lifecycle. ...
Cloud-native, run everywhere architecture Zero-downtime operations with rolling upgrades At-least-once and exactly-once processing guarantees for stream processing pipelines Data replication between data centers and geographic regions using WAN Microsecond performance for key-value point lookups and pub-sub...