申请试用
HOT
登录
注册
 
Power Your Delta Lake with Streaming Transactional Changes
Power Your Delta Lake with Streaming Transactional Changes

Power Your Delta Lake with Streaming Transactional Changes

Spark开源社区
/
发布于
/
3478
人观看

Organizations are adopting data digitization and data-driven decision making is at the heart of this transformation. Cloud Data Lakes and Datawarehouses provide great flexibility to proto-type and roll out applications continuously at much lower costs.

Transactional databases are optimized for processing huge volumes of transactions in real-time, whereas the cloud data lake needs to be optimized for analyzing huge volumes of data quickly. This brings about a challenge in creating a streamlined data flow process from capturing realtime transactions into a cloud datawarehouse to drive realtime insights in a scalable and cost effective manner.

In this session, we’ll show how organizations can easily overcome that challenge by adopting a robust platform with StreamSets and Delta Lake. StreamSets provides a no-code framework to automate ingestion of transactional data and data processing on Spark, while Delta Lake provides ACID transactions, scalable metadata handling, and unifies streaming and batch data processing.

6点赞
2收藏
0下载
确认
3秒后跳转登录页面
去登陆