Lakeflow 声明式管道集成与互操作性：从任何地方获取数据.pdf

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1、Forward-looking StatementThis presentation has been prepared for informational purposes only.The information set forth herein does not purport to be complete or contain all relevant information.Statements contained herein are made as of the date of this presentation unless stated otherwise.This pres

2、entation and the accompanying oral commentary may contain forward-looking statements.In some cases,forward-looking statements can be identified by terms such as“may”,“will”,“should”,“expects”,“plans”,“anticipates”,“could”,“intends”,“projects”,“believes”,“estimates”,“predicts”,or“continue”,or the neg

3、ative of these words or other similar terms or expressions that concern Databricks expectations,strategy,plans,or intentions.Forward-looking statements are based on information available at the time those statements are made and are inherently subject to risks and uncertainties that could cause actu

4、al results to differ materially from those expressed in or suggested by the forward-looking statements.Forward-looking statements should not be read as a guarantee of future performance or outcomes.Except as required by law,Databricks does not undertake any obligation to publicly update or revise an

5、y forward-looking statement,whether as a result of new information,future developments or otherwise.2DLT Integrations and InteroperabilityGet Data From and to AnywhereRyan Nienhuis6/10/2025Why interoperability matters?Most data pipelines touch external systems:databases,APIs,message queues,and key-v

6、alue storesTraditional ETL jobs can ingest from anywherebut DLT was historically limitedYou told us:DLT needs to connect with your ecosystemThis talk:how we fixed that and whats now possible4The world is not just Lakehouse-native100s of connectors via Scala&Python Data Source APIsJDBC(Postgres,MySQL