Terminology · Lakeflow

Lakeflow Declarative Pipelines vs Delta Live Tables: What Changed & Why

They're the same product. Delta Live Tables (DLT) was renamed Lakeflow Declarative Pipelines at the Databricks Data + AI Summit in June 2025, as part of the new Lakeflow platform. Your existing DLT code still runs unchanged — what changed is the name, the branding umbrella, and the fact that the core engine is now open source.

Last updated July 2026.

The short answer

If you've read competitor content that still says "DLT," it's out of date on the name — but not on the concept. Lakeflow Declarative Pipelines is DLT: the same declarative approach where you define the tables and transformations you want, and Databricks manages the execution, dependencies, orchestration, and data quality for you.

No migration required. Databricks kept existing DLT pipelines and syntax working. You don't have to rewrite anything to be on Lakeflow Declarative Pipelines — the rename is backward-compatible.

What actually changed

Three things changed, and none of them is the pipeline logic itself:

Where it fits: the Lakeflow platform

Lakeflow unifies data engineering into three components. Knowing which is which — and their former names — is exactly the terminology discipline the current exam expects:

INGESTION Lakeflow Connect

Managed, high-throughput connectors that bring data in from databases, apps, and files.

TRANSFORMATION · formerly DLT Lakeflow Declarative Pipelines

The declarative engine for building Bronze → Silver → Gold transformations with built-in data quality — this is the renamed Delta Live Tables.

ORCHESTRATION · formerly Workflows Lakeflow Jobs

Scheduling and orchestration for production pipelines — previously known as Databricks Workflows / Jobs.

Old name → new name cheat sheet

You may have learned…Current name
Delta Live Tables (DLT)Lakeflow Declarative Pipelines
Databricks Workflows / JobsLakeflow Jobs
(various ingestion connectors)Lakeflow Connect

What it means for the exam

The May 2026 version of the Data Engineer Associate exam uses the current Lakeflow terminology, and it added a dedicated Lakeflow Jobs section. When you study, treat "DLT" and "Lakeflow Declarative Pipelines" as interchangeable concepts, but recognize the new names in questions. If a practice resource still frames everything as DLT and Workflows, it predates the rebrand — the ideas are right, the labels are stale.

Exam tip: Concepts like streaming tables, materialized views, and expectations (data-quality constraints) are unchanged by the rename. Learn the behavior; just attach the current name to it.

FAQ

Is Lakeflow Declarative Pipelines the same as Delta Live Tables?

Yes. It's the renamed Delta Live Tables. Same declarative pipeline model, same core capabilities — Databricks changed the name in 2025 and folded it into the Lakeflow platform.

Do I need to migrate my DLT pipelines?

No. The rename is backward-compatible. Existing DLT code and pipelines continue to work as Lakeflow Declarative Pipelines without any rewrite.

When did the name change?

At the Databricks Data + AI Summit in June 2025, when Databricks introduced the Lakeflow platform and reintroduced DLT as Lakeflow Declarative Pipelines.

What is Spark Declarative Pipelines?

It's the open-source core of the declarative pipeline engine, contributed by Databricks to Apache Spark (from Spark 4.1). Lakeflow Declarative Pipelines is the managed Databricks experience built on top of that engine.

Master the current terminology

The course uses today's Lakeflow naming throughout, so you won't get caught out by stale labels on exam day.

Start the Lakeflow Jobs unit →