DP-700 or Databricks Data Engineer Associate - which is better?

Neither is universally better; they are tied to different ecosystems. The DP-700 certifies data engineering on Microsoft Fabric and OneLake, while the Databricks Data Engineer Associate certifies pipelines on the multi-cloud Databricks lakehouse. The right choice is dictated by the platform your target employers run, so check the job postings in your field and let the stack decide.

Why does the DP-700 expire after a year but Databricks lasts two?

Microsoft uses annual renewals to keep its role-based certifications current, so the DP-700 is valid for one year - but renewal is a free, online, open-book assessment on Microsoft Learn, taken in the six months before it lapses. The Databricks Data Engineer Associate is valid for two years, but renewal means retaking the current paid exam, as there is no continuing-education option. So Databricks gives you a longer window but charges to renew; the DP-700 expires sooner but renews for free. Confirm current rules with each vendor.

Which is harder, DP-700 or the Databricks exam?

Both are intermediate, associate-level exams. The DP-700 runs 100 minutes, may include interactive question types, and expects you to work across SQL, PySpark and KQL over the full Fabric workflow - ingestion, security and optimisation. The Databricks Data Engineer Associate is shorter at 45 questions in 90 minutes and centres on Spark SQL and PySpark on the lakehouse. The DP-700 is broader across Fabric tooling; Databricks is more focused on Spark-based engineering.

The Databricks Data Engineer Associate is US$200 per attempt; the DP-700 is around US$165, though Microsoft prices it by region. Both have effectively free study paths: Microsoft Learn and a Fabric trial capacity for the DP-700, and Databricks Academy with a Community Edition or trial workspace for Databricks. Remember the renewal difference - the DP-700 renews for free yearly, while Databricks needs a paid retake every two years. Confirm current pricing with each vendor.

Do I need to know KQL for the Databricks exam?

No. KQL (Kusto Query Language) is part of the Microsoft Fabric world and appears in the DP-700, alongside SQL and PySpark, for real-time and Eventhouse scenarios. The Databricks Data Engineer Associate centres on Spark SQL and PySpark on the lakehouse and does not test KQL. If real-time data with KQL is part of your job, that points to the DP-700.

Should I learn both Fabric and Databricks?

Many data engineers encounter both over a career, especially as both run on Azure and overlap on open formats. But for a first credential, pick the platform your immediate target roles use rather than splitting effort. The core data-engineering concepts - loading patterns, transformations, orchestration, optimisation - transfer between them, so you can add the second platform later when a specific job calls for it.

Head-to-head comparison

DP-700 vs Databricks Data Engineer Associate: which should you choose?

By The Exam Atlas Editorial Team · Verified 2026-06-06

Our verdict

Both are associate-level data-engineering credentials, but they are tied to different ecosystems. Choose the DP-700 if your organisation runs Microsoft Fabric, OneLake and Power BI - common in Microsoft-centric and DACH enterprises - and you work across SQL, PySpark and KQL. Choose the Databricks Data Engineer Associate if your team runs the multi-cloud Databricks lakehouse with Spark and Delta Lake. One key practical difference: the DP-700 expires after one year (free online renewal), while Databricks is valid for two. Let the platform on your target jobs decide.

Side by side

The numbers that decide it, lined up across every dimension that matters.

	DP-700	Databricks DE Associate
Platform	Microsoft Fabric + OneLake	Databricks lakehouse (Spark + Delta Lake)
Vendor	Microsoft	Databricks
Ecosystem	Microsoft stack (Power BI, Azure)	Multi-cloud (AWS, Azure, GCP)
Cost	~US$165 (priced by region)	US$200 per attempt
Format	100 min; question count not published	45 scored questions, 90 min
Pass mark	700 / 1000 (scaled)	Not published by Databricks
Validity	1 year (free online renewal)	2 years (paid retake to renew)
Query languages	SQL, PySpark, KQL	Spark SQL, PySpark

Full exam pages: Microsoft Fabric Data Engineer (DP-700) · Databricks Certified Data Engineer Associate

The DP-700 and the Databricks Data Engineer Associate are both associate-level data-engineering credentials, but they live in different ecosystems: Microsoft Fabric on one side, the multi-cloud Databricks lakehouse on the other. Here is the detailed comparison, beyond the table above.

The core difference

The DP-700 (Microsoft Fabric Data Engineer Associate) is about data engineering on Microsoft Fabric. You implement and manage an analytics solution, ingest and transform data, and monitor and optimise it across Lakehouse and Warehouse, Spark notebooks, Dataflows Gen2, pipelines, OneLake and real-time data with KQL. It is depth in the Microsoft Fabric stack, and it sits naturally beside Power BI and Azure.

The Databricks Data Engineer Associate is about the lakehouse: building pipelines on the Databricks Data Intelligence Platform with Apache Spark, Delta Lake and open formats, and governing them with Unity Catalog. It is depth in engineering data on Spark, and it runs across AWS, Azure and Google Cloud rather than a single vendor’s ecosystem.

If you can say which platform your work runs on, the choice is largely made. Most of the other differences follow from it.

Cost compared

Both are moderate, with free study paths:

DP-700: around US$165, but Microsoft prices the exam by region, so confirm locally. Microsoft Learn materials are free and a Fabric trial capacity is available.
Databricks Data Engineer Associate: US$200 per attempt, plus any applicable tax. Databricks Academy offers free self-paced learning, with a free Community Edition or trial workspace for practice.

The bigger cost difference is renewal, not the sticker price. The DP-700 renews for free each year; the Databricks credential needs a paid retake every two years to stay current. Confirm current fees with each vendor.

Difficulty and time

Both are intermediate exams, in different shapes:

DP-700: 100 minutes, delivered through Pearson VUE, and it may include interactive question types as well as multiple choice. Microsoft does not publish the question count, and the pass mark is 700 out of 1000 on a scaled system. The breadth is wide: it expects you to manipulate data with SQL, PySpark and KQL across the entire Fabric workflow.
Databricks Data Engineer Associate: shorter and more focused - 45 scored questions (plus a few unscored items) in 90 minutes, online with a proctor. Databricks does not publish the passing score or per-topic weighting, so aim for broad competence. The difficulty is practical comfort with Spark SQL and PySpark.

Neither is “easier”. The DP-700 is broader across Fabric tooling and adds KQL; Databricks is a tighter, Spark-focused exam.

Platform and ecosystem

This is often the deciding factor:

Microsoft Fabric (DP-700) is deeply integrated with the Microsoft stack: OneLake as the unified data lake, tight links to Power BI, and a place in Azure-centric and DACH enterprises. The trade-off is that it ties you to the Microsoft ecosystem.
Databricks is built on Apache Spark and Delta Lake, favours open table formats, and runs on AWS, Azure and Google Cloud. The trade-off is fewer out-of-the-box ties to a single vendor’s BI and cloud services, in exchange for multi-cloud openness.

So the honest framing is Microsoft ecosystem integration versus multi-cloud open flexibility. There is also the renewal cadence to weigh: a Fabric credential expires yearly (free to renew), while Databricks lasts two years but charges to renew.

Career outcomes

DP-700 maps to: data engineers, analytics engineers and ETL/ELT developers in Microsoft-centric organisations adopting Fabric and OneLake. It is the Fabric-era successor to the retired DP-203.
Databricks Data Engineer Associate maps to: junior and aspiring data engineers, ETL developers moving into lakehouse work, and Spark or SQL practitioners on Databricks teams.

Both platforms are widely adopted, and a minority of engineers work with both, especially on Azure. But earn the one your target roles actually use first.

How to decide

Ignore prestige and answer one question: which platform do the jobs you want actually run?

Microsoft Fabric, OneLake, Power BI, or SQL plus PySpark plus KQL in a Microsoft-centric shop → DP-700.
The Databricks lakehouse with Spark and Delta Lake, especially across multiple clouds → Databricks Data Engineer Associate.
Genuinely torn → check the job postings in your region and let the platform that appears most pick the exam. Factor in the renewal difference too: the DP-700 expires yearly but renews for free, while Databricks lasts two years and charges to renew.

The core data-engineering concepts transfer between them, so choose by fit with your stack rather than by which name sounds bigger.

Which should you choose?

Choose DP-700 if

Data engineers in Microsoft-centric organisations who build analytics solutions on Microsoft Fabric and OneLake and work across SQL, PySpark and KQL.

Choose Databricks DE Associate if

Aspiring or junior data engineers on the Databricks lakehouse who build pipelines with Spark SQL and PySpark across AWS, Azure or Google Cloud.

Our specialty · side by side

Related comparisons

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VS Databricks vs Snowflake: which data certification should you choose? Compare → VS DP-700 vs Google Professional Data Engineer: which cloud data cert? Compare →

Where these exams lead

Career paths featuring these exams

See where DP-700 and Databricks DE Associate sit in a longer certification sequence.

How to become a data analyst: the certs, then the path to data engineer View path →

FAQ

DP-700 or Databricks Data Engineer Associate - which is better?: Neither is universally better; they are tied to different ecosystems. The DP-700 certifies data engineering on Microsoft Fabric and OneLake, while the Databricks Data Engineer Associate certifies pipelines on the multi-cloud Databricks lakehouse. The right choice is dictated by the platform your target employers run, so check the job postings in your field and let the stack decide.
Why does the DP-700 expire after a year but Databricks lasts two?: Microsoft uses annual renewals to keep its role-based certifications current, so the DP-700 is valid for one year - but renewal is a free, online, open-book assessment on Microsoft Learn, taken in the six months before it lapses. The Databricks Data Engineer Associate is valid for two years, but renewal means retaking the current paid exam, as there is no continuing-education option. So Databricks gives you a longer window but charges to renew; the DP-700 expires sooner but renews for free. Confirm current rules with each vendor.
Which is harder, DP-700 or the Databricks exam?: Both are intermediate, associate-level exams. The DP-700 runs 100 minutes, may include interactive question types, and expects you to work across SQL, PySpark and KQL over the full Fabric workflow - ingestion, security and optimisation. The Databricks Data Engineer Associate is shorter at 45 questions in 90 minutes and centres on Spark SQL and PySpark on the lakehouse. The DP-700 is broader across Fabric tooling; Databricks is more focused on Spark-based engineering.
Which costs more?: The Databricks Data Engineer Associate is US$200 per attempt; the DP-700 is around US$165, though Microsoft prices it by region. Both have effectively free study paths: Microsoft Learn and a Fabric trial capacity for the DP-700, and Databricks Academy with a Community Edition or trial workspace for Databricks. Remember the renewal difference - the DP-700 renews for free yearly, while Databricks needs a paid retake every two years. Confirm current pricing with each vendor.
Do I need to know KQL for the Databricks exam?: No. KQL (Kusto Query Language) is part of the Microsoft Fabric world and appears in the DP-700, alongside SQL and PySpark, for real-time and Eventhouse scenarios. The Databricks Data Engineer Associate centres on Spark SQL and PySpark on the lakehouse and does not test KQL. If real-time data with KQL is part of your job, that points to the DP-700.
Should I learn both Fabric and Databricks?: Many data engineers encounter both over a career, especially as both run on Azure and overlap on open formats. But for a first credential, pick the platform your immediate target roles use rather than splitting effort. The core data-engineering concepts - loading patterns, transformations, orchestration, optimisation - transfer between them, so you can add the second platform later when a specific job calls for it.