DataEngPrep.tech
QuestionsPracticeAI CoachDashboardPacksBlog
ProLogin
Home/Questions/Spark/Big Data/What are the advantages of using Delta Lake over Parquet?

What are the advantages of using Delta Lake over Parquet?

Spark/Big Dataeasy0.5 min read

**Why Delta Over Raw Parquet**: Parquet is immutable; no deletes, no transactional writes. Concurrent writers create corrupt state. Delta adds transaction log and metadata. **Delta Advantages**: (1) **ACID**—concurrent writes; readers see consistent snapshot. (2) **Time...

🤖 Analyze Your Answer
Frequency
Low
Asked at 1 company
Category
452
questions in Spark/Big Data
Difficulty Split
88E|81M|283H
in this category
Total Bank
1,863
across 7 categories
Asked at these companies
Puma

Why This Question Matters

This easy-level Spark/Big Data question appears frequently in data engineering interviews at companies like Puma. While less common, it tests deeper understanding that distinguishes strong candidates.

How to Approach This

Start by clearly defining the core concept being asked about. Interviewers want to see that you understand the fundamentals before diving into implementation details. Structure your answer with a definition, then explain the practical application with a concise example.

Expert Answer
103 words

Why Delta Over Raw Parquet: Parquet is immutable; no deletes, no transactional writes. Concurrent writers create corrupt state. Delta adds transaction log and metadata.

Delta Advantages: (1) ACID—concurrent writes; readers see consistent snapshot. (2) Time travel—versionAsOf, timestampAsOf for audits and rollback. (3) MERGE/UPDATE/DELETE—CDC, upserts without overwrite. (4) Schema enforcement/evolution—reject bad data; add columns safely. (5) OPTIMIZE/VACUUM—compact small files; reclaim storage.

Scalability Trade-offs: Transaction log can grow; checkpoint files and VACUUM manage it. Z-ordering helps reads but costs write time.

Cost Implications: Delta adds ~5–10% storage for log; read performance often better via compaction. Enables use cases (CDC, time travel) impossible with raw Parquet.

dataengprep.techdataengprep.techdataengprep.techdataengprep.tech
dataengprep.techdataengprep.techdataengprep.techdataengprep.tech
dataengprep.techdataengprep.techdataengprep.techdataengprep.tech
dataengprep.techdataengprep.techdataengprep.techdataengprep.tech
dataengprep.techdataengprep.techdataengprep.techdataengprep.tech
dataengprep.techdataengprep.techdataengprep.techdataengprep.tech

Want feedback on your answer?

Paste your answer to this question and our AI Coach scores it, finds gaps, and shows you the FAANG-level version.

Try Answer Analyzer →
Want all answers as a PDF for offline study?
1,863 questions across 7 categories — Interview Packs →

Free: Top 20 SQL Interview Questions (PDF)

Get the most asked SQL questions with expert answers. Instant download.

No spam. Unsubscribe anytime.

Related Spark/Big Data Questions

mediumWhat is the difference between repartition and coalesce in Apache Spark?FreehardWhat is the difference between SparkSession and SparkContext in Spark?FreemediumWhat is the difference between cache() and persist() in Spark? When would you use each?FreemediumWhat is the difference between groupByKey and reduceByKey in Spark?FreemediumWhat is the difference between narrow and wide transformations in Apache Spark? Explain with examples.Free

Companies that ask this Spark/Big Data question

Puma interview questions →

Want to know if YOUR answer is good enough?

Paste your answer and get instant AI feedback with a FAANG-level improved version.

Analyze My Answer — Free

According to DataEngPrep.tech, this is one of the most frequently asked Spark/Big Data interview questions, reported at 1 company. DataEngPrep.tech maintains a curated database of 1,863+ real data engineering interview questions across 7 categories, verified by industry professionals.

← Back to all questionsMore Spark/Big Data questions →