Hadoop vs Apache Iceberg in 2025

 Hadoop vs Apache Iceberg: The Future of Data Management in 2025!!

1. Introduction

• Briefly introduce Hadoop and Apache Iceberg.
• Importance of scalable big data storage and processing in modern architectures.
• The shift from traditional Hadoop-based storage to modern table formats like Iceberg.

2. What is Hadoop?

• Overview of HDFS, MapReduce, and YARN.
• Strengths:
  • Scalability for large datasets.
  • Enterprise adoption in on-premise environments.
  • Integration with ecosystem tools (HBase, Hive, Spark).
• Weaknesses:
  • Complexity in management.
  • Slow query performance compared to modern solutions.
  • Lack of schema evolution and ACID compliance.

3. What is Apache Iceberg?

• Modern open table format for big data storage.
• Built for cloud and on-prem hybrid environments.
• Strengths:
  • ACID transactions for consistency.
  • Schema evolution & time travel queries.
  • Better performance with hidden partitioning.
  • Compatible with Spark, Presto, Trino, Flink.
• Weaknesses:
  • Still evolving in enterprise adoption.
  • More reliance on object storage than traditional HDFS.

4. Key Differences: Hadoop vs Iceberg

Feature	Hadoop (HDFS)	Apache Iceberg
Storage	Distributed File System (HDFS)	Table format on Object Storage (S3, ADLS, HDFS)
Schema Evolution	Limited	Full Schema Evolution
ACID Transactions	No	Yes
Performance	Slower due to partition scanning	Faster with hidden partitioning
Query Engines	Hive, Spark, Impala	Spark, Presto, Trino, Flink
Use Case	Batch processing, legacy big data workloads	Cloud-native analytics, real-time data lakes

5. Which One Should You Choose in 2025?

• Hadoop (HDFS) is still relevant for legacy systems and on-prem deployments.
• Iceberg is the future for companies adopting modern data lake architectures.
• Hybrid approach: Some enterprises may still use HDFS for cold storage but migrate to Iceberg for analytics.

6. Conclusion

• The big data landscape is shifting towards cloud-native, table-format-based architectures.
• Hadoop is still useful, but Iceberg is emerging as a better alternative for modern analytics needs.
• Companies should evaluate existing infrastructure and data processing needs before making a shift.

Call to Action:

• What are your thoughts on Hadoop vs Iceberg? Let us know in the comments!