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Migration centers — AWS, GCP, Snowflake, Databricks, Teradata, Cloudera, Informatica, Palantir, SAS, Oracle to Azure

Hadoop / Hive to Azure Migration Center

Comparative positioning note

This document is written from the perspective of Microsoft Azure, Cloud Scale Analytics, and CSA Loom. Any description of third-party or competing products, services, pricing, or capabilities is derived from publicly available documentation and sources believed accurate at the time of writing, and is provided for general comparison only. We do not claim expertise in, or authority over, any non-Microsoft product or service; the respective vendor's official documentation is the authoritative source for their offerings, which may change over time. Nothing here is intended to disparage any vendor — where a competing product has genuine advantages, we aim to note them honestly. Verify all third-party details against the vendor's current official documentation before making decisions.

The definitive resource for migrating from Hadoop (Cloudera, Hortonworks, MapR, vanilla Apache) and Hive to Microsoft Azure, Databricks, Microsoft Fabric, and CSA-in-a-Box.

Who this is for

This migration center serves data platform leaders, Hadoop administrators, data engineers, and architects who are evaluating or executing a migration from on-premises or cloud-hosted Hadoop clusters to Azure-native services. Whether you are responding to end-of-support announcements (Cloudera CDP, HDInsight retirement), rising hardware refresh costs, or a strategic push toward a modern lakehouse, these resources provide the evidence, patterns, and step-by-step guidance to execute confidently.

Quick-start decision matrix

Your situation Start here
Executive evaluating Azure vs keeping Hadoop Why Azure over Hadoop
Need cost justification for migration Total Cost of Ownership Analysis
Need a component-by-component comparison Complete Feature Mapping
Ready to migrate HDFS data HDFS to ADLS Gen2
Ready to migrate Hive workloads Hive to dbt / SparkSQL
Running Spark on YARN Spark Migration
Have HBase clusters HBase to Cosmos DB
Have Kafka, Oozie, or other supporting services Supporting Services Migration
Need security/governance migration guidance Security Migration
Want hands-on tutorials Tutorials
Need performance data Benchmarks
Want operational best practices Best Practices

Strategic resources

These documents provide the business case, cost analysis, and strategic framing for decision-makers.

Document Lines Summary
Why Azure over Hadoop ~400 Nine evidence-based reasons the Hadoop era is ending and Azure is the successor
TCO Analysis ~350 Five-year cost comparison: bare-metal/IaaS Hadoop vs Azure PaaS lakehouse
Complete Feature Mapping ~400 35+ Hadoop components mapped to Azure equivalents with migration complexity ratings

Component migration guides

Detailed, component-by-component migration playbooks for every major Hadoop service.

Document Lines Summary
HDFS to ADLS Gen2 ~400 Storage migration: DistCp, AzCopy, format conversion, small-file compaction
Hive to dbt / SparkSQL ~400 Metastore migration, HiveQL conversion, UDF porting, worked examples
Spark on YARN to Databricks/Fabric ~350 Spark version migration, job submission, cluster policies, library management
HBase to Cosmos DB ~350 Column-family to document model, coprocessors to Change Feed, API mapping
Kafka, Oozie, and Supporting Services ~350 Kafka to Event Hubs, Oozie to ADF/Workflows, Sqoop, Flume, ZooKeeper, Pig
Security and Governance ~350 Ranger/Sentry to Purview, Kerberos to Entra ID, encryption, ACL mapping

Tutorials

Hands-on, step-by-step walkthroughs for the most common migration tasks.

Document Lines Summary
Tutorial: HDFS to ADLS Gen2 ~350 End-to-end data migration with format conversion and validation
Tutorial: Hive to dbt on Databricks ~350 Convert Hive SQL to dbt models, migrate metastore, run first dbt build

Operational resources

Document Lines Summary
Benchmarks ~300 MapReduce vs Spark, HDFS vs ADLS throughput, Hive vs Databricks SQL, cost comparisons
Best Practices ~300 Cluster decomposition, parallel-run, decommission planning, team retraining

How CSA-in-a-Box accelerates this migration

CSA-in-a-Box provides Bicep-based landing zones that deploy the Azure target architecture in hours rather than weeks:

  • Data Management Landing Zone (DMLZ): Purview catalog, Key Vault, shared networking — replaces Atlas, Ranger, and ZooKeeper governance functions
  • Data Landing Zone (DLZ): ADLS Gen2, Databricks workspace, ADF, Event Hubs — replaces HDFS, Spark-on-YARN, Oozie, and Kafka
  • Compliance YAMLs: Machine-readable FedRAMP/CMMC/HIPAA control mappings for every deployed resource

For capabilities beyond CSA-in-a-Box's current scope (e.g., Cosmos DB for HBase replacement, Fabric Real-Time Intelligence), this migration center provides direct guidance using the broader Azure ecosystem.

Migration timeline overview

gantt
    title Typical Hadoop-to-Azure Migration (40 weeks)
    dateFormat  YYYY-MM-DD
    section Phase 1 — Assessment
    Cluster inventory & workload profiling    :a1, 2026-01-06, 6w
    Tier classification (A/B/C/D)             :a2, after a1, 2w
    section Phase 2 — Design
    Target architecture & landing zones       :a3, after a2, 3w
    CSA-in-a-Box DMLZ/DLZ deployment          :a4, after a2, 2w
    section Phase 3 — Migration
    HDFS → ADLS Gen2 bulk copy                :a5, after a4, 6w
    Hive → dbt/SparkSQL conversion            :a6, after a4, 10w
    Spark jobs → Databricks/Fabric            :a7, after a4, 8w
    HBase → Cosmos DB (if applicable)         :a8, after a4, 10w
    Kafka → Event Hubs                        :a9, after a4, 4w
    Oozie → ADF/Workflows                     :a10, after a4, 6w
    Security: Ranger → Purview/RBAC           :a11, after a4, 8w
    section Phase 4 — Cutover
    Parallel run & reconciliation             :a12, after a6, 4w
    Consumer repointing & validation          :a13, after a12, 2w
    section Phase 5 — Decommission
    Cluster shutdown & license termination    :a14, after a13, 4w

Last updated: 2026-04-30 Maintainers: CSA-in-a-Box core team