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Apache Hadoop · Apache Hadoop → Google Cloud Dataproc · Migration

Your Hadoop to Dataproc Migration: Trusted, Fixed-Scope, Senior-Led

We lift and shift your Hadoop, Spark, and Hive workloads to Google Cloud Dataproc with serverless scaling and lower TCO – no refactoring required.

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Powered by the 3PS Migration Engine

The lowest-cost way off Apache Hadoop: our migration tooling automates the repetitive work —you pay senior engineers for judgment, not keystrokes.

Automated discovery
Your Apache Hadoop estate mapped — workloads, dependencies, licensing — before day one
Conversion tooling
Schema, config and workload translation to Google Cloud Dataproc, automated where it's safe
Parity validation
Side-by-side testing proves Google Cloud Dataproc matches production before cutover
Runbook cutover
Rehearsed, reversible, scheduled in your maintenance window
3–6 months with 2–4
Typical migration timeline
$60,000–$500,000
Project budget range
40–70% vs vendor ren
Savings on legacy platform support

How we support Apache Hadoop → Google Cloud Dataproc after migration

  • Fixed-scope migration projects with senior platform engineers.
  • Legacy Hadoop stays under vendor support while you plan the move.
  • 40–70% savings vs vendor support renewals on your existing platform.
  • 24/7 US-based support after migration to Dataproc.
  • No forced big-bang cutover – migrate on your timeline.

Escalating Infrastructure Costs

High cost of maintaining on-prem Cloudera or Hortonworks clusters.

LDAP Lock-In

Strict on-prem LDAP dependencies that seem impossible to replicate in the Cloud.

Uncertain Compatibility

Complex legacy custom JAR dependencies that may break after migration.

Apache Hadoop → Google Cloud Dataproc migration — your questions answered

What happens to support for my on-premise Hadoop during migration?+

Yes. For the life of your vendor contract, your legacy Cloudera/Hortonworks platform remains under vendor support. If the contract lapses, our third-party support covers most operational issues while you complete the move (it is not vendor support and does not include vendor patches).

We rely on on-prem LDAP. How does that work in the Cloud?+

We handle it in the migration plan. Our engineers refactor your code to use GCS connectors or bridge through a lightweight LDAP proxy without rewriting core jobs.

My code has HDFS file-system assumptions. Will that break?+

We can treat the HDFS data path as a temporary staging layer or directly stream to GCS. The migration includes rewriting hard-coded HDFS paths in your Spark, Hive, and custom code.

We have many custom JARs. Will they work on Dataproc?+

We catalog every JAR dependency before the move. Senior engineers recompile or replace incompatible libraries as part of the fixed-scope project.

Ready to Migrate? Get a Hadoop to Dataproc TCO Assessment

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