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3rd Party Support
Progress Software · Progress OpenEdge → Google BigQuery · Migration

Trust our team for your OpenEdge to BigQuery migration

You migrate your Progress OpenEdge databases to Google BigQuery by first building a high-performance export pipeline that bypasses JDBC bottlenecks.

Get My Free AssessmentNo obligation. Just a clear plan from our senior engineers.

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No obligation. Just a clear plan from our senior engineers.

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Powered by the 3PS Migration Engine

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

Automated discovery
Your Progress OpenEdge estate mapped — workloads, dependencies, licensing — before day one
Conversion tooling
Schema, config and workload translation to Google BigQuery, automated where it's safe
Parity validation
Side-by-side testing proves Google BigQuery matches production before cutover
Runbook cutover
Rehearsed, reversible, scheduled in your maintenance window
3–6 months
Project timeline
2–3 senior engineers
Senior consultants per project
40–70%
Cost savings on legacy support

How we support Progress OpenEdge → Google BigQuery after migration

  • Senior platform engineers execute your fixed-scope migration.
  • Stay on OpenEdge vendor support until you’re ready to cut over.
  • Reduce legacy support costs by 40–70% while you plan the move.
  • 24/7 US-based support for post-migration analytics pipelines.
  • Eliminate legacy reporting queries crashing your operational systems.
  • Run blazing-fast analytical queries on Google BigQuery.

Crashing operational systems

Your legacy reporting queries consume so many resources they crash the operational system. Meanwhile, your business team demands machine-learning insights from historical data that OpenEdge can’t serve. You need a modern analytics platform like Google BigQuery – but the move feels risky.

Slow, unreliable data extraction

OpenEdge lacks high-performance native ODBC/JDBC interfaces, making data extraction a bottleneck. Standard connectors crawl when handling large transactional databases, and you can’t afford downtime for a lengthy export.

Change-tracking complexity

Managing change tracking across a large OpenEdge database without slowing transactions is difficult. Every approach you’ve seen either impacts performance or loses data fidelity. You need a CDC method that works at scale without risk.

Progress OpenEdge → Google BigQuery migration — your questions answered

Do I lose vendor support during the migration?+

Yes. While your vendor contract is active, you keep full vendor support on the legacy Progress OpenEdge platform. If the contract lapses, our independent third-party support covers most operational issues for the legacy system while you complete the move (it is not vendor support and does not include patches). We never force a big-bang cutover — you migrate on your timeline.

What is the typical timeline and budget for a Progress OpenEdge to BigQuery migration?+

Most projects run 3–6 months with 2–3 of our senior platform engineers. Budget typically ranges $70,000–$400,000 depending on data volume and complexity. We scope the work up front – no surprises.

How do you handle change data capture without slowing my operational database?+

We build a high-performance data export and CDC architecture that bypasses the traditional JDBC bottleneck. This lets you replicate change data from your OpenEdge RDBMS into BigQuery without slowing down transactional systems or losing change-tracking fidelity.

How do you deal with OpenEdge’s proprietary date/time formatting?+

Yes. OpenEdge stores dates and times in a proprietary format. Our migration engineers have deep experience normalizing these values during the export pipeline so they land in BigQuery as standard TIMESTAMP and DATE types – no manual rework required.

Accelerate with Managed Analytics – Claim Your Free Migration Blueprint

Let’s build your path to BigQuery. Claim your **Free Progress to BigQuery Migration Blueprint** today, and ask about our BigQuery Architecture Optimization and Managed Analytics Pipelines to accelerate insights.

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