Informatica vs Apache Hop: which to choose

Informatica vs Apache Hop: which fits your ETL estate

If you are facing the PowerCenter 10.4 support end, a renewal quote, or a data residency rule that keeps batch ETL on your own servers, Apache Hop is a credible fit for a self-hosted replacement, but only if your team can own the build, the runtime and the operations. Informatica's answer to the support change was a move to fee-based Extended Support, an upgrade to PowerCenter 10.5, or a path into its cloud Intelligent Data Management Cloud (IDMC). Hop is the open-source option in this comparison: Apache-2.0 licensed, no license fee, and run wherever you host it. Informatica fits when you want a managed cloud service, bundled data quality and catalog capabilities, and a single vendor to call when a pipeline fails at 2 a.m. Those services are the main reason organizations keep paying, and they are real costs that a Hop deployment has to add back through other tools and staff. Hop fits when batch ETL must stay on infrastructure you control, when you have engineers who can design, test and version pipelines in Git, and when the licensing line item is the problem. Hop's visual Hop GUI, its 250+ pipeline transforms and its ability to run the same pipeline on the native engine, Spark, Flink or Databricks through configuration give a credible base. Confirm the transform coverage against your actual mappings before you commit. The decision turns on four things: which support path your contract allows, where the data may physically sit, how many PowerCenter mappings and workflows you run and how complex they are, and whether your staff has the skills to operate Hop Server, schedulers and a metadata layer. Start by counting mappings and noting any that use PowerCenter-specific features, because no automatic PowerCenter importer exists and each one will need manual rebuilding. Hop's Kettle importer covers Kettle/PDI assets only, so do not expect it to convert PowerCenter work.

Which option fits which scenario

This table matches common Informatica situations to the option that usually fits best, with a one-line reason for each. Read it by finding the row closest to your current constraint, then checking the reason against your own estimate of data quality, catalog and hosting needs.

Scenario	Better fit	Why
Staying on PowerCenter 10.5 with Extended Support for a short bridge	PowerCenter 10.5 with Extended Support	Keeps existing mappings running while a rebuild is planned, but the Extended Support fee recurs and the path still ends at a migration.
Moving to Informatica's cloud service	IDMC	Keeps the vendor's managed platform and its data quality and catalog services, but consumption is billed and data processing leaves your own servers.
Keeping batch ETL on your own servers after PowerCenter support ends	Apache Hop	Runs pipelines on the native engine, Spark, Flink or Databricks, with no license fee, provided your team owns hosting and operations.
Team already maintains Kettle (PDI) or Talend jobs	Apache Hop	Hop's importer converts Kettle jobs and transformations, so the rebuild starts from working logic rather than from a blank canvas.
Team needs data quality, catalog and lineage out of the box	IDMC or PowerCenter with added services	Hop covers pipelines and metadata, so quality rules, stewardship and a catalog must be added as separate self-hosted tools.
Team that mainly ingests files, APIs and streams continuously	Apache NiFi, with Hop for batch transforms	NiFi's flow-based model fits continuous routing better than scheduled batch mappings, so pair it with Hop where heavy transformation is needed.
Team with few engineers and no Java or container operations skills	IDMC or a managed partner-run Hop deployment	Hop requires Java 21 and a scheduler or orchestrator around Hop Server, so the operating burden must be budgeted before committing.
Regulated team that must keep all processing in its own environment with a documented ETL inventory	Apache Hop	Pipelines and metadata stay in your repositories and infrastructure, and the team controls versions, access and evidence for its own assessments.

How PowerCenter, IDMC and Hop compare on design and execution

PowerCenter is Informatica's on-premises ETL product. Its design model centers on mappings built in a graphical designer and grouped into workflows that a workflow manager runs, with objects and connections held in a central repository. Teams with long-established PowerCenter estates usually know this repository model well, and that knowledge is useful when inventorying what must be rebuilt. Support timing also shapes the comparison: Informatica announced that PowerCenter 10.4 support ended March 31, 2024, after which it moved to fee-based Extended Support.

Visual design: Mappings are built in a graphical designer against a central repository that stores folders, objects and connections.
Workflow control: Workflows and worklets sequence sessions, carry dependencies and handle scheduling, so those behaviors must be rebuilt or replaced elsewhere.
Transform coverage: This comparison does not state a PowerCenter transform count. Confirm the transform list for your installed version in Informatica's documentation.
Execution: Jobs run on Informatica's own execution engine on servers you operate. Confirm which engine options and pushdown features apply to your version.
Support path: Extended Support is fee-based, so staying on PowerCenter is also a support decision.

Check your installed version, its full transform inventory and any pushdown settings against Informatica's current documentation before comparing them with Hop.

Capability comparison from supplied facts

This table sets what Apache Hop supplies for batch ETL against what Informatica sells as PowerCenter or IDMC, and what an Informatica exit must add or confirm. Read the Informatica column as a checklist to verify against your own contract and product edition, since the facts available here do not cover Informatica's internal feature set. The main takeaway is that Hop covers pipeline design, execution and deployment, while managed cloud, vendor support and data quality and catalog services become costs you must staff, buy or confirm.

Capability	Apache Hop	Informatica (confirm with vendor)
Visual design	Pipelines and workflows built on the Hop GUI visual canvas	Visual mapping design in PowerCenter Designer and IDMC; confirm which editions and tools your team uses
Transform coverage	250+ pipeline transforms and 80+ workflow actions	Confirm transform inventory per mapping against your PowerCenter XML exports; no automatic PowerCenter importer exists
Execution engines	Native Hop engine, Apache Spark, Apache Flink, Google Dataflow via Beam, Databricks, selected by runtime configuration	PowerCenter Integration Service or IDMC runtime; confirm whether your workloads need a different engine after migration
Deployment	Hop Server, apache/hop Docker image, exported ZIP resources or Git checkout; Hop Server is not a scheduler	On-premises PowerCenter servers or IDMC cloud; confirm the on-premises path available after 10.5.x support ends
Metadata and lineage	Metadata lives in Hop projects and metadata files; lineage across the estate needs a catalog to be added	Repository metadata and catalog features; confirm lineage depth and what it covers in your edition
Managed cloud	None from the Apache project; run on your own servers or cloud accounts, or deploy with DeployOpen	IDMC is Informatica's managed cloud path; confirm migration tooling and costs with Informatica
Vendor support	Community support through Apache channels; commercial support must be contracted separately	Vendor support and Extended Support for PowerCenter 10.4 (fee-based); confirm terms for 10.5.x
Data quality and catalog services	Not included; add a data quality tool and a catalog such as OpenMetadata or DataHub	Included as product modules in some editions; confirm which modules your contract covers

Where the data and control sit with each option

Informatica's cloud path and Apache Hop differ mainly in where pipeline metadata, run logs and data move during execution. Each card below covers one decision point that a CISO or platform lead should settle before comparing features or fees.

Data location in IDMC

IDMC is Informatica's hosted control plane, and workloads that run there move data through Informatica-managed services. Ask where metadata, job logs and any staging data are stored, which regions are available, and whether a hybrid or customer-run agent can keep source reads inside your network. Confirm these points in writing with Informatica, because the answer determines which data residency statements you can make to regulators.

Self-hosted Hop and Hop Server

With Apache Hop, the Hop GUI, pipeline metadata and execution run on hosts you control. A long-lived Hop Server executes pipelines on your machines, so source data, transformation output and logs stay within the network boundary you define. The remaining work is hardening those hosts, encrypting connections and deciding where Hop project files are versioned.

Docker deployment on your infrastructure

The apache/hop image suits short-lived runs, while apache/hop-web serves the browser-based Hop Web GUI. Both images are built on Alpine Linux with OpenJDK 21, so your team owns image scanning, patching, registry access and the Java runtime. Deciding which image runs where is an early architecture choice that affects who can reach the web interface.

Orchestration outside Hop Server

Hop Server is not a scheduler. It runs pipelines and workflows when work is submitted, so an external scheduler or orchestrator must trigger jobs, retry failures and record run status. Choose that orchestrator before cutover, because it also becomes a control point for credentials, access to Hop Server and audit logging of every scheduled run.

Identity and access under each option

In IDMC, user accounts, roles and connection credentials are managed inside Informatica's platform, and you should ask how SSO, role-based access and audit exports are configured. In Hop, access is whatever your team builds: directory integration for the web GUI, secrets stored in a vault rather than project files, and separate service accounts for each Hop Server. Map these controls to your existing identity provider before deciding.

Compliance evidence that DeployOpen prepares

DeployOpen can prepare the systems, configuration baselines and evidence that a compliance assessment examines for a self-hosted Hop estate. Auditors and certification bodies issue the reports and attestations, and no vendor or service provider issues them on your behalf. Ask IDMC's vendor which third-party reports it can share, and ask your assessor which evidence they will accept from a self-hosted stack.

What a Hop deployment has to add that Informatica bundles

A Hop deployment does not inherit the services that Informatica bundles with PowerCenter and IDMC, so the buyer has to decide who provides each one before the migration is scoped. The first gap is operations. Under IDMC, Informatica runs the cloud control plane and its runtime. With Apache Hop, your team or a partner runs the Hop Server processes, the Docker images or the Hop Web GUI, along with patching, high availability, backups of the project repositories and capacity planning. Confirm whether your platform team has capacity for that work, and whether an existing Kubernetes or VM standard can host Hop without a new operating model.

The second gap is vendor support and data quality tooling. Apache Hop is a community project with no commercial support contract, so production incidents, security advisories and version upgrades route to your own engineers or to a third-party provider you contract. Informatica's Extended Support and data quality services are separate purchases that you should map explicitly: profiling, cleansing and match rules are not part of a Hop pipeline by default, and you will need to decide whether to build them with Hop transforms, adopt a separate open-source quality tool, or keep a commercial one. The third gap is catalog and lineage. Hop keeps its metadata in project files, such as pipelines, workflows, environment definitions and metadata objects stored in Git, which makes versioning and code review straightforward. It does not provide an enterprise catalog with search, business glossary and cross-system lineage across warehouses and BI tools. That is a separate choice, covered on the sibling catalog page, and you should decide on it before you plan lineage requirements for auditors.

Two gaps remain in day-to-day operation. Scheduling is handled by an external orchestrator, because Hop Server executes pipelines and workflows but does not schedule them, so you need a tool such as an enterprise scheduler or Apache Airflow to submit work, handle retries and manage dependencies. Monitoring also requires your own stack: decide which logs, execution metrics and alerts from Hop Server feed your existing observability platform, and who is paged when a load fails. Before you commit, ask your provider to write these responsibilities into a scope document covering operations, support, quality, catalog, scheduling and monitoring, and use it as the basis for comparing the total cost of ownership with your current Informatica contract.

Cost components on each side and what drives them

Informatica and Apache Hop are priced in very different ways, so the comparison has to be made component by component rather than as a license line against zero. The cards below separate what Informatica bills for from what a self-hosted Hop deployment has to pay for in people, infrastructure and support, and mark each as one-time or recurring.

Informatica license or subscription

On the Informatica side, this is either PowerCenter Extended Support, which is fee-based after PowerCenter 10.4 support ended, or IDMC consumption measured in IPUs. Extended Support is typically recurring, while IDMC consumption scales with the jobs and services you run. Ask the vendor for the exact unit of measure, the term length, what happens if usage rises mid-term, and whether the quote covers PowerCenter 10.5 or only the older release.

Apache Hop software

Apache Hop is licensed under Apache-2.0, so there is no software license fee for the platform itself. The cost you still carry is the time to plan upgrades, since Hop 2.19.0 requires Java 21. Confirm the JDK version your security baseline allows, and budget for patching the Hop Server, the Hop GUI and any Java dependencies you add to the runtime.

Infrastructure and runtime hosting

Hop pipelines can run on the native engine, on a remote Hop Server, on Spark, on Flink, on Google Dataflow or on Databricks. Infrastructure is recurring: servers or containers for Hop Server, storage for the metadata project, and cluster capacity if you choose Spark or Flink. Compare this with IDMC consumption, where compute is included in the bill but tied to the vendor's platform. Ask your cloud or data center team to size compute for your peak batch window, not your average day.

Pipeline rebuild and migration effort

This is usually the largest one-time cost. No conversion tool covers PowerCenter mappings, so each mapping, session and workflow must be redesigned as a Hop pipeline or workflow and then tested against the same output. Hop's Kettle importer does not read PowerCenter objects, so this effort is not reduced by that tool. Drivers include the number of mappings, the use of custom expressions and Java transformations, and the quality of your existing pmrep exports. Ask any implementation partner to price the work per mapping group with a stated test approach.

Scheduler and orchestration

PowerCenter workflows often rely on its built-in scheduler, and Hop Server does not schedule work on its own. You will need an external scheduler or orchestrator to submit pipelines and workflows, which is a one-time design task followed by recurring operation. Choose it early, because it determines how dependencies, retries and alerting are handled. Confirm who will maintain it after go-live and whether it adds licensing if you choose a commercial distribution.

Support, data quality and engineering time

Informatica bundles vendor support and its data quality and catalog services under the subscription. A Hop deployment replaces that with a support contract from a third party, internal engineers or a retainer, and any data quality or catalog tooling must be added and licensed separately. Recurring engineering time covers upgrades, incident response and new pipelines. Ask for the support response terms in writing, the named skills in the team, and a clear split between one-time build work and ongoing run work.

How a move from PowerCenter to Hop proceeds

The sequence turns PowerCenter's repository into a verified inventory, proves the approach on a pilot, and then moves production ETL to Hop with both platforms running side by side until the cutover is signed off. There is no automatic PowerCenter importer, so every mapping is rebuilt and tested by people who understand the business logic.

Export the PowerCenter repository inventory
The PowerCenter team exports folders, mappings, sessions, workflows and connection references from Repository Manager or with pmrep ObjectExport, and stores the XML under version control. Architects then build a list of every mapping, source, target and schedule that the export describes. The output is a complete inventory with an owner and a business purpose for each object. Runtime behavior, session overrides and connection credentials are not fully carried in the XML, so the team also collects them from the administration console and the people who run the jobs. The step is done when every production workflow appears in the inventory with a named owner.
Classify workloads by pattern and risk
Working with data engineers and business owners, group the inventory into batch transformations, file loads, database-to-database moves, slowly changing dimensions, and jobs that depend on PowerCenter-specific transformations or pushdown optimization. Mark each group by business criticality, regulatory exposure and the number of downstream consumers. Flag any mapping that uses features you have not yet confirmed in Hop, such as particular Java or expression functions, partitioning or custom plug-ins. The output is a ranked migration backlog and a short list of features to verify. This classification decides which pipelines become the pilot and which wait until the pattern is proven.
Build a Hop pilot on a representative pipeline
Install Hop GUI on a workstation or in a development environment, using the Java version the current release requires, and set up a project with environment-specific metadata for connections. Choose two or three mappings that cover the common patterns from the classification step, then rebuild them as Hop pipelines and workflows. Record the design decisions, such as how lookups, error handling and parameters were mapped, in the project documentation. The pilot is complete when the rebuilt pipelines run against non-production data and the team can explain each difference from the original mapping. Confirm the transform coverage for each pattern against the Hop documentation before committing to a design.
Rebuild and test the remaining pipelines
Migrate the backlog in waves, grouped by the patterns from the classification. For each mapping, build the Hop pipeline, then compare row counts, checksums, reject files and aggregate totals between the PowerCenter output and the Hop output using the same input extracts. Store test data and expected results in version control so later changes can be checked against them. Where no equivalent transform exists, document a workaround and have the business owner approve it. The output for each wave is a signed test report per workflow. Plan the effort using the pilot's measured results rather than an estimate from this page, because the size of the rebuild depends on your mapping complexity.
Stand up Hop Server or containers
Decide where pipelines will execute: the local Hop engine on a server, a remote Hop Server, or a container image run in your orchestration platform. Hop Server is a long-running process that executes pipelines and workflows but does not schedule them, and the Hop documentation describes deploying projects as Docker images, exported ZIP resources or from a Git checkout. Configure the Hop Server, secure its access, and place project metadata and credentials in the environment that your security team approves. Engineers should confirm whether Spark, Flink or Databricks engines are needed for high-volume jobs. The step is done when a test pipeline runs on the target runtime from a clean deployment.
Add an external scheduler
Because Hop Server does not schedule work, choose and configure an external scheduler or orchestrator to submit pipelines and workflows on the same calendar as the PowerCenter sessions. Replicate dependencies, retry rules, alerting and restart behavior from the inventory, and document the mapping between each old schedule and each new job. Operations staff should be able to see run history, failures and logs in one place. The output is a scheduled job catalog with alerting that has been tested by forcing a failure. Many teams pair this step with the orchestration work described in the Airflow migration page, so check that choice before building job definitions.
Run both platforms in parallel
Run each migrated workflow on Hop while PowerCenter continues to run the same job against the same sources, and write the results to separate staging targets. Compare outputs every cycle, log every difference, and resolve each one by fixing the Hop pipeline or documenting an accepted variance with the business owner. Keep the parallel period long enough to cover month-end, quarter-end and any other cycle that your business treats as material. The output is a reconciliation log with zero unexplained differences for the agreed scope. Ask your PowerCenter support provider and Informatica account team to confirm the support status of the version you run during this period.
Cut over and retire PowerCenter jobs
After the reconciliation log is signed off by the data owners, switch downstream consumers to the Hop outputs, disable the PowerCenter sessions in the same change window, and keep the repository and its backups available for read-only reference. Record the cutover plan, rollback steps and the named person who approves a rollback. Review monitoring for the first full cycle after cutover and confirm that alerts reach the people who will respond. The output is a closed migration record, an archived PowerCenter repository and a runbook for the Hop environment. Retire the PowerCenter servers only after your retention and audit obligations for the archived outputs are met.

Questions buyers ask before moving from Informatica to Hop

What does moving from Informatica PowerCenter to Apache Hop cost?

The cost is mostly people time, with infrastructure and support as smaller recurring items. Apache Hop is Apache-2.0 licensed, so there is no license fee to remove. The one-time cost is rebuilding each PowerCenter mapping and workflow as a Hop pipeline or workflow, since no automatic PowerCenter importer exists. Effort rises with the number of mappings, the depth of transformation logic, the number of connections and how much testing each flow needs. Recurring costs include the servers or cloud accounts that run Hop, Hop Server or Spark and Flink clusters if you use them, monitoring, patching, and engineering time for upgrades. Ask any implementation partner for a quote built from a written inventory of mappings, connections and schedules, with rebuild, test, cutover and post-cutover support priced separately.

How long does a PowerCenter to Hop migration take?

Duration depends on the size and complexity of the PowerCenter estate, not on the tool itself. The main drivers are the number of mappings and workflows in scope, how many of them carry complex lookups, sessions with custom SQL or heavy business rules, the number of source and target systems, how well the existing logic is documented, and how much parallel running the business requires before cutover. Start by exporting the PowerCenter repository objects to build an inventory, then classify each item by complexity. Ask any provider to tie its timeline to that inventory and to a written scope, and confirm how data reconciliation and user acceptance testing are counted.

Can our team migrate from PowerCenter to Hop without outside help?

A team with ETL experience can do it alone if it has time, a clear inventory and someone who owns testing. Skills that matter include a working understanding of PowerCenter mappings, transformations, sessions and workflows, SQL against your source and target databases, Java for runtime setup (Hop 2.19.0 requires Java 21), Docker or Linux administration for deployment, Git for versioning Hop projects, and a scheduler such as Apache Airflow or cron, because Hop Server is not a scheduler. Gaps usually appear in performance tuning on Spark or Flink, in reconciliation of results, and in production operations. Assess those gaps honestly before deciding whether to staff internally, bring in help for specific phases, or use a retainer for support after go-live.

Does Apache Hop import PowerCenter mappings and workflows?

No. Apache Hop's built-in importer converts Kettle (Pentaho Data Integration) projects, including .kjb jobs, .ktr transformations and kettle.properties, into Hop workflows and pipelines. It does not read PowerCenter repositories or mappings. PowerCenter objects must be rebuilt by hand or with a custom conversion effort. Useful inputs for that work are the XML exports from PowerCenter Repository Manager or the pmrep ObjectExport command, which document sources, targets, transformations and connections. Those exports do not capture runtime behavior, session-level overrides or connection credentials, so validate each rebuilt pipeline against the output of the original job.

Which Apache Hop version and Java version do we need?

Apache Hop 2.19.0 is the release to plan against, and it was released on August 17, 2026. It requires Java 21. The apache/hop Docker image and the separate apache/hop-web image for the browser-based GUI are built on Alpine Linux with OpenJDK 21, so container deployments meet the same requirement. Before you standardize, confirm the current release on the Apache Hop download page, check that your JDK, database drivers and any Spark, Flink or Databricks runtime versions are compatible with Java 21, and test your pipelines on the exact version you will run in production.

Which Informatica services does Hop not replace?

Apache Hop covers batch ETL design, execution and orchestration. It does not include the managed cloud service, vendor support, a data quality rules engine with Informatica's feature set, or a data catalog with Informatica's automation. If your PowerCenter estate depends on those, you need to add them. Options include open-source catalogs such as OpenMetadata or DataHub, self-built data quality checks in SQL or Python, and a support contract from a commercial or implementation provider. Map each Informatica service you use to a named replacement and an owner before you commit to a timeline.

When should we bring in DeployOpen for a fixed-scope written agreement?

Bring in DeployOpen when you want a defined delivery of a self-hosted Hop platform inside your own infrastructure, with scope, deliverables and timelines agreed in writing before work starts. Typical written scopes cover planning, deploying Hop and Hop Server in your cloud accounts or data centers, integrating with your sources and targets, hardening, backup, documentation, and handover. Ongoing support, upgrades and testing can follow under a retainer. DeployOpen does not publish a price list, so ask for a quote based on your written inventory and scope. DeployOpen prepares systems and evidence for compliance assessments but does not issue audit reports or certifications.

Questions to answer before choosing a path

The first question is how exposed you are to the support deadline. PowerCenter 10.4 support ended March 31, 2024, and Informatica's announcement named three options: modernize to its cloud Intelligent Data Management Cloud (IDMC), buy Extended Support, or upgrade to PowerCenter 10.5. Confirm which version and Extended Support term your contract actually covers, and whether your Informatica account team will extend it. If your renewal date falls before a Hop rebuild can finish, Extended Support or a 10.5 upgrade buys time, but it is a recurring fee for a platform that is not moving forward. If a fixed exit date is not negotiable, plan for Hop to start in parallel rather than after the renewal.

The second question is where the data may legally be processed. If residency rules or your compliance program require that ETL logic, staging data and logs stay inside your own accounts or data centers, IDMC is the weakest fit, because it runs as a managed cloud service. Apache Hop runs on your own servers, through the native engine, a Hop Server or Spark, Flink or Databricks, so the residency answer depends on your infrastructure rather than on a vendor's region list. Ask Informatica in writing where IDMC processes and stores your data before you rely on it for an in-scope workload. Next, count the mappings and workflows that touch regulated data, since those decide how much of the estate must stay on infrastructure you control. The third and fourth questions are mapping volume and scheduler dependencies. Export the PowerCenter repository with Repository Manager or pmrep ObjectExport and count mappings, transformations, sessions, worklets and workflows, grouped by complexity. Hop has no automatic PowerCenter importer, so every mapping you rebuild is manual effort, and a large estate with many custom Expression or Java transformations pushes Hop toward a longer project. Also check which workflows are triggered by PowerCenter's own scheduler and which by external tools. Hop Server is not a scheduler, so jobs triggered from PowerCenter must be assigned to an external orchestrator before cutover.

The last two questions are data quality needs and in-house skills. If your team relies on PowerCenter's data profiling, cleansing or address validation, Hop will not replace those services out of the box, and you will need to choose and integrate a separate data quality tool or build the rules yourself. If you cannot name at least two engineers who will own Hop pipelines, Java 21 runtime upkeep and container or Git-based deployment after go-live, the cost of a self-hosted path rises sharply. Choose IDMC if you need a managed service and the residency terms are acceptable, choose PowerCenter 10.5 with Extended Support if you need a short bridge, and choose Hop if your mapping inventory is manageable, your data must stay on your infrastructure and your team can operate it.

How DeployOpen helps evaluate, implement or migrate

DeployOpen plans, implements, hardens, documents and supports self-hosted open-source platforms inside your own infrastructure, including Apache Hop for batch ETL. We start with a written scope for your PowerCenter or IDMC estate, then build and hand over the Hop environment you will run yourself.

How we scope

Inventory existing PowerCenter or IDMC mappings, workflows, connections and schedules before estimating any rebuild work.
Map each workload to Hop pipelines, Hop workflows or another tool, and flag transforms that need a manual rebuild.
Agree the execution target in writing, whether the native engine, Hop Server, Spark, Flink, Beam or Databricks.

How we build

Stand up Hop GUI, Hop Server and Docker-based deployment on your own servers or cloud accounts, using a pinned Java runtime.
Rebuild pipelines and workflows against source and target data sets, with reconciliation checks against PowerCenter output.
Set up metadata, shared connections, secrets handling and Git-based project versioning so lineage and changes stay traceable.

How we hand over

Document each pipeline, its dependencies, its scheduler trigger and the test results that show parity with the original job.
Walk your data engineering and operations staff through deployment, troubleshooting and promotion between environments.
Deliver runbooks for Hop Server, the external scheduler and backups, so your team can operate the stack without us.

How we support

Ongoing support, upgrades and continuous testing are available as a retainer after handover.
Plan Hop version upgrades and Java runtime changes as scheduled work, with regression runs on your pipelines first.
Confirm with us which data quality, catalog and monitoring services will be added, since Hop does not include them.

Informatica vs Apache Hop