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Google Cloud Migration Tools

10 Google Cloud Migration Tools and Services

Migrating cloud infrastructure to Google Cloud Platform is a complex process. However, getting the right Google Cloud migration tools and expertise will ensure a successful and streamlined migration.

Kevin KiruriAleksander HougenSimona Ivanovski

Written by Kevin Kiruri (Writer)

Reviewed by Aleksander Hougen (Co-Chief Editor)

Facts checked by Simona Ivanovski (Fact-Checker)

Last Updated: 2024-09-11T09:02:05+00:00

All our content is written fully by humans; we do not publish AI writing. Learn more here.

Cloud migration is the process of moving data, applications or other business elements to a different cloud service provider, or from an organization’s on-premises infrastructure to another. Google Cloud migration tools are a suite of services and tools designed to facilitate a simple and smooth migration from on-premises or other cloud environments to Google Cloud Platform. 

They also provide cost optimization and performance improvement opportunities, enabling businesses to fully leverage Google Cloud’s scalability and flexibility. 

Google Cloud Migration Tools: 10 Options

The main Google Cloud Migration tools and services include Migrate for Compute Engine, Storage Transfer Service, Transfer Appliance, BigQuery Data Transfer Service, Database Migration Service, Anthos, Cloud Data Fusion, Datastream, Dataflow and Cloud Run.

  • Migrate for Compute Engine: A lift-and-shift cloud migration tool for moving virtual machines from on-premises infrastructure, AWS or Azure to GCP. It supports multiple operating systems, minimizes downtime and simplifies the migration of large-scale VM workloads to GCP. 
  • Storage Transfer Service: A fully managed service for migrating large volumes of data from online or on-premises infrastructure to Google Cloud Storage. It enables scalable and automated transfers of object storage, file systems and other data to GCP.
  • Transfer Appliance: A high-capacity storage appliance for physically transferring petabytes of data to Google Cloud Storage. It also facilitates offline data migration for large datasets that aren’t suitable for network transfer.
  • BigQuery Data Transfer Service: A fully managed service for ingesting data from databases and various SaaS applications, such as Salesforce and Teradata, into BigQuery.
  • Database Migration Service: A completely managed service that allows you to migrate databases from on-premises infrastructure or other clouds into Google Cloud databases like Cloud Spanner. It simplifies the database migration process, has minimal downtime and supports heterogeneous database migrations. 
  • Anthos: A hybrid and multi-cloud platform for building and managing modern applications with Kubernetes. It helps run containerized applications on-premises, in GCP or in other clouds, providing a consistent development and operational experience.
  • Cloud Data Fusion: A fully managed data integration service for building and managing data pipelines. It enables data extraction, transformation and loading from diverse sources into GCP warehouses and lakes.
  • Datastream: A serverless CDC (change data capture) and replication service for capturing database changes and delivering them to GCP. It facilitates real-time data replication from various relational databases to GCP services like BigQuery and Pub/Sub.
  • Dataflow: A fully managed, serverless data processing service for batch and streaming workloads. It provides a unified platform for developing and executing data pipelines that can process large volumes of data in parallel.
  • Cloud Run: A serverless platform for running stateless containers that are invocable through HTTP requests. It allows you to build and deploy highly scalable microservices and web applications on GCP without managing the underlying infrastructure.

1. Migrate for Compute Engine (Formerly Velostrata)

migrate for compute engine
Migrate for Compute Engine lets you migrate VMs from different
cloud sources to VM instances on Google Cloud.

Migrate for Compute Engine facilitates the transfer of virtual machines (VMs) from a bare metal solution or other cloud environment to Google Cloud’s Compute Engine. It features live VM migration with minimal downtime, automated conversion of VM formats to GCE-compatible images, support for various hypervisors and virtual desktops, and migration task runbook automation.

Migrate for Compute Engine allows integration with on-premises VMs, AWS, Azure and VMware. It simplifies VM migration tasks, reduces migration time and offers continuous data replication. However, the service requires careful planning and network assessment, so you may need to have technical expertise in VM management for a successful migration.

With this service, you can migrate VMs into Google Cloud for free, but charges may be incurred for the resources consumed during replication, such as storage and compute costs. The service is mostly used for data center exit and consolidation, disaster recovery, business continuity planning and hybrid cloud infrastructure setup.

2. Storage Transfer Service

storage transfer service
Storage Transfer Service automates data transfer to and from Google Cloud Storage.

Storage Transfer Service imports data from external sources via other cloud providers or from on-premises file systems into Google Cloud Storage. Its features include scheduled data transfers, data validation and verification using checksums to ensure data integrity, data filtering and transformation options, as well as the transfer of objects, files and directories.

Storage Transfer Service easily integrates with AWS S3, HTTP/HTTPS locations and on-premises file systems. Its benefits include a simple and easy-to-use data migration interface, scalability for large-scale data transfers, and automated scheduling and monitoring. However, the service can transfer data to cloud storage only, and it may have network bandwidth limits.

Transferring data into Google Cloud is free, but outgoing transfers have egress charges. The pricing depends on the amount of data transferred and the storage class used. Storage Transfer Service is used for migrating data to GCP, archiving large data volumes to cloud storage, performing backups and disaster recovery, and ingesting data for analytics and machine learning.

3. Transfer Appliance

transfer appliance
Google Cloud Transfer Appliance transfers large amounts of data
from on-premises servers to Google Cloud Storage

Transfer Appliance is a physical device that can transfer large datasets (petabyte-scale) to Google Cloud. It’s ideal for scenarios where network transfer isn’t feasible or cost-effective. The device features high-capacity storage, secure data transfers, and status tracking and monitoring for the appliance.

It integrates with both on-premises and cloud storage systems. It’s efficient for very large datasets, providing both security and reliability. The service also reduces data transfer time compared to a network transfer. However, using it for small datasets can be costly as it requires physical shipping and handling, and the initial setup may be complex.

Transfer Appliance’s pricing includes appliance rental and shipping fees, as well as data ingestion fees. Its use cases revolve around large-scale data migrations, backup and disaster recovery, media and entertainment content archives, and the shutdown of physical servers.

4. BigQuery Data Transfer Service

bigquery data transfer service
BigQuery Data Transfer Service automates data movement
between SaaS applications and BigQuery.

The BigQuery Data Transfer Service lets users automate data flow from SaaS applications to BigQuery. It supports various SaaS applications and databases, enabling scheduled and recurring data transfers. The service offers scheduled data imports, support for multiple data sources and incremental data updates, and data transformation and mapping options.

It also integrates with SaaS services such as Google Ads, Salesforce, Teradata and Google Analytics. Some benefits include automated data ingestion into BigQuery, simplified data pipeline management, reduced manual effort for data loading, and real-time analytics. However, data source compatibility issues and limited data transformation capabilities may pose a challenge to users.

The BigQuery Data Transfer Service is priced based on the amount of data that is processed and stored in BigQuery. Some of its use cases include business intelligence, marketing analytics, data warehousing, machine learning and data science applications.

5. Database Migration Service

database migration service
The Database Migration Service helps to migrate databases into Google Cloud.

The Database Migration Service allows you to migrate databases to Google Cloud with minimal downtime. It handles schema and data conversion, ensuring a smooth migration process. The service supports homogenous and heterogenous migrations, online and offline migration, and automated schema conversion and data replication. You can also monitor and log migration progress.

The service integrates with various on-premises databases, cloud databases like AWS RDS and Azure SQL Database, and database engines like MySQL, PostgreSQL and SQL Server. It offers simplified database migration, automated schema and data conversion, and reduced downtime risk during migration. However, it can be complex to set up and manage, and large databases may take a while to migrate.

Pricing for the Database Migration Service is based on the instance size and the duration of the migration. Its use case is centered around migrating cloud databases to Cloud SQL, consolidating databases on GCP, modernizing applications and developing cloud-native applications.

6. Anthos

anthos
With Anthos, users can build and run modern applications using Google Cloud.

Anthos is a hybrid- and multi-cloud management platform that lets you run containerized applications. It provides a consistent development and operational experience in a range of environments. Anthos provides unified management of Kubernetes clusters, centralized configuration and policy enforcement, and service mesh for secure communication and traffic management.

It easily integrates with Google Kubernetes Engine, on-premises Kubernetes clusters and cloud Kubernetes services such as AWS EKS and Azure AKS. It thrives due to its portability and flexibility across environments. In addition to providing improved security and observability, Anthos decreases complexity and reduces management overhead.

Working with Anthos does pose some challenges, though. For one, dealing with Kubernetes and containerization requires technical expertise. The initial setup can also be complicated, and it may require complex networking and security configurations.

Pricing is subscription-based, and it also depends on the number of vCPUs and the memory used for Anthos components. Its main use cases include modernizing existing apps with containers, building hybrid and multi-cloud architectures, accelerating application development and deployment, and implementing microservices architectures.

7. Cloud Data Fusion

cloud data fusion
The Cloud Data Fusion service is an enterprise data integration
option for quickly building and managing pipelines.

Cloud Data Fusion is a fully managed data integration platform that provides a visual interface for building and managing data pipelines. 

It allows users to connect to various data sources, transform data, and load it into data warehouses or lakes. The service features a visual pipeline designer with drag-and-drop components, prebuilt connectors for various data sources and destinations, support for batch and real-time data processing, and data transformation capabilities using Apache Spark.

Cloud Data Fusion integrates with BigQuery, cloud storage, Cloud SQL, Pub/Sub, on-premises data storage and SQL servers, as well as other SaaS applications. It simplifies ETL processes, offers scalable data integration, and reduces the time and effort required for data integration tasks. The service also supports various data formats and protocols.

On the other hand, working with Cloud Data Fusion does present some challenges. Users must be familiar with data integration concepts and tools, and complex transformations could require custom code development. The initial setup and configuration process may also be complex for beginners.

Pricing is split across two functions: pipeline development and execution. Pipeline development is subscription-based and offers three editions: Developer, Basic and Enterprise. For pipeline execution, you are charged for the Dataproc clusters created. The service is used to build data warehouses and data lakes, perform data ingestion, processing and integration, and manage ETL and ELT processes.

8. Datastream

datastream
The Datastream API allows you to synchronize data across
heterogeneous databases and storage systems.

Datastream API is a serverless change data capture (CDC) and replication service that lets users capture database changes in real time and deliver them to various Google Cloud target platforms. 

It supports Oracle and MySQL as source databases. In terms of features, Datastream offers real-time data capture from Oracle and MySQL, low-latency data replication to Google Cloud services, schema evolution support for adapting to database changes, and exactly-once delivery for reliable data replication.

Cloud Datastream integrates with services such as Oracle, MySQL, BigQuery, Pub/Sub and cloud storage. Its benefits include real-time, scalable and reliable data replication, simplified data integration and reduced operational overhead. However, it’s limited to MySQL and Oracle workloads, and its setup and configuration procedures are complex.

Datastream pricing is based on the volume of data that is replicated or processed, as well as the number of connections used. Its use cases involve running real-time analysis and reporting, executing data synchronization between databases, providing event-driven architectures and microservices, and building real-time dashboards and applications.

9. Dataflow

dataflow
The Dataflow service helps developers build and run data pipelines.

Dataflow is a serverless stream and batch processing service that lets developers build and run data pipelines capable of processing large volumes of data in parallel. It offers real-time data processing, a unified programming model for batch and streaming data processing, autoscaling, support for various programming languages, and prebuilt templates for data processing tasks.

The tool integrates with services like BigQuery, Pub/Sub, Apache Beam and cloud storage. It can handle large-scale data processing and easily integrates with the Google Cloud ecosystem. Dataflow is also scalable and reliable for large data workloads. Some challenges include its reliance on Apache Beam or other supported programming models, and it may need significant development effort.

Dataflow’s pricing is based on the number of vCPUs, memory and persistent disks used during pipeline execution. Its use cases include facilitating ETL and ELT processes, conducting real-time data processing and analytics, preparing data for machine learning, performing stream processing and building event-driven architectures.

10. Cloud Run

cloudrun
The Cloud Run platform helps developers run containers directly
on top of Google’s scalable infrastructure.

Cloud Run is a serverless platform that enables developers to run stateless containers that are invocable via HTTP requests. It features fast autoscaling and direct VPC connectivity, and it can also run scheduled jobs to completion. Cloud Run supports various programming languages, and it offers integrated logging and monitoring.

The platform integrates with many GCP services like Cloud Build, Cloud Monitoring, Cloud Logging and Container Registry. It simplifies application deployment and management, and it offers high availability, scalability and portability across different cloud environments. Some downsides include cold start latency and stateless architecture limitations for applications requiring persistent connections.

Cloud Run’s pricing is based on the number of requests, vCPU usage and memory usage. Its use cases include building microservices and APIs, building web applications and backend services, running event-driven applications and functions, and hosting containerized workloads.

What Are the Best Third-Party Cloud Migration Tools for Migrating to GCP?

The best third-party cloud migration tools for migrating to Google Cloud are NetApp Cloud Volumes ONTAP, DuploCloud, Carbonite Migrate, Corent MaaS and Turbonomic.

  • NetApp Cloud Volumes ONTAP: A cloud-based storage solution that provides advanced data management capabilities for file and block workloads on GCP. It features enterprise-grade data management, seamless GCP integration, high availability, disaster recovery, simplified cloud migration and reduced storage costs. The pricing is subscription-based and depends on the storage capacity and features used.
  • DuploCloud: A cloud migration and management platform that automates the deployment and configuration of cloud infrastructure. The service offers configuration and deployment automation, security and compliance automation, and Infrastructure-as-Code automation. It also helps reduce time to market, improves operational efficiency, and enhances security and compliance. It has subscription-based pricing with the option to get custom prices depending on the number of nodes.
  • Carbonite Migrate: A disaster recovery and migration solution that simplifies workload migration. It features agentless automated migration, continuous data replication and flexible migration options. The service helps mitigate risks, accelerate migration and ensure business continuity. It offers flexible pricing for personal, professional or business operations.
  • Corent MaaS: A Platform-as-a-Service solution that helps migrate legacy applications to the cloud. Some features include automated infrastructure discovery and assessment, recommendations for optimal GCP resources and configurations, and automated migration. It can provide ongoing monitoring and optimization of migrated workloads. The platform has flexible pricing alternatives, including subscription and pay-as-you-go options based on the services you utilize.
  • Turbonomic: An application resource management (ARM) platform that helps optimize the performance and cost of cloud applications. Turbonomic supports multiple cloud platforms, and it provides cost and performance optimization, automated scaling, and continuous monitoring and adjustment of the migrated environment. It also offers flexible pricing models, including per-workload or per-virtual machine subscriptions, plus enterprise-level agreements.

What Are the Best Third-Party Cloud Migration Service Providers for Migrating to GCP?

The best third-party cloud migration service providers for migrating to GCP are Zluri, DigitalSuits, Cloud4C, Chetu, Adastra and Onica.

  • Zluri: This SaaS management platform aids in cloud migration. It simplifies the process by providing tools for discovery, license optimization and automated provisioning. It offers consultancy services by providing insights into usage, costs and security. The subscription-based pricing depends on the size of your organization, and it’s also open to providing custom pricing.
  • DigitalSuits: DigitalSuits provides end-to-end cloud migration consultancy services including assessment, planning, migration and post-migration support. It guides its clients through the entire migration process, which mitigates risks and ensures a smooth transition. Pricing is project-specific and based on the scope and complexity of the migration. Quotes are provided after initial consultation.
  • Cloud4C: A cloud managed services provider offering comprehensive solutions such as cloud migration, cloud migration strategy development, cloud optimization and disaster recovery. It offers multi-cloud support, has 24/7 customer support and provides managed security services. The service provides customized pricing.
  • Chetu: A custom software development company that provides cloud migration services. It helps its clients move legacy applications to the cloud by offering cloud migration and integration services, along with data migration and management. Chetu tailors its service delivery and pricing. 
  • Adastra: A data and analytics consulting firm that also offers cloud migration services. It focuses on migrating data warehouses and analytics platforms to the cloud. Adastra offers data migration, cloud data warehouse implementation, cloud strategy and consulting, and managed cloud services. It has customized pricing.
  • Onica: A cloud consulting and managed services provider that offers a full range of cloud migration services, from pre-migration assessment to post-migration optimization. It helps businesses optimize their cloud infrastructure and implement best practices for cloud operations. Onica’s pricing is tailored to the client’s project requirements. 

What Are the Benefits of Migrating to Google Cloud?

The benefits of a cloud migration to Google Cloud are scalability and flexibility, cost optimization, high performance and global reach, improved collaboration and simplified infrastructure management. Using the right Google Cloud migration tools is key to achieving these benefits.

  • Scalability and flexibility: These factors involve the ability to increase or decrease resources as your needs change. GCP’s infrastructure is designed for dynamic scaling. You can quickly scale up resources and storage to meet business demands with a few clicks or through automated policies. This ensures that web apps can efficiently handle traffic spikes.
  • Cost optimization: This refers to reducing IT expenses by paying for only the resources you use and taking advantage of flexible pricing models. GCP provides pricing options and discounts, which ensures that you only pay for the resources you use and enhances business logic. You can also use tools like the GCP pricing calculator to estimate costs and optimize your resource allocation. 
  • High performance and global reach: This factor ensures that your applications run quickly and are accessible to users worldwide. GCP has a vast network of data centers across the globe that allow you to deploy applications closer to your users, reducing latency and improving performance metrics.
  • Improved collaboration: Migrating to Google Cloud enables teams to work together more efficiently, regardless of location. GCP cloud storage and infrastructure makes data available anywhere you are, anytime you need it. People can access data all over the world from any device as long as they have an internet connection.
  • Simplified infrastructure management: GCP migration will reduce the complexity of managing your IT infrastructure so you can focus on your core business processes. Leveraging tools such as the Cloud Foundation Toolkit can help optimize resource allocation and automate infrastructure provisioning. This frees up your IT team to focus on strategic initiatives rather than routine maintenance.

What Are the Benefits of Migrating to GCP From AWS?

The primary benefits of migrating to GCP from AWS is better pricing and more advanced tools for data analytics and machine learning. GCP frequently provides more cost-effective pricing models, especially for sustained usage or long-term commitments. 

For data-driven businesses, GCP excels in data analytics and machine learning, with its powerful BigQuery platform and an array of AI and ML services. Additionally, for organizations already using Google Workspace, GCP’s easy and simple integration helps to streamline workflows and enhance productivity.

What Are the Benefits of Migrating to GCP From Microsoft Azure?

The main benefits of moving from Microsoft Azure to GCP includes more flexible pricing, advanced data analytics and better integration with Google Workspace.

GCP’s granular pricing model is more flexible, which could lead to lower cloud costs. Its advanced data and analytics tools, such as BigQuery, cater to organizations looking for powerful data processing and machine learning capabilities. For companies using Google Workspace, GCP’s infrastructure offers better integration.

Final Thoughts

Migrating to Google Cloud Platform can be a challenging task. However, with the right tools and services, this process can be seamless and highly beneficial. Whether using the native Google Cloud migration tools through the GCP console or leveraging third-party solutions, organizations can find tailored options to meet their specific needs.

As you consider your migration journey, what challenges do you foresee? Which tools do you think will be the most effective for your organization? Have you used any of the tools we mentioned? How did they affect your migration process? Please share your thoughts in the comments section below. Thank you for engaging with our article, and we look forward to your insights.

FAQ: GCP Migration Tools 

  • Google Cloud migration tools include Migrate for Compute Engine, Storage Transfer Service, Transfer Appliance, BigQuery Data Transfer Service, Database Migration Service, Anthos, Cloud Data Fusion, Datastream, Dataflow and Cloud Run.

  • Google’s migration tool is called Google Cloud Migration Center. It streamlines the entire cloud journey by acting as a hub to manage the migration program from a physical data center or other cloud environment to GCP. It provides a centralized platform that integrates various tools and services from GCP, such as Google Cloud RaMP and Migrate to Virtual Machines.

  • Google Cloud migration is the process of migrating data, infrastructure and applications from an on-premises environment or other cloud provider to Google Cloud Platform.

  • There are several tools used for cloud migration, such as Migrate for Compute Engine, AWS Application Migration Service, Azure Migrate, NetApp Cloud Volumes ONTAP, DuploCloud, Carbonite Migrate, Corent MaaS and Turbonomic.

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