10 Best Data Migration Tools

Nowadays, most businesses are implementing data-driven decisions for their growth. For seamless performance and stability, processes like data replication and data migration need to be in place. Data migration allows organizations to move their data from one data warehouse to another. You may need to migrate data for various reasons, for example, to create a replica of data in another cluster (a set of servers that are interconnected to each other is known as a cluster), to balance the current workload between multiple clusters, create a new data warehouse, upgrade databases, move a data warehouse to the cloud, etc. For smaller workloads, the data can be migrated physically using an SSD or HDD. Another better alternative for data migration is via the cloud.

Table of contents

  1. What Is Data Migration?
  2. Different Types of Database Migration Tools
  3. Cloud Data Migration Tools Pros and Cons
  4. Open Source Migration Tools Pros and Cons
  5. On-Premise Data Migration Software Pros and Cons
  6. Data Migration Best Practices
  7. Conclusion

What Is Data Migration?

Data Migration is the process of transferring the data from one location or storage system to another system. It is generally a one-time process that may include extracting and transforming the data as well. For migration of data, multiple components are involved in the process. Although there is a general misconception that data replication, data integration, and data migration are similar processes, they are different in reality. The below table attempts to clear the air for the readers.

Database Migration Tools

Data migration tools provide clients with a platform for transferring the data from one data cluster or server to another. The users can migrate the data from databases or transfer the data to a file and then move it to the server. The data migration activities are usual in data centers where the data is stored, managed, and replicated for disaster recovery. Such data migration tools prove to be very useful in such scenarios. The database migration software can also connect with CRM and other applications to migrate application-related data to the data warehouse. It can connect with on-premise data storage like HDFS to migrate the data to a cloud-oriented data storage like AWS. To migrate the data, these big data migration tools allow a connection with several databases. Some users might have to write code to transform the data and then transfer the data to the target location.

Different Types of Database Migration Tools

There are three types of data migration tools: cloud-based, on-premise and open-source tools. Let’s consider each of type separately.

4 Best Cloud-based Migration Tools

Cloud-based tools are hosted on a cloud server that can be accessed through the Internet. These tools use their servers to compute and transfer the data as needed by clients. Some of the cloud-based data migration tools are listed below:

  • Fivetran is an automated data integration platform that provides 150+ connectors to connect with different data sources. It provides ETL features along with data integration, data replication, and migration. It does not provide a free version of the tool but provides a trial period of 14 days upon signing up on the platform. The commercial versions come in four forms — Starter, Standard, Enterprise, and Custom. The pricing starts from 1 USD per credit for the Starter pack to 2 USD per credit for the Enterprise pack. Here, credit corresponds to the monthly active rows observed by the vendor.
  • Xplenty as a part of Integrate.io is a data integration platform that connects with multiple data sources for data integration. Integrate.io is specially designed as a data warehouse integration platform for e-commerce solutions. It offers more than 100 connectors to integrate the data between systems. Apart from the ETL capabilities, it also features real-time data replication, performance monitoring, providing API services, etc. The pricing is not disclosed on the platform but it provides a 7-day trial period.
  • AWS Data Pipeline provides various tools that serve different purposes. AWS data pipeline concentrates on transferring and processing the data between different AWS storage services and other data sources, including on-premise databases. It provides a web service for the users for reliable processing and movement of the data at regular intervals. It offers a free tier for the users to run 3 preconditions or 5 activities for each month. The pricing is based upon two factors: the frequency of preconditions or activities to be used, whether these are to be run on AWS or on-premise.
  • Skyvia is a complete cloud-oriented data management platform. It can integrate with a wide range of databases, whether on-premise or on the cloud. It also provides features like data replication, data management, data migration, persistent backup for disaster recovery, etc. It provides around 100 connectors to process the data and perform data-related tasks. These connections can be easily made on the platform via Skyvia’s no-code wizard-based user interface. Skyvia provides a free version that can process 5k records per month or 100k records of importing/exporting of CSV files. Skyvia Data Integration’s paid services come in 4 different commercial packs — Basic, Standard, Professional, and Enterprise. The annual pricing starts from $15 per month allowing 25k records to be processed per month to $799 per month which allows 50M records to be processed per month. More details regarding the pricing and the usage of these packages can be found on this link.

 3 On-premise Migration Tools

On-premise data migration tools are designed to migrate the data between the servers that reside within the organization’s network. These tools are generally commercialized by the vendor. Examples of such tools are shown below:

  • Informatica PowerCenter is primarily an ETL tool that is used to extract, load, and transform data from multiple sources. It also provides features like data migration, data integration, data governance, etc. It can connect with a vast range of databases to process the data. However, they are planning to modernize their current architecture by replacing the PowerCenter with Informatica Intelligent Cloud Services (IICS). They are providing a cloud trial for a time period of 30 days. After that, the pricing of IICS is based upon the Informatica Processing Units (IPUs) being bought. These are nothing but units of software capacity. These units can be scaled up and down based upon the customer’s requirements and can be used for a wide range of services.
  • Talend Data Fabric provides multiple solutions as a part of its data integration services. It allows connecting from most of the data sources and managing the data cluster on-site as well as on the cloud. It provides features like data cleaning, data governance, data integration, etc. It provides over 1,000 connectors to choose from and process the data. It provides a trial version when you submit your personal details. The pricing of the tools is not disclosed, and you need to contact sales support for further information.
  • Oracle Data Integrator is a data integration platform that can be used for all data integration services. It can connect with multiple sources to perform multiple tasks like data synchronization, data quality, data management, etc. Moreover, it, being a product of Oracle, also enables easier integration with other products of Oracle like Oracle GoldenGate, etc. It provides documentation for getting started on the software. It does not provide a free version of its software and the pricing of the tool i.e. Data Integrator Enterprise Edition is around 30,000 USD.

3 Best Open Source Migration Tools

Open source tools are free-of-cost tools that are publicly available to all users. These tools are used by the organizations having technically skilled resources for maintaining the software. Below you can find popular data migration tools that are open-sourced:

  • Apache Nifi serves as a data logistics platform that allows the real-time movement of data from various data systems. Along with the movement of data, it also transforms the data in real-time. It is built to automate the flow of data between multiple systems. The user interface represents the flow in the form of directed graphs that are easy to understand, modify, and monitor. It allows the flow of these graphs to be changed at runtime itself making it more configurable.
  • Airbyte is a data integration and ELT platform that can connect with multiple sources through its connectors. It can be used to integrate data as well as to migrate data between systems. It provides around 150 connectors that can be used for migrating the data. It also provides a development kit to create custom connectors. The tool comes in the form of an open-sourced version as well as a commercialized cloud version. The commercial tool is currently available only in the United States of America.
  • Apache Airflow is essentially a tool, which is used to provide data pipelining solutions and to run and monitor daily workflows. These workflows are represented using Directed Acyclic Graphs (DAGs) that are easy to run and monitor. It allows creating workflows in python that can move the data between systems through different operators. Apart from moving the data, it can also connect with the popular data sources that allow the data to be migrated between different databases.

Cloud Data Migration Tools

The cloud data migration tools allow data to be migrated via the cloud. These tools can serve as a platform to transfer the data and also can store the data on their cloud servers. The data that resides on the cloud servers are managed by the organization through the web interface provided by the platform. These tools can connect with various popular data streams and sources to move the data to the cloud. Many organizations use the data migration tools to move their on-premise data to the cloud platforms as they provide easy availability of the resources and allows the organizations to grow their architecture efficiently. Many esteemed organizations like Oracle and Amazon (AWS) have hosted their services on the cloud. The data migration tools can connect with such services to help in migrating the data to the cloud.

Cloud Data Migration Tools

PROS

  • Some tools follow a record-based pricing model that might lead to better pricing than the on-premise tools.
  • The cloud tools provide high availability and efficient scalability.
  • They keep replicated data in place for disaster recovery.

CONS

  • Data security can be compromised when stored on cloud servers.
  • Due to security compliance, some organizations’ policies might not allow the data to be stored or transferred over the cloud. Organizations are reluctant to migrate the data to the cloud due to a lack of reliability.
  • Accessing the data through the cloud will require high-speed internet access.

Open Source Migration Tools

The open source migration tools are driven by the developers’ community who work together to create and improve the tools. The source code of these tools is typically available on a central repository like git. Some licensed tools also make use of these source codes as the underlying code for their software. The open source data migration tools allow data to be migrated between different data systems at no cost. The users can also modify or contribute to the open source code. These tools are suitable for tech-savvy people that can understand the open source code and implement the changes if required.

Open Source Migration Tools

PROS

  • The tools are free to use.
  • As the source code is available freely, it can be modified as per the requirement.
  • Community-driven support allows the developers to get assistance.

CONS

  • Technically skilled human resources are required to use these tools.
  • No assurance of receiving required support.
  • There is a possibility of the tools getting deprecated for use.

On-Premise Data Migration Software

The on-premise data migration tools are deployed within the same network and help in migrating the data without using the cloud. Such tools are used by organizations that do not allow the data to be uploaded on the cloud for security restrictions. The license of on-premise data migration tools needs to be procured to make use of them as they are commercialized.

On-Premise Data Migration Software

PROS

  • As the software is deployed within the same network, latency could be less.
  • The security of the data can be maintained by the internal team.
  • Internet access is not required for operating the tools

СONS

  • It is relatively difficult to scale and manage the tools.
  • Required support might not be available at all times.
  • Storage costs can be expensive.

Data Migration Best Practices

Below you can find the best practices to keep in mind while implementing the data migration plan:

  • Strategize the data migration plan thoroughly and check if there are any constraints in implementing the plan. Layout a diagram for understanding the sources and destinations.
  • Check for any data issues before the migration of the data. Remove or transform the data if any issues are present.
  • Try to implement the data migration in a replica of the target location. Testing the data migration plan is very crucial before its implementation.
  • Create a backup of the data before proceeding with the data migration. This assures disaster recovery is in place.
  • Make sure the required storage space is available in the target location for storing the data.
  • If there are any network-related constraints, try to create chunks of the data before moving it to the target location.
  • Reassess the data after the data migration is completed to make sure there is no data loss.
Data Migration Best Practices

Conclusion

One of the most critical components of any data migration activity is proper planning. Many factors are to be considered during this activity like the number of sources and destinations, maintaining the integrity of the data, etc. Choosing a data migration tool is a vital step in the planning process. One should check whether the sources and destinations can be connected via the tool, and whether it supports the magnitude of the data to ensure the data migration process goes efficiently. The decision depends on the use case of the organization.

Prathamesh Thakar
Prathamesh Thakar
Associate Data Science
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