Discovering the ideal data migration service is paramount in today’s dynamic cloud landscape. While AWS Data Migration Service offers a robust solution, it may slow down when moving enormous volumes of data. So, exploring alternatives can be helpful to you for diverse business needs. From seamless database transfers to efficient data synchronization, each tool empowers you to replicate data with agility and precision. By delving into the unique features of these substitutes, you can make informed decisions while capitalizing on the flexibility and reliability of these services.
In this article, you will learn about AWS Data Migration Service, its benefits, limitations, and the alternative services for streamlined data transfer.
AWS Data Migration Service Overview
AWS Data Migration Service (AWS DMS) is a cloud service by AWS that helps you migrate data across 20+ databases and analytic engines. It allows you to actively manage data replication to AWS, ensuring fast and secure migration of your database and analytical workloads with zero data loss. DMS supports various data types, such as relational database structures, NoSQL data formats, semi-structured documents, large objects (LOBs), and primitives like integers, floats, strings, dates, and booleans.
AWS ETL tools, such as AWS DMS offer capabilities extend beyond one-time data migration, allowing for continuous data replication. It operates by gathering changes from the database logs through the native API of the database system. This enables you to handle ongoing changes effectively, synchronizing source and target.
Benefits of Using AWS Data Migration Service
Here are some advantages of using AWS DMS:
Ease of Use
While using AWS DMS for data integration, you don’t have to install any drivers or applications. Initiating a data migration is as simple as a few clicks using the AWS Management Console.
Downtime is Minimal
You can seamlessly transfer your databases to AWS with AWS DMS, ensuring minimal downtime. It maintains continuous replication of all data changes from the source database to the target, enabling full operational functionality of the source database throughout the migration process.
Limitations of AWS Data Migration Service
Here are some of AWS DMS's limitations that initiate you to choose other alternatives.
Large Data Volumes
Migrating extensive or full-load data can be challenging when using AWS DMS. During this process, it uses resources from your source database.
Sync Issues
Sometimes, a discrepancy arises between the source and the target database, known as sync lag. This occurs due to interruptions in the replicating process, causing a ripple effect in the entire dataset of the target database. As a result, important changes in the source might not be detected in the target database.
Limited Support for Certain Databases
AWS DMS supports an array of databases. However, it is important to note that certain databases and versions are not fully supported. Examples include legacy or proprietary databases with closed ecosystems, niche or specialized databases, and some older versions of mainstream databases.
Best 5 Alternatives for AWS Data Migration Service
Here are the top five alternatives for AWS DMS.
Airbyte
Airbyte is a data integration platform that helps you synchronize data from various sources to destinations such as data warehouses, lakes, databases, and more. It offers an extensive set of over 350+ pre-built connectors for seamless integration. If you don’t find your specific connectors, you can leverage its Connector Developer Kit (CDK) to construct a custom one. In addition, Airbyte allows you to create specific pipelines according to your preferences. You can build pipelines using UI, custom code, or API.
Some of the key features of Airbyte are:
- Change Data Capture (CDC): Airbyte supports CDC functionality, enabling incremental data replication by capturing only the changes made to the source data, which enhances efficiency and reduces processing overhead.
- Security: Airbyte guarantees the security of data movement by implementing robust measures, including strong encryption, audit logs, role-based access control, and secure transmission of data.
- Handling Schema Changes: With Airbyte, you have the flexibility to manage schema changes for each transfer. It ensures the robustness of the data migration process, even in situations where the source schema undergoes continuous evolution.
- Multiple User Access: You can create a collaboration in Airbyte with multiple users on a single instance, using Single Sign-On (SSO) and role-based access control (RBAC) for streamlined user management. This approach ensures smooth scalability, allowing you to effortlessly expand into multiple workspaces to meet the needs of larger teams.
Oracle GoldenGate
Oracle GoldenGate empowers you to replicate, filter, and transform data seamlessly. You can migrate data between Oracle and other supported heterogeneous databases. It also facilitates you to move data to Java Messaging Queues and Big Data targets by integrating with Oracle GoldenGate for Big Data.
Some of the significant features of Oracle GoldenGate are:
- Reduce Downtime: It helps you operate your system uninterruptedly during activities such as routine database maintenance, application updates, and migrations to new platforms. You can safeguard all your operations using the failback capabilities that minimize the risk of data loss, ensuring a secure and reliable process for handling these activities without experiencing downtime.
- End-to-end Monitoring: Oracle GoldenGate ensures you the service level agreement (SLA) commitment by employing data verification techniques and gaining real insights into performance and usage statistics across all sources and targets. This focuses on end-to-end monitoring, assuring reliability and accountability.
Fivetran
Fivetran is an automated data integration platform that has the flexibility to work with either cloud or on-premise infrastructure. It has over 400 built-in, no-code source connectors for migrating data from various sources to your destinations. If it does not support any custom data source or private API, you can develop a custom connector with the help of its Function connector.
Some of the key features of Fivetran are:
- Security: Fivetran enhances data security, safeguarding sensitive information like Personally Identifiable Information (PII) through features such as column blocking and hashing. Column blocking restricts specific replication-required columns, while column hashing protects PII data before transferring it to the target file. These measures minimize the risk of data exposure, providing you with greater control over your data.
- Transformation: You can manage complex transformations in Fivetran by integrating with the dbt core, a freely available tool designed to simplify transformations.
💡Suggested Read: Fivetran Competitors
Azure Migrate
Microsoft’s Azure Migrate is a cloud-computing platform that allows you to evaluate and effortlessly move your on-premises data or applications to the Azure cloud. It provides integrated features and assessment tools like server and database assessment, data migration assistance, and more. With the help of these tools, you can streamline the migration journey and enhance the efficiency of workloads within the Azure environment. The extensible framework also supports the integration of third-party tools, broadening the range of use cases it can handle.
Some of the significant features of Microsoft Azure are:
- Discovery and Assessment: Azure Migrate serves as a centralized hub to monitor and manage the discovery, assessment, and migration process of on-premise infrastructure and applications. It also provides tools for discovering on-premise resources and evaluating their readiness for migration. Along with these offerings, Azure Migrate also supports third-party tools from Independent Software Vendors (ISVs).
- Developer Tools: It offers extensive development tools that cater to various programming languages and operating systems, simplifying the process for you to create and deploy applications.
Qlik Replicate
Qlik Replicate is a data integration and replication tool offered by Qlik. It enables you to ingest, replicate, and integrate data across a broad spectrum of heterogeneous databases, data warehouses, and big data platforms. It is known to securely synchronize data with minimal operational impact, often using the log-based CDC technology for continuous replication in the target systems.
Some of the amazing features of Qlik Replicate are:
- Monitoring and Control: Qlik Replicate helps you streamline your data management by utilizing a unified interface to create data endpoints and execute replication tasks. This empowers you to monitor thousands of tasks seamlessly through a single console, with user-defined alerts and Key Performance Indicators (KPIs).
- Optimize Data: With Qlik Replicate, you can enable low-impact, near real-time Change Data Capture (CDC) across various database systems, providing flexible choices for handling captured data changes. This allows you to optimize data ingestion by capturing only the appended data, ensuring your target system stays up-to-date.
💡Suggested Read: Qlik Competitors
Conclusion
Exploring the five best alternatives to AWS Data Migration Service uncovers a diverse set of solutions, each crafted to address specific needs. These platforms offer a spectrum of capabilities from robustness to flexibility and simplicity. If you are looking for options outside the AWS ecosystem, refer to the tools mentioned above. You can select a migration solution that aligns with your scalability requirements, ease of use, and budget constraints. This array of options will not only enhance data migration processes but also empower you to optimize data management in the ever-changing cloud environment. Ultimately, searching for suitable replacements for AWS DMS opens avenues for tailored solutions catering to the unique demands of modern data migration.
We recommend the user-friendly features of Airbyte, a tool with a diverse range of connectors and robust security measures. Simplify your workflows today with Airbyte’s open-source version for free!
💡Suggested Read: Data Migration Tools
What should you do next?
Hope you enjoyed the reading. Here are the 3 ways we can help you in your data journey:
Frequently Asked Questions
What is ETL?
ETL, an acronym for Extract, Transform, Load, is a vital data integration process. It involves extracting data from diverse sources, transforming it into a usable format, and loading it into a database, data warehouse or data lake. This process enables meaningful data analysis, enhancing business intelligence.
This can be done by building a data pipeline manually, usually a Python script (you can leverage a tool as Apache Airflow for this). This process can take more than a full week of development. Or it can be done in minutes on Airbyte in three easy steps: set it up as a source, choose a destination among 50 available off the shelf, and define which data you want to transfer and how frequently.
The most prominent ETL tools to extract data include: Airbyte, Fivetran, StitchData, Matillion, and Talend Data Integration. These ETL and ELT tools help in extracting data from various sources (APIs, databases, and more), transforming it efficiently, and loading it into a database, data warehouse or data lake, enhancing data management capabilities.
What is ELT?
ELT, standing for Extract, Load, Transform, is a modern take on the traditional ETL data integration process. In ELT, data is first extracted from various sources, loaded directly into a data warehouse, and then transformed. This approach enhances data processing speed, analytical flexibility and autonomy.
Difference between ETL and ELT?
ETL and ELT are critical data integration strategies with key differences. ETL (Extract, Transform, Load) transforms data before loading, ideal for structured data. In contrast, ELT (Extract, Load, Transform) loads data before transformation, perfect for processing large, diverse data sets in modern data warehouses. ELT is becoming the new standard as it offers a lot more flexibility and autonomy to data analysts.