AWS Database Migration Service vs IBM InfoSphere DataStage comparison

AWS Database Migration Service, also known as AWS DMS, is a cloud service that facilitates the migration of relational databases, NoSQL databases, data warehouses, and other types of data stores. The product can be used to migrate users' data into the AWS Cloud or between combinations of on-premises and cloud setups. The solution allows migration between a wide variety of sources and target endpoints; the only requirement is that one of the endpoints has to be an AWS service. AWS DMS cannot be used to migrate from an on-premises database to another on-premises database.

AWS Database Migration Service allows users to perform one-time migrations, as well as replications of ongoing changes to keep sources and targets in sync. Organizations can utilize the AWS Schema Conversion Tool to translate their database schema to a new platform and then use AWS DMS to migrate the data. The product offers cost efficiency as a part of the AWS Cloud, as well as speed to market, flexibility, and security.

The main use cases of AWS Database Migration Service include:

• Migrating from legacy or on-premises databases to managed cloud services through a simplified migration process.
  
  
• Reliable replication of backup files to minimize downtime and data loss.
  
  
• Improvement of integration through building of data lakes and performing real-time processing on change data from users' data stores.

AWS Database Migration Service Components

AWS Database Migration Service consists of various components which function together to achieve users’ data migration. A migration on AWS DMS is structured in three levels: a replication instance, source and target endpoints, and a replication task. The components include the following actions:

• Replication instance: AWS Database Migration Service provides users with a variety of replication instances, allowing them to select the optimal configuration for their use case. Depending on the instance class an organization selects, their replication instance provides a different amount of data storage.
  
  
• Endpoint: AWS DMS uses an endpoint to access users' source or target data stores. The connection information is different and depends on the specific data store, but it usually consists of the following information: endpoint type, engine type, server name, port, encryption, and credentials. This information can easily be managed through the AWS DMS console.
  
  
• Replication tasks: AWS Database Migration Service replication tasks can be used to move a set of data from the source endpoint to the target endpoint. The creation of a replication task is the last required step before starting a migration. Each replication task requires the following settings to be set: replication instance, source endpoint, target endpoint, and migration type options.
  
  
• Ongoing replication or change data capture (CDC): AWS DMS also has the capacity to capture ongoing changes to the source that is stored while users migrate their data to a target.
  
  
• Schema and code migration: The product requires assistance from tools such as MySQL Workbench, pgAdmin III, and Oracle SQL Developer to perform schema or code conversion, as it cannot do it on its own.

AWS Database Migration Service Benefits

AWS Database Migration Service offers its users a wide range of benefits. Among them are the following:

• The solution ensures minimal downtime, as it continuously replicates the changes to the user’s source database during migration.
  
  
• AWS DMS provides users with flexibility, as it supports many commonly used databases, including commercial and open-source ones.
  
  
• The product is user friendly, as it offers an easy set of tasks in the AWS Management Console.
  
  
• Users of Aurora, Redshift, DocumentDB, and DynamoDB can benefit from the free use of AWS DMS.
  
  
• AWS Database Migration Service is very reliable because it is a self-healing service that automatically restarts in cases of interruptions.
  
  
• The product supports both homogenous migrations and heterogenous migrations.
  
  
• AWS DMS accelerates business growth, as it scales businesses at an affordable price.

Reviews from Real Users

Vishal S., an infrastructure lead at a computer software company, likes AWS Database Migration Service because it is easy to use and set up.

Vinod K., a data analyst at AIMLEAP, describes AWS DMS as an easy solution to save and extract data.

IBM InfoSphere DataStage is a high-quality data integration tool that aims to design, develop, and run jobs that move and transform data for organizations of different sizes. The product works by integrating data across multiple systems through a high-performance parallel framework. It supports extended metadata management, enterprise connectivity, and integration of all types of data.

The solution is the data integration component of IBM InfoSphere Information Server, providing a graphical framework for moving data from source systems to target systems. IBM InfoSphere DataStage can deliver data to data warehouses, data marts, operational data sources, and other enterprise applications. The tool works with various types of patterns - extract, transform and load (ETL), and extract, load, and transform (ELT). The scalability of the platform is achieved by using parallel processing and enterprise connectivity.

The solution has various versions, catering to different types of companies, which include the Server Edition, the Enterprise Edition, and the MVS Edition. Depending on which version a company has bought, different goals can be achieved. They include the following:

• Designing data flows to extract information from multiple sources, transform the data, and deliver it to target databases or applications.
  
  
• Delivery of relevant and accurate data through direct connections to enterprise applications.
  
  
• Reduction of development time and improvement of consistency through prebuilt functions.
  
  
• Utilization of InfoSphere Information Server tools for accelerating the project delivery cycle.

IBM InfoSphere DataStage can be deployed in various ways, including:

• As a service: The tool can be accessed from a subscription model, where its capabilities are a part of IBM DataStage on IBM Cloud Park for Data as a Service. This option offers full management on IBM Cloud.
  
  
• On premises or in any cloud: The two editions - IBM DataStage Enterprise and IBM DataStage Enterprise Plus - can run workloads on premises or in any cloud when added to IBM DataStage on IBM Cloud Pak for Data as a Service.
  
  
• On premises: The basic jobs of the tool can be run on premises using IBM DataStage.

IBM InfoSphere DataStage Features

The tool has various features through which users can integrate and utilize their data effectively. The components of IBM InfoSphere DataStage include:

• AI services: The tool offers services such as data science, event messaging, data warehousing, and data virtualization. It accelerates processes through artificial intelligence (AI) and offers a connection with IBM Cloud Paks - the cloud-native insight platform of the solution.
  
  
• Parallel engine: Through this feature, ETL performance can be optimized to process data at scale. This is achieved through parallel engine and load balancing, which maximizes throughput.
  
  
• Metadata support: This feature of the product uses the IBM Watson Knowledge Catalog to protect companies' sensitive data and monitor who can access it and at what levels.
  
  
• Automated delivery pipelines: IBM InfoSphere DataStage reduces costs by automating continuous integration and delivery of pipelines.
  
  
• Prebuilt connectors: The feature for prebuilt connectivity and stages allows users to move data between multiple cloud sources and data warehouses, including IBM native products.
  
  
• IBM DataStage Flow Designer: This feature offers assistance through machine learning design. The product offers its clients a user-friendly interface which facilitates the work process.
  
  
• IBM InfoSphere QualityStage: The tool provides a feature that automatically resolves data quality issues and increases the reliability of the delivered data.
  
  
• Automated failure detection: Through this feature, companies can reduce infrastructure management efforts, relying on the automated detection that the tool offers.
  
  
• Distributed data processing: Cloud runtimes can be executed remotely through this feature while maintaining its sovereignty and decreasing costs.

IBM InfoSphere DataStage Benefits

This solution offers many benefits for the companies that utilize it for data integration. Some of these benefits include:

• Increased speed of workload execution due to better balancing and a parallel engine.
  
  
• Reduction of data movement costs through integrations and seamless design of jobs.
  
  
• Modernization of data integration by extending the capabilities of companies' data.
  
  
• Delivery of reliable data through IBM Cloud Pak for Data.
  
  
• Utilization of a drag-and-drop interface which assists in the delivery of data without the need for code.
  
  
• Effective data manipulation allows data to be merged before being mapped and transformed.
  
  
• Creating easier access of users to their data by providing visual maps of the process and the delivered data.

Reviews from Real Users

A data/solution architect at a computer software company says the product is robust, easy to use, has a simple error logging mechanism, and works very well for huge volumes of data.

Tirthankar Roy Chowdhury, team leader at Tata Consultancy Services, feels the tool is user-friendly with a lot of functionalities, and doesn't require much coding because of its drag-and-drop features.