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:
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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.
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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.
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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.
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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.
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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.
Informatica Cloud Data Integration is a cloud-native cloud data integration solution that enables users to connect a large number of applications and data sources across on-premises and integrate the data sources at scale on the cloud. The product is built on microservices-driven management and integration platform as a service (iPaaS) and assists organizations to govern costs, increase productivity and collaboration, and simplify their experience. Informatica Cloud Data Integration allows companies to deliver data and analytics to lines of business in a timely manner, build data warehouses on Amazon Redshift, Google Cloud BigQuery, Snowflake, and Microsoft Azure Synapse Analytics, and utilize the required data integration patterns, including elastic processing, extract, load, and transform (ELT), and extract, transform, and load (ETL).
The solution allows users to to build enterprise-scale integration workloads within hours while it improves the productivity of development teams by providing them a codeless, drag-and-drop user interface. Companies can benefit from integration features built for data warehousing and optimized connectors for bulk loads of billions of records. Informatica Cloud Data Integration offers organizations the option of going serverless at scale by allowing them to process data integration jobs from cloud-hosted as well as managed environments. The Spark-based engine allows the solution to handle high-volume data demands and complex data integration tasks.
Informatica Cloud Data Integration Features
Informatica Cloud Data Integration provides its users with various features and tools. Among the key capacities of the product are:
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Advanced Pushdown Optimization: Informatica Cloud Data Integration offers a feature that provides users with the benefits of ELT while maintaining their data flow definitions at a logical or abstract level. This feature allows users to choose a runtime option that complies with the workload as well as send their data processing work to cloud ecosystem pushdown, cloud data warehouse pushdown, Spark serverless processing, or traditional ETL.
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Connectors for all major data sources: This feature provides out-of-the-box connectivity to a large number of cloud and on-premise systems, data stores, analytics and BI tools, and enterprise and middleware applications.
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Data transformation capabilities: This feature allows users to process data transformation in real time or batch by using a variety of transformation types, such as cleansing, masking, aggregation, fileting, parsing, and ranking.
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Spark-based complex data integration: Informatica Cloud Data Integration Elastic allows specialists to use elastic clusters to process their data transformation.
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Codeless integration: This feature facilitates the creation of simple-to-sophisticated data integration projects with a visual mapping designer that speeds up pre-build transformations for development through a variety of endpoints across cloud and on-premises.
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Serverless data integration: Users can achieve cloud data integration in a mode called Advanced Serverless, where they can benefit from a fully managed environment with no software, no cloud administration, and no servers or clusters to manage.
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Taskflow orchestration: This feature allows users to combine batch and real-time integration through a taskflow designer in order to create simple-to-sophisticated orchestrations.
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Intelligent structure discovery: This feature uses the CLAIRE engine to automatically understand the parsing model for complicated files based on their structure.
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Change data capture: Utilizing the prebuilt task wizards and Change Data Capture tool, users can automatically pull only the updated or incremental data from source systems to the targets on a frequent basis.
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Security: The product offers various features which ensure the highest level of data and workload security and comply with various policies.
Informatica Cloud Data Integration Benefits
Informatica Cloud Data Integration brings multiple benefits to its users. These include:
- The product offers optimized connectivity to various systems through custom build-connectors.
- Users can benefit from improved elasticity and performance by utilizing Spark clusters and auto-tuning.
- The tool allows developers to focus on business logic by facilitating infrastructure management through serverless deployment features.
- Informatica Data Cloud Integration provides user flexibility by connecting to any database, cloud data lake, on-premise apps, and data warehouses.
- Through a zero-coding environment and role-appropriate user experience, the solution is suitable for all types of users.
- The solution offers consistent experience and unified metadata across all cloud services.
- Users can leverage enterprise-level performance for integration design with no coding required.
- Informatica Data Cloud Integration scales as a business grows, providing a high level of adaptability.
Reviews from Real Users
Divya R., a senior consultant at Deloitte, rates Informatica Cloud Data Integration highly because it is a UI-based tool with great scripting.
A data architect at a retailer likes Informatica Cloud Data Integration because of its flexible licensing, good connectors, and timely upgrades and patches.
Oracle Data Integrator (ODI) is a data integration software solution that provides a unified infrastructure to streamline data and application integration projects. It uses a powerful design approach to data integration, which separates the declarative rules from the implementation details. The solution is based on a unique ELT (Extract Load Transform) architecture, eliminating the need for a standalone ETL server and proprietary engine.
Oracle Data Integrator Features
ODI has many valuable key features. Some of the most useful ones include:
- Automatic documentation generation
- Visualization of data flows in the interfaces
- Customization of generated code
- Automatic reverse-engineering of existing applications or databases
- Graphical development and maintenance of transformation and integration interfaces
- Robust data integrity control features, assuring the consistency and correctness of data
- Powerful core differentiators
- Heterogeneous ELT, declarative design and knowledge modules
- Flexibility and modularity
- Oracle Data Integrator repository
- Topology navigator
- Operator Navigator
- Security Navigator
- Integrator Console
- ODI domains
Oracle Data Integrator Benefits
There are many benefits to implementing ODI. Some of the biggest advantages the solution offers include:
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Efficient architecture: Oracle Data Integrator has a simple architecture that utilizes the source and target servers to perform complex transformations, making it an efficient solution.
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Supports all platforms: ODI gives you platform independence by supporting all platforms, hardware, and OSes with the same software.
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Cost-effective: Oracle Data Integrator reduces costs associated with initial hardware and software acquisition, and also decreases maintenance costs because it eliminates the need for an ETL Server and an ETL engine.
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Automatic detection of faulty data: By using ODI, faulty data is recycled before insertion in the target application, providing you with a data quality firewall.
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Easy development and maintenance: With a low learning curve, Oracle Data Integrator increases developer productivity while facilitating ongoing maintenance.
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Active integration: ODI includes all styles of data integration: data-based, event-based and service-based.
Reviews from Real Users
Below are some reviews and helpful feedback written by PeerSpot users currently using the Oracle Data Integrator (ODI) solution.
Brian D., Business Process and Strategy Specialist Advisor at NTTData, says, “The Knowledge Module (KM) is my favorite feature of ODI. This is where I learned how to use variables to make jobs dynamic. I took that knowledge and created a KM that would go into iTunes and pull the sales of eBooks. Making something that is reusable, like a KM, is important to not only reduce build time but also maintenance in the future.”
Ashok S., Applications Support Manager at a marketing services firm, mentions, "The most valuable features of ODI are the ease of development, you can have a template, and you can onboard transfer very quickly. There's a lot of knowledge modules available that we can use. If you want to connect, for example, a Sibyl, SQL, Oracle, or different products, we don't have to develop them from scratch. They are available, but if it's not, we can go into the marketplace and see if there's a connector there. Having the connector available reduces the amount of hard work needed. We only have to put the inputs and outputs. In some of the products, we use there is already integration available for ODI, which is helpful."
Veoci, Trimble, Nasdaq, shaadi.com, Hotelbeds, SysAid, Verizon, Expedia, Pega
Chicago Cubs, Telegraph Media Group
Griffith University, Kansas City Power & Light, Keste, Raymond James Financial, Valdosta State University