Find out in this report how the two Cloud Data Integration solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.
I can specify savings of around 40 to 60%.
Using SSIS has proven cost-effective as there are no additional fees outside the SQL Server license, and it significantly enhances data management efficiency.
I am happy with the technical support from AWS.
When working with AWS GovCloud, we often did not get an answer in time because AWS seemed more focused on the commercial side.
Even if there was a failure, we could catch it and rerun it.
AWS's scalable nature involves a human approach, meaning it is not auto-scalable.
While scalability is good, latency exists due to our business nature.
Minor version upgrades are handled by DMS automatically.
It processes large volumes of data quickly.
DMS works within AWS ecosystem, but they also have to look for third party solutions. Now Snowflake is a bigger player, or Databricks.
Sometimes, those who implement the service face problems and resolve it, but I may not even know what problems they faced.
Within the South African context, if you are getting your enterprise agreement from First Technology, they don't provide support.
SSIS has a difficult learning curve when dealing with complex transformations.
Utilizing SSIS involves no extra charges beyond the SQL Server license.
You can copy the database at first without impacting your current database, and then use CDC to copy incremental changes.
AWS offers a way to build jobs that are scalable, expandable for new and current tables, and can be deployed quickly.
The scalability option is another valuable feature because AWS provides its own compute behind it, so I can scale up and scale down at any given point.
One of the best aspects of SSIS is that it is built into Microsoft SQL Server, so there are no additional costs involved.
The challenge lies in Microsoft withdrawing a lot of the qualifications and watering down its emphasis, leading to a perception that this is supposed to be an elite product.
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:
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:
AWS Database Migration Service Benefits
AWS Database Migration Service offers its users a wide range of benefits. Among them are the following:
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.
SSIS is a versatile tool for data integration tasks like ETL processes, data migration, and real-time data processing. Users appreciate its ease of use, data transformation tools, scheduling capabilities, and extensive connectivity options. It enhances productivity and efficiency within organizations by streamlining data-related processes and improving data quality and consistency.
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