AWS Database Migration Service helps users migrate databases to AWS. The source database remains fully operational during the migration to minimize downtime to applications that rely on the database. The vendor states that AWS Database Migration Service can migrate data to and from most widely used commercial and open-source databases.
N/A
ER/Studio
Score 9.9 out of 10
N/A
ER/Studio is a database development and management tool from Embarcadero Technologies (acquired by Idera) in California.
$2,687
per year per user
Komprise
Score 10.0 out of 10
N/A
Komprise is the database development and management solution from the company of the same name in Campbell, California.
N/A
Pricing
AWS Database Migration Service
ER/Studio
Komprise
Editions & Modules
No answers on this topic
Standard
$2,687
per year per user
Professional
$3,693
per year per user
Enterprise
Custom
per year per user
No answers on this topic
Offerings
Pricing Offerings
AWS Database Migration Service
ER/Studio
Komprise
Free Trial
No
No
No
Free/Freemium Version
No
No
No
Premium Consulting/Integration Services
No
Yes
No
Entry-level Setup Fee
No setup fee
No setup fee
No setup fee
Additional Details
—
Pricing for new customers only, first year maintenance included. Maintenance includes access to technical support and product updates for the defined period of the agreement.
As stated previously, AWS Database Migration Service excels when replicating very specific data elements between environments. AWS Database Migration Service handles replication tasks to load equipment assets or customer job sites from production to QA databases very well. Full load replication - e.g., we need an exact copy of the production database in another region - works well. But when we need to load the QA database with the latest production data - it does work as well. AWS Database Migration Service comes up short because we do not want to wipe the QA database completely and make an exact copy. We want to keep what's already in the QA database and add production data so that we can QA with that level of volume. And at least with our database design, we end up having to do a lot of manual data manipulation and de-duplication.
Data Architect is well suited at organizations of all sizes. It is never too early or unnecessary to enforce proper modelling and design standards on data solutions, and this tool will help that greatly by providing an industry leading data modelling tool, ability to import ETL mappings for data lineage, enforcing and managing naming conventions through the naming convention tool, and publishing of data dictionaries through the report publisher. I was successfully able to build models, provide traceability, and document source to target with lineage throughout for both the business (by providing business definitions in the descriptions), and technical teams (by documenting ETL instructions in text fields) along with field level mapping (by creating "Attachments" representing data sources, tables, and fields) providing easy search capabilities using business friendly terms
As any other archiving solution, it is very well suited for environments with a large footprint of unstructured data (CIFS / NFS shares for user data) with a large amount of unused/old files and a need to keep those unused files for long term. In our scenario, due to some legal and contractual constraints we need to keep these files for 15 years. Archiving is a good choice to move the unused files to a cheaper storage tier, both on-prem or cloud.
ER/Studio has the ability to provide consistent field names and data types through domains, which are templates. This provides a way to have consistent naming of common fields, like CreatedBy and the data types for the fields. They also have the ability to change all the fields that use that domain to a different data type.
ER/Studio provides the ability to create custom macros. These macros can be used to apply everything from standard fields based on domains to naming all constraints and indexes. I've also used a macro that comes with ER/Studio to spell check field and table names.
My favorite feature is the ability to compare your data model to databases for deployments of changes, and to other data models.
ER\Studio licensing can be cumbersome and upgrading from one version to another usually takes several phone calls and emails to the licensing group to get the update installed and running.
The repository can be slow when the model count gets larger. By large I mean 20 to 30 models.
A nice feature that I would like to see is table comments be displayed on the model along with the attributes. Currently you have to choose between the two.
I can call or email support and both get quick turn around. The only issue is they are on the west coast (US) and have a west coast work schedule and I'm on the East coast.
We have used Veritas Enterprise Vault in the past, and besides its being a well-known player on the data archiving market, their tool is far more complex to implement, to manage and to keep working. Komprise is very robust and also very easy to implement, as most part of the job is done on Komprise side. The management console is delivered through a public URL as a SaaS platform. You only need to deploy a few VMs for scan/archiving/user access, which they call "Observer VMs." Komprise also doesn't uses Stub files, which is a poor implementation adopted by the competitor for file access. We had a lot of issues in the past with stub files. Komprise has implemented 'bread crumbs', which are CIFS symlinks to the files on the Observer. It is a very good implementation and it works really well.
ER/Studio has had a positive impact on my project as we can develop the data model and have a clear understanding of business needs before we continue with the development phase.
