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 advocate using Glue in such cases.
AWS's documentation is reliable, and careful reference often resolves missed upgrade details.
I can get solutions quickly, and any tickets I submit to Oracle are responded to and resolved rapidly.
It can easily handle data from one terabyte to 100 terabytes or more, scaling nicely with larger datasets.
It is beneficial to upgrade jobs, and we conduct extensive testing in development before migrating to production.
AWS Glue is highly stable, and I would rate its stability as nine.
Migrating jobs from version 3.0 to 4.0 can present compatibility issues.
With AWS, I gather data from multiple sources, clean it up, normalize it, de-duplicate it, and make it presentable.
A more user-friendly and simpler process would help speed up the deployment process.
If I use a source system like Oracle and a target system like Teradata, ODI will still run, but it struggles a bit with different infrastructures.
The smallest cost for a project is around €700, while the largest can reach up to €7,000 based on the scale of the usage.
AWS charges based on runtime, which can be quite pricey.
Costing depends on resource usage, and cost optimization may involve redesigning jobs for flexibility.
ODI is cheaper compared to Informatica PowerCenter and IBM DataStage.
AWS Glue's most valuable features include its transformation capabilities, which provide data quality and shape for processing in ML or AI models.
For ETL, I feel the performance is excellent. If I create jobs in a standard way, the performance is great, and maintenance is also seamless.
I think if I'm working with big data, common languages like Python work quite nicely, which is advantageous.
Oracle Data Integrator (ODI) is powerful and strong if my system uses Oracle components for environments like OLTP, enterprise data warehouse, or data marts.
AWS Glue is a serverless cloud data integration tool that facilitates the discovery, preparation, movement, and integration of data from multiple sources for machine learning (ML), analytics, and application development. The solution includes additional productivity and data ops tooling for running jobs, implementing business workflows, and authoring.
AWS Glue allows users to connect to more than 70 diverse data sources and manage data in a centralized data catalog. The solution facilitates visual creation, running, and monitoring of extract, transform, and load (ETL) pipelines to load data into users' data lakes. This Amazon product seamlessly integrates with other native applications of the brand and allows users to search and query cataloged data using Amazon EMR, Amazon Athena, and Amazon Redshift Spectrum.
The solution also utilizes application programming interface (API) operations to transform users' data, create runtime logs, store job logic, and create notifications for monitoring job runs. The console of AWS Glue connects all of these services into a managed application, facilitating the monitoring and operational processes. The solution also performs provisioning and management of the resources required to run users' workloads in order to minimize manual work time for organizations.
AWS Glue Features
AWS Glue groups its features into four categories - discover, prepare, integrate, and transform. Within those groups are the following features:
AWS Glue Benefits
AWS Glue offers a wide range of benefits for its users. These benefits include:
Reviews from Real Users
Mustapha A., a cloud data engineer at Jems Groupe, likes AWS Glue because it is a product that is great for serverless data transformations.
Liana I., CEO at Quark Technologies SRL, describes AWS Glue as a highly scalable, reliable, and beneficial pay-as-you-go pricing model.
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:
Oracle Data Integrator Benefits
There are many benefits to implementing ODI. Some of the biggest advantages the solution offers include:
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."
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