Azure Data Factory vs. Oracle Data Integrator (ODI)

Azure Data Factory is a great data integration tool for developing a cloud data platform, especially within the Azure ecosystem. Azure Data Factory is very good for the Data Ingestion part. It can work for simple data transformation with its Data Flow, but it will also need cluster configuration, and there is some cost. Also, it is an excellent tool for orchestrating data pipelines. But for complex data transformations, you may need to use technologies like Databricks and PySpark.

Incentivized

I tried various ETL tools and here is [where and] why I recommend Oracle Data Integrator. 1. When you want to process structured data from different databases - Teradata, Exadata, DB2, SQL, Oracle etc. 2. Oracle Data Integrator supports all platforms, hardware, and OS. This is a major advantage compared to other leading tools. 3. The ELT architecture giving a cutting edge performance over leading ETL tools. There is no need to align Oracle Data Integrator between source and target. ODI uses the source and target servers to perform complex transformations. 4. Speeds up the development and maintenance by reducing the code that developers need to write

Incentivized

• It allows copying data from various types of data sources like on-premise files, Azure Database, Excel, JSON, Azure Synapse, API, etc. to the desired destination.
• We can use linked service in multiple pipeline/data load.
• It also allows the running of SSIS & SSMS packages which makes it an easy-to-use ETL & ELT tool.

Incentivized

• Converts data from various sources into one target format using various business logic rules and integrates with various DBMS types.
• Transformed data from DB2, SQL Server and other Oracle databases into flat files and then used ETL jobs to load into Oracle DB target
• Data Integrator and Goldengate were used together to accomplish the data movement needed for business and data consolidation in live environment. Data Integrator helped with development and in reducing lead time to convert data into target.

Incentivized

• Limited source/sink (target) connectors depending on which area of Azure Data Factory you are using.
• Does not yet have parity with SSIS as far as the transforms available.

Incentivized

• Oracle support is not the best when needing help with the system
• The documentation is also very poor and takes very long to generate
• Some parts of it are not intuitive to use and get hard to troubleshoot
• Like other Oracle products, you must have very, very thorough knowledge about their systems to understand
• Like all Oracle products, cost is high

Incentivized

It is maturing and over time will have a good pool of resources. Each new version has addressed the issues of the previous ones. Its getting better and bigger.

So far product has performed as expected. We were noticing some performance issues, but they were largely Synapse related. This has led to a shift from Synapse to Databricks. Overall this has delayed our analytic platform. Once databricks becomes fully operational, Azure Data Factory will be critical to our environment and future success.

Incentivized

We have not had need to engage with Microsoft much on Azure Data Factory, but they have been responsive and helpful when needed. This being said, we have not had a major emergency or outage requiring their intervention. The score of seven is a representation that they have done well for now, but have not proved out their support for a significant issue

Incentivized

Azure Data Factory is more of a universal pipeline. SAP BW is a tool offering good SAP connectivity but very limited third-party connectivity. The same is the case with BW4hana. SAP Datasphere is offering better connectivity with SAP sources, but not so good when compared to adf. Power Center of Informatica is a legacy tool, and Anaplan is a planning tool with limited connectivity options.

Incentivized

Talend Data Integrator has been evaluated during the setup of the architecture for a customer, in comparison to ODI, since it's an open source ETL. But, differently from the meaning of "open source", it has licence costs too that aren't that different from ODI ones. Moreover, the other components of the business intelligence architecture of the customer were Oracle, so we thought that ODI would suit at best with them, more than a different vendor software.

Incentivized

• Cost Savings: By automating our ETL processes with Azure Data Factory, we've reduced manual data handling by approximately 60%. This translates to savings from reduced man-hours and the overhead of maintaining legacy systems.
• Timeliness: Our report generation time has reduced by 70% with Azure Data Factory's scheduled pipelines. Faster insights mean quicker decisions for us, enabling our teams to capitalize on time-sensitive opportunities. We can easily share the data visualizations to all stakeholders.

Incentivized

• Oracle Data Integrator helps provide a business with the data it needs to defend the decisions it makes.
• Oracle Data Integrator allows you to analyze data from what can be separate, different, and often outdated data sources. It allows you to make direct comparisons when analyzing data from different pieces of equipment.
• Data from Oracle Data Integrator was used to analyze manufacturing quality and drive down spoilage, saving the company money.

Incentivized