Oracle Data Integrator vs Talend Data Integration

• Oracle Data Integrator nearly addresses every data issue that one can expect. Oracle Data Integrator is tightly integrated to the Oracle Suite of products. This is one of the major strengths of Oracle Data Integrator. Oracle Data Integrator is part of the Oracle Business Intelligence Applications Suite - which is highly used by various industries. This tool replaced Informatica ETL in Oracle Business Intelligence Applications Suite.
• Oracle Data Integrator comes with many pre-written data packages. If one has to load data from Excel to Oracle Database, there is a package that is ready available for them - cutting down lot of effort on writing the code. Similarly, there are packages for Oracle to SQL, SQL to Oracle and all other possible combinations. Developers love this feature.
• Oracle Data Integrator relies highly on the database for processing. This is actually an ELT tool rather than an ETL tool. It first loads all the data into target instance and then transforms it at the expense of database resources. This light footprint makes this tool very special.
• The other major advantage of Oracle Data Integrator, like any other Oracle products, is a readily available developer pool. As all Oracle products are free to download for demo environments, many organizations prefer to play around with a product before purchasing it. Also, Oracle support and community is a big advantage compared to other vendors.

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• JSON parsing, if you are into highly nested JSON object parsing Talend has the ability to display the structure of JSON and allows you to define the extraction logic in the metadata. Same with XML source.
• Customization, For mostly all ETL work you will have a component in Talend. And in case you have a very specific requirement you can end up easily designing a custom component that you can code and reuse and share with others.
• Talend has a connectivity option to almost all the databases (relational or NOSQ)L and sources available. It also has generic JDBC/ ODBC drivers in case you need it.
• I like the ease of deployment across environment (DEV and PROD) with the use of context variables.

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• ODI does not have an intuitive user interface. It is powerful, but difficult to figure out at first. There is a significant learning curve between usability, proficiency, and mastery of the tool.
• ODI contains some frustrating bugs. It is Java based and has some caching issues, often requiring you to restart the program before you see your code changes stick.
• ODI does not have a strong versioning process. It is not intuitive to keep an up to date repository of versioned code packages. This can create versioning issues between environments if you do not have a strong external code versioning process.

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• Syncing with Git should be made easier
• Can face issues with certain big data spaces
• Support find it difficult to resolve complex issues

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• Lead time to complete data integration and transformation project was reduced due to Oracle Data Integrator tools that helped in setting up transformations relatively quickly once it was set up.
• Reduced lead time helped in reducing project cost as less resources were spent in data conversion project.
• Overall data consolidation project resulted in quick integration of data from varied DBMS and data sources.

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• Easy to build complex data transformations.
• Licensing model isn't that flexible.
• Memory mangement for huge volumes of information. You have to modify ETL designs to handle it properly.

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