Matillion vs Oracle Data Integrator

• The workspace is drag and drop, which makes it intuitive and easy to use.
• Server creation and management is robust. We haven't had to worry too much about it once we got it created.
• The job scheduler is very simple and intuitive.
• Matillion allows you to run Python, which grants almost unlimited flexibility, even without using any other components.

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• 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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• Limited selection of instance sizes - Larger organizations and groups my need to set up multilple instances depending on estimations on concurrent users.
• Lack of complete github, gitlab, or other source control integration - it has internal versioning but it is limited. Manual job exports currently don't lend well for useful DIFFs comparison when using those technologies.
• Needs more options for authentication and security - User creation is very manual and can be tedious and difficult to manage for larger installations.

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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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• Matillion has dramatically decreased the time it takes to create new ETL
• Matillion has reduced the amount of time it takes to execute our daily ETL processing (by 50% or more)
• Matillion has increased the number of people who can develop ETL by making ETL development easier
• Matillion has increased the variety of data sources we can bring into our data warehouse
• Matillion has made it a little harder to manage source control and deployment

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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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