Databricks offers the Databricks Lakehouse Platform (formerly the Unified Analytics Platform), a data science platform and Apache Spark cluster manager. The Databricks Unified Data Service provides a platform for data pipelines, data lakes, and data platforms.
$0.07
Per DBU
Oracle Data Integrator (ODI)
Score 7.6 out of 10
N/A
Oracle Data Integrator is an ELT data integrator designed with interoperability other Oracle programs. The program focuses on a high-performance capacity to support Big Data use within Oracle.
N/A
Pricing
Databricks Data Intelligence Platform
Oracle Data Integrator (ODI)
Editions & Modules
Standard
$0.07
Per DBU
Premium
$0.10
Per DBU
Enterprise
$0.13
Per DBU
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Offerings
Pricing Offerings
Databricks Data Intelligence Platform
Oracle Data Integrator (ODI)
Free Trial
No
No
Free/Freemium Version
No
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
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More Pricing Information
Community Pulse
Databricks Data Intelligence Platform
Oracle Data Integrator (ODI)
Features
Databricks Data Intelligence Platform
Oracle Data Integrator (ODI)
Data Source Connection
Comparison of Data Source Connection features of Product A and Product B
Databricks Data Intelligence Platform
-
Ratings
Oracle Data Integrator (ODI)
8.0
12 Ratings
3% below category average
Connect to traditional data sources
00 Ratings
8.012 Ratings
Connecto to Big Data and NoSQL
00 Ratings
8.010 Ratings
Data Transformations
Comparison of Data Transformations features of Product A and Product B
Databricks Data Intelligence Platform
-
Ratings
Oracle Data Integrator (ODI)
8.0
12 Ratings
1% below category average
Simple transformations
00 Ratings
8.012 Ratings
Complex transformations
00 Ratings
8.012 Ratings
Data Modeling
Comparison of Data Modeling features of Product A and Product B
Databricks Data Intelligence Platform
-
Ratings
Oracle Data Integrator (ODI)
7.4
12 Ratings
5% below category average
Data model creation
00 Ratings
8.011 Ratings
Metadata management
00 Ratings
8.011 Ratings
Business rules and workflow
00 Ratings
7.012 Ratings
Collaboration
00 Ratings
7.011 Ratings
Testing and debugging
00 Ratings
7.012 Ratings
Data Governance
Comparison of Data Governance features of Product A and Product B
Medium to Large data throughput shops will benefit the most from Databricks Spark processing. Smaller use cases may find the barrier to entry a bit too high for casual use cases. Some of the overhead to kicking off a Spark compute job can actually lead to your workloads taking longer, but past a certain point the performance returns cannot be beat.
Oracle Data Integrator is well suited in all the situations where you need to integrate data from and to different systems/technologies/environments or to schedule some tasks. I've used it on Oracle Database (Data Warehouses or Data Marts), with great loading and transforming performances to accomplish any kind of relational task. This is true for all Oracle applications (like Hyperion Planning, Hyperion Essbase, Hyperion Financial Management, and so on). I've also used it to manage files on different operating systems, to execute procedures in various languages and to read and write data from and to non-Oracle technologies, and I can confirm that its performances have always been very good. It can become less appropriate depending on the expenses that can be afforded by the customer since its license costs are quite high.
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.
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.
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.
Because it is an amazing platform for designing experiments and delivering a deep dive analysis that requires execution of highly complex queries, as well as it allows to share the information and insights across the company with their shared workspaces, while keeping it secured.
in terms of graph generation and interaction it could improve their UI and UX
Oracle Data Integrator (ODI) is a reliable ELT tool, supporting data loads from various heterogenous sources. It is effective both for structured as well as non structured data. Its works well for creating translations and transformation and also aids in the data quality checks when combined with an MDM solution. Troubleshooting issues can be of a challenge if it is not configured properly.
One of the best customer and technology support that I have ever experienced in my career. You pay for what you get and you get the Rolls Royce. It reminds me of the customer support of SAS in the 2000s when the tools were reaching some limits and their engineer wanted to know more about what we were doing, long before "data science" was even a name. Databricks truly embraces the partnership with their customer and help them on any given challenge.
The most important differentiating factor for Databricks Lakehouse Platform from these other platforms is support for ACID transactions and the time travel feature. Also, native integration with managed MLflow is a plus. EMR, Cloudera, and Hortonworks are not as optimized when it comes to Spark Job Execution. Other platforms need to be self-managed, which is another huge hassle.
I have used Trifacta Google Data Prep quite a bit. We use Google Cloud Platform across our organization. The tools are very comparable in what they offer. I would say Data Prep has a slight edge in usability and a cleaner UI, but both of the tools have comparable toolsets.