Oracle Data Integrator vs SAS Data Management

Last Updated:

Our analysts compared Oracle Data Integrator vs SAS Data Management based on data from our 400+ point analysis of ETL Tools, user reviews and our own crowdsourced data from our free software selection platform.

Oracle Data Integrator Software Tool
SAS Data Management Software Tool

Product Basics

Oracle Data Integrator (ODI) is a data integration platform designed to extract, transform, and load (ETL) data from various sources to target systems. It offers a visual interface for building and managing data pipelines, including pre-built connectors for popular databases, applications, and cloud services. ODI is ideal for organizations needing to integrate data from diverse sources for business intelligence, data warehousing, and other analytical needs. Its key benefits include ease of use, scalability, high performance, and extensive out-of-the-box functionality. Popular features include graphical mapping interface, data quality checks, data lineage tracking, and support for complex data transformations. User reviews highlight ODI's strengths in simplifying complex data integration tasks, offering robust data quality tools, and ensuring efficient data processing. However, some users report occasional performance issues and limited flexibility compared to more open-source solutions. Pricing varies based on deployment options and required features, typically ranging from several thousand to tens of thousands of dollars per year, with payment options including annual licenses and subscription plans.

Pros
  • Easy to use interface
  • Strong data quality tools
  • High performance & scalable
  • Extensive built-in functionality
  • Connects to popular data sources
Cons
  • Occasional performance issues
  • Less flexible than open-source tools
  • Steeper learning curve for advanced tasks
  • Potentially high cost depending on deployment
  • Limited community support compared to open-source options
read more...
SAS Data Management empowers organizations to wrangle their data, from ingestion and cleansing to transformation and governance. It excels at handling mountains of complex data, making it ideal for industries like finance, healthcare, and government. Key benefits include streamlined data integration, enhanced data quality, and robust security controls. Popular features include its drag-and-drop interface, automation capabilities, and advanced analytics tools. User experiences suggest it can be powerful for data wranglers but might have a steeper learning curve compared to simpler options. Pricing is typically per seat or core, with annual subscriptions or perpetual licenses available.

Pros
  • Robust for large datasets
  • Scalable & high performance
  • Advanced data manipulation
  • Automate complex tasks
  • Strong statistical analysis
Cons
  • Steep learning curve
  • Costly licensing & maintenance
  • Limited visual analytics
  • Not user-friendly interface
  • Difficult to debug code
read more...
$0.09/OCPU, /Hour
Free Trial is unavailable →
Get a free price quote
Tailored to your specific needs
$300 Monthly
Get a free price quote
Tailored to your specific needs
Small 
i
Medium 
i
Large 
i
Small 
i
Medium 
i
Large 
i
Windows
Mac
Linux
Android
Chromebook
Windows
Mac
Linux
Android
Chromebook
Cloud
On-Premise
Mobile
Cloud
On-Premise
Mobile

Product Assistance

Documentation
In Person
Live Online
Videos
Webinars
Documentation
In Person
Live Online
Videos
Webinars
Email
Phone
Chat
FAQ
Forum
Knowledge Base
24/7 Live Support
Email
Phone
Chat
FAQ
Forum
Knowledge Base
24/7 Live Support

Product Insights

  • Maximize ROI: Reduces infrastructure costs by eliminating the need for an ETL server and engine. Save on labor costs with a smaller learning curve and reduce TCO with lower development costs. 
  • Integrate Disparate Data: Supports all RDBMS like Oracle, Exadata, Teradata, IBM DB2, Netezza, Sybase IQ, ERPs, LDAP, XML and flat files, among others. 
  • Deploy Faster: Enhance user experience and developer productivity with a flow-based declarative user interface. Enables developers to focus on describing what’s to be done visually, with data architects defining processes and executing data integration separately. Shorten implementation times and simplify maintenance. 
  • Map Big Data: Transform large, complex data sets by leveraging its flexible and highly performant architecture. Generate Apache Spark code as per big data standards, with native support for big data and parallel processing. 
  • Access Data 24*7: Scales as the data grows with clustered deployments for high availability. Optimizes workloads with JDBC connection pooling, load balancing and a connection retry mechanism to recover failed sessions. 
read more...
  • Faster, Deeper Insights: SAS Data Management streamlines data preparation, reducing time spent wrangling data and freeing you to focus on analysis. Dive into complex datasets faster with automated tasks, data quality checks, and efficient transformation tools.
  • Unify Data from Anywhere: Break down data silos and gain a holistic view with seamless access across diverse sources. Connect to databases, cloud platforms, and data lakes with ease, regardless of format or location.
  • Empower Business Users: Equip non-technical users with self-service tools for data discovery and exploration. Drag-and-drop interfaces and intuitive wizards make data manipulation accessible, fostering data-driven decision-making across the organization.
  • Boost Efficiency and Productivity: Automate repetitive tasks and simplify complex workflows with SAS Data Management's powerful scripting language. Eliminate manual processes and free up time for higher-value analysis, boosting team productivity.
  • Build Trustworthy Data: Ensure data quality and compliance with comprehensive governance features. Track data lineage, maintain audit trails, and apply robust security measures to build trust in your data and its insights.
  • Unleash the Power of AI and Machine Learning: Integrate AI and machine learning capabilities directly into your data pipelines. Cleanse data with intelligent algorithms, identify hidden patterns, and generate predictive models, all within the SAS Data Management platform.
  • Scale with Confidence: SAS Data Management scales seamlessly to meet your growing data needs. Handle large and complex datasets efficiently, whether on-premises or in the cloud, with robust infrastructure and performance optimization tools.
  • Future-proof Your Data Strategy: Stay ahead of the curve with SAS Data Management's continuous innovation. Access cutting-edge technologies like in-memory analytics and cloud-native capabilities to adapt to the evolving data landscape.
read more...
  • Simple Design: Save on a separate ETL server and engine; transform complex datasets using only the source and target servers. Deploys E-LT architecture based on existing RDBMS engines and SQL. Uses database CPU and memory to run transformations. 
    • Service-Oriented Architecture (SOA): Consolidate databases, ERP and middleware in a single business solution by building a shared services layer with Oracle SOA Suite. Improve bulk data transfer performance, business optimization, process visibility and exception handling. 
  • ODI Studio: Configure and manage ODI; administer the infrastructure, reverse engineer the metadata, develop projects, schedule, operate and monitor executions. 
  • Administer Centrally: Set up production environments, manage and monitor run-time operations and diagnose errors with the ODI Enterprise Edition Console. 
    • Get read access to the metadata repository, and perform topology configuration and production operations through a web-based UI. 
    • Integrates with the Oracle Enterprise Manager Fusion Middleware Control Console for single-screen monitoring of data integration and Fusion Middleware components. 
    • Manage all ODI environment components from Oracle Enterprise Manager Cloud Control through the Management Pack. 
  • Data Quality Firewall: Automatically detects and recycles faulty data before incorporating it in the target system – no need for programming. Follows the data integrity rules and constraints defined on the target platform and in ODI. 
read more...
  • Integrated Development Environment (IDE): Access source systems virtually and create target structures. Manage processes with an intuitive, point-and-click, role-based GUI – import and export metadata functions and run ETL and ELT process flows. Supports interactive debugging and testing of jobs with full log access. 
    • Unified Architecture: Leverage the complete data pipeline — from data quality to data federation — in one platform. Ensure data transparency and accountability with auditing tools and source data lineage. 
  • Process Designer: Build and update data management processes with a visual, end-to-end event designer. Control and run data integration tasks and fork jobs to execute in parallel. Run shell scripts by calling REST and SOAP web services. 
  • Embeddable Data Quality: Access customizable business rules within batch, near-time and real-time processes and reuse as needed. Identify incomplete, ambiguous and inaccurate data with its interactive GUI. Get alerts for when data quality falls below acceptable standards. Supports data cleansing in native languages for more than 38 regions globally. 
  • Data Transformation: Build data warehouses, data marts, and BI and analytic data stores by pulling data from multiple sources. Extract required data with more than 300 out-of-the-box SQL-based transforms. Reuse transform functions in different projects and environments through custom exits, message queues and web services. 
read more...

Product Ranking

#31

among all
ETL Tools

#43

among all
ETL Tools

Find out who the leaders are

Analyst Rating Summary

95
94
100
100
100
94
88
84
Show More Show More
Data Delivery
Data Quality
Metadata Management
Performance and Scalability
Platform Capabilities
Data Delivery
Metadata Management
Performance and Scalability
Platform Capabilities
Platform Security

Analyst Ratings for Functional Requirements Customize This Data Customize This Data

Oracle Data Integrator
SAS Data Management
+ Add Product + Add Product
Data Delivery Data Quality Data Sources And Targets Connectivity Data Transformation Metadata Management Platform Capabilities Workflow Management 100 100 88 96 100 100 89 100 94 84 97 100 100 92 0 25 50 75 100
100%
0%
0%
100%
0%
0%
100%
0%
0%
85%
15%
0%
79%
0%
21%
71%
0%
29%
96%
0%
4%
96%
0%
4%
100%
0%
0%
100%
0%
0%
100%
0%
0%
100%
0%
0%
90%
0%
10%
80%
10%
10%

Analyst Ratings for Technical Requirements Customize This Data Customize This Data

100%
0%
0%
100%
0%
0%
100%
0%
0%
100%
0%
0%

User Sentiment Summary

Great User Sentiment 243 reviews
Great User Sentiment 99 reviews
81%
of users recommend this product

Oracle Data Integrator has a 'great' User Satisfaction Rating of 81% when considering 243 user reviews from 5 recognized software review sites.

86%
of users recommend this product

SAS Data Management has a 'great' User Satisfaction Rating of 86% when considering 99 user reviews from 4 recognized software review sites.

4.0 (17)
4.2 (18)
4.39 (18)
n/a
4.4 (18)
4.6 (17)
4.2 (69)
4.6 (29)
3.9 (121)
4.0 (35)

Synopsis of User Ratings and Reviews

Easy to Use: Intuitive drag-and-drop interface simplifies data integration tasks, even for non-technical users.
Pre-built Connectors: Supports a wide range of data sources and targets, including databases, applications, and cloud platforms.
Scalable and Robust: Handles large data volumes and complex data integration processes efficiently.
Data Quality Management: Built-in features for data cleansing, validation, and transformation ensure data accuracy.
Workflow Automation: Schedule and automate data integration tasks for timely data delivery.
Security and Governance: Comprehensive security features and role-based access control ensure data privacy and compliance.
Show more
Streamlined Workflow: Simplifies data management tasks with drag-and-drop interface and automated processes, saving time and improving efficiency.
Robust Data Quality: Ensures data accuracy and consistency through comprehensive cleaning, validation, and transformation tools, fostering trust in data-driven decisions.
Scalability and Performance: Handles large datasets efficiently with parallel processing and optimized algorithms, enabling complex analyses without performance bottlenecks.
Extensive Integrations: Connects seamlessly with various data sources and analytics platforms, facilitating a holistic view of data across the organization.
Regulatory Compliance: Supports secure data governance and auditability for meeting industry regulations, providing peace of mind and reducing compliance risks.
Show more
Steep Learning Curve: Mastering ODI's features and functionalities requires significant training and experience.
Limited Open-Source Community: Compared to other ETL tools, ODI has a smaller open-source community, which can lead to fewer resources and support.
High Cost: Oracle Data Integrator can be expensive to purchase and maintain, especially for small and medium-sized businesses.
Limited Cloud Support: While ODI supports cloud deployments, its cloud capabilities are not as mature as some other ETL tools.
Performance Bottlenecks: Complex mappings and large data volumes can lead to performance issues.
Show more
Cost and Licensing: Requires significant upfront investment and ongoing licensing fees, making it less accessible to smaller organizations or budget-constrained projects.
Steep Learning Curve: Complex interface and proprietary language can be challenging for users without prior SAS experience, requiring dedicated training and support.
Limited Open-Source Integration: Primarily focused on its own ecosystem, with limited compatibility and integration with open-source tools and platforms.
Black-Box Nature: Limited transparency into internal algorithms and processes can make troubleshooting and debugging complex issues challenging.
Vendor Lock-in: Switching to other data management solutions can be difficult and costly due to data dependencies and lack of standard export formats.
Show more

Oracle Data Integrator (ODI) receives mixed reviews, with users praising its intuitive interface, wide range of supported data sources, and robust data quality management features. However, some users find its learning curve steep and criticize its limited open-source community and high cost. Many users appreciate ODI's ease of use, particularly its drag-and-drop interface. One user noted, "ODI's intuitive interface made it easy to learn and use, even for someone with limited technical experience." This is a significant advantage compared to other ETL tools with steeper learning curves, like Informatica PowerCenter. ODI's wide range of pre-built connectors and support for various data sources is another highlight. "We were able to integrate data from a variety of sources, including databases, applications, and cloud platforms, without any major challenges," stated a user. This flexibility is crucial for modern businesses working with diverse data landscapes, especially compared to competitors like Talend which may require additional configurations for specific data sources. However, ODI's learning curve can be daunting for new users. One user commented, "It took me a while to feel comfortable using ODI, as I had to learn its specific terminology and concepts." Additionally, the limited open-source community can make it difficult to find answers or support online. "Compared to other ETL tools, the lack of a strong open-source community around ODI can be frustrating," noted a user. This is a disadvantage compared to open-source alternatives like Apache Airflow, which offer extensive online resources and communities. Another drawback is ODI's high cost. "The cost of ODI was a major concern for us, and we had to carefully consider our budget before making a decision," said a user. This high cost can be a deterrent for small and medium-sized businesses, particularly when compared to more cost-effective solutions like Pentaho Data Integration. Overall, ODI offers powerful data integration capabilities with a user-friendly interface and comprehensive data quality features. However, its steep learning curve, limited open-source community, and high cost can be significant drawbacks for some users. Ultimately, the decision of whether ODI is the right fit depends on individual needs and priorities.

Show more

User reviews of SAS Data Management paint a nuanced picture. Fans praise its streamlined workflow, robust data quality tools, and scalability for handling massive datasets. They appreciate its seamless integration with various data sources and analytics platforms, enabling a holistic view and fostering trust in data-driven decisions. Regulatory compliance support is another major plus, offering peace of mind and reducing risks. However, critics point to the hefty price tag and complex licensing structures as major barriers, especially for smaller companies or budget-constrained projects. The steep learning curve can be daunting for new users, requiring dedicated training and potentially slowing down productivity. Limited open-source integration and a closed-ecosystem nature restrict flexibility and collaboration with external tools. The black-box nature of its algorithms can also make troubleshooting and debugging difficult. Some users feel locked in due to data dependencies and non-standard export formats, making transitioning to other solutions costly and cumbersome. Ultimately, SAS Data Management's strengths in robust data handling, scalability, and compliance shine for organizations with complex data needs and strict regulations. However, its high cost, limited open-source compatibility, and steep learning curve make it less ideal for smaller companies or those seeking greater flexibility and affordability. Users weighing options should carefully consider their specific needs and resources before making a decision.

Show more

Screenshots

Top Alternatives in ETL Tools


AWS Glue

Azure Data Factory

Cloud Data Fusion

Dataflow

DataStage

Fivetran

Hevo

IDMC

Informatica PowerCenter

InfoSphere Information Server

Integrate.io

Pentaho

Qlik Talend Data Integration

SAP Data Services

SAS Data Management

Skyvia

SQL Server

SQL Server Integration Services

Talend

TIBCO Cloud Integration

Related Categories

Head-to-Head Comparison

WE DISTILL IT INTO REAL REQUIREMENTS, COMPARISON REPORTS, PRICE GUIDES and more...

Compare products
Comparison Report
Just drag this link to the bookmark bar.
?
Table settings