Talend vs Oracle Data Integrator

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Our analysts compared Talend vs Oracle Data Integrator 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

Product Basics

Talend is an open-source data integration and management platform that enables big data ingestion, transformation and mapping at the enterprise level. The vendor provides cross-network connectivity, data quality and master data management in a single, unified hub – the Data Fabric. Based on industry standards like Eclipse, Java and SQL, it helps businesses create reusable pipelines – build once and use anywhere, with no proprietary lock-in.

The open-source version is free, with the cloud data integration module available for a monthly and annual fee. The price of Data Fabric is available on request.

Pros
  • Open source & affordable
  • Visual drag-and-drop UI
  • Wide range of connectors
  • Scalable & cloud-ready
  • Active community & support
Cons
  • Steeper learning curve
  • Limited native profiling
  • Customization can be complex
  • Debugging can be challenging
  • Enterprise features require paid editions
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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
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$4,800 Annually
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$0.09/OCPU, /Hour
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Product Insights

  • Maximize ROI: Save money and time – build data pipelines faster. Lower operational costs with a zero-footprint solution. Build long-term customer associations by making reliable, accurate data available. Reduce risk and ensure regulatory compliance. Get a fast return on investment with its usage-based subscription model. 
  • Make Business Decisions Quicker: Live preview business data and diagnose issues instantly. Refer to dataset documentation to understand how datasets relate and change through the data flow and how variables used in analysis are defined. Transform data while maintaining optimum quality by applying built-in functions across batch and streaming pipelines. 
  • Integrate Big Data: Connect to a variety of data sources with more than 800 data connectors, with native support for Hadoop, MapReduce and NoSQL. Delivers clean, consistent assets at a big data scale. 
  • Deploy Anywhere: Get data from behind firewalls, data centers or in secure cloud environments. Manage data in the public cloud, with self-managed private clouds and on-premise platforms, or go hybrid. 
  • Scale As The Business Grows: Scales as more complex, larger data sets are generated to provide advanced analytics. Works with Amazon Web Services, Microsoft Azure, Google Cloud Platform, Snowflake and Databricks. 
  • Maintain Data Quality: Identify, highlight and fix issues as data moves across systems. Ensure data quality at every stage of the data pipeline with embedded checks. Preempt inconsistencies before they can impact crucial decisions. 
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  • 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. 
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  • Pipeline Designer: Pull in data to create dashboards that power business insights. Build reusable pipelines to integrate data from any source, then transform it to upload to data warehouses. 
    • DIY Data Workflows: Design and preview data workflows directly in the web browser without IT help. Run pipelines directly where the data lives, with support for disparate filesystems, business apps, databases, data warehouses and messaging services. Automate data stewardship, preparation and cataloging into data pipelines. 
  • Data Inventory: Prepare, consume and share data from a single, centralized hub. Make informed decisions by putting unique, accurate data at the center of business. 
    • View data trustworthiness at a glance with the Trust Score. Aggregates multiple metrics into a single, easy-to-understand score, scaling from 0 to 5. 
    • Flags data silos across sources and resolves the gap with reusable and shareable data assets. 
    • Make data work for you by sharing assets between the data preparation and designer modules. 
  • Talend Open Studio: Handles big data by leveraging Hadoop and its databases, or HBase, HCatalog, HDFS and Hive. Connects to Oracle, Teradata, Microsoft SQL Server, Marketo, Salesforce, Netsuite, SAP, Sugar CRM, Microsoft Dynamics, SMTP, FTP/SFTP, LDAP and more. Provides an Eclipse-based integrated environment (IDE) for system development. 
  • Talend Sandbox: The vendor provides a sandbox environment for data warehouse optimization, clickstream analytics, social media sentiment analysis and Apache weblog analytics. 
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  • 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. 
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Product Ranking

#10

among all
ETL Tools

#31

among all
ETL Tools

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Analyst Rating Summary

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Data Delivery
Data Quality
Data Transformation
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Data Delivery
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Platform Capabilities

Analyst Ratings for Functional Requirements Customize This Data Customize This Data

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Data Delivery Data Quality Data Sources And Targets Connectivity Data Transformation Metadata Management Platform Capabilities Workflow Management 100 100 92 100 100 100 89 100 100 88 96 100 100 89 0 25 50 75 100
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User Sentiment Summary

Great User Sentiment 270 reviews
Great User Sentiment 243 reviews
82%
of users recommend this product

Talend has a 'great' User Satisfaction Rating of 82% when considering 270 user reviews from 4 recognized software review sites.

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.

n/a
4.0 (17)
4.19 (22)
4.39 (18)
4.0 (52)
4.4 (18)
4.1 (145)
4.2 (69)
4.1 (51)
3.9 (121)

Awards

SelectHub research analysts have evaluated Talend and concluded it earns best-in-class honors for Data Transformation.

Data Transformation Award

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Synopsis of User Ratings and Reviews

Simplified Lineage Tracking: Visually map data flows and transformations for enhanced auditability and compliance, ensuring your data journey is clear and transparent.
Centralized Policy Management: Define and enforce data quality, access, and security rules across the organization, fostering a consistent and controlled data environment.
Automated Data Catalog: Discover, document, and govern all data assets for improved data visibility and utilization, empowering your teams to find and leverage the right data.
Streamlined Data Masking & Anonymization: Protect sensitive data during development and testing while preserving data utility, safeguarding privacy and complying with regulations.
Scalable & Collaborative:** Manage data governance across diverse data sources and teams with ease, adapting to your evolving data landscape and fostering collaboration.
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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.
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Limited Native Profiling: Lacks built-in tools for advanced data profiling and quality monitoring, requiring additional integrations or third-party tools, increasing complexity and potentially costs.
Steep Learning Curve: Complex UI and configuration can be challenging for beginners, especially non-technical users, requiring significant training and investment in onboarding and ongoing support.
Customization Challenges: Extensive customization options, while offering flexibility, can lead to complexity and maintenance overhead, particularly for large deployments or intricate data governance requirements.
Limited Community Support: While the Talend community is active, it may not be as extensive as other data governance solutions, potentially impacting troubleshooting and knowledge sharing, especially for niche issues or advanced configurations.
Enterprise Features in Paid Editions: Key data governance features like advanced lineage tracking, data masking, and data quality monitoring often require purchasing higher-tiered paid editions, increasing costs and potentially limiting accessibility for organizations with budget constraints.
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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.
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Users praise Talend's visual drag-and-drop builder as a major draw, especially when compared to code-heavy platforms like Informatica. "Talend's UI feels much more intuitive and beginner-friendly," one reviewer shared, making it easier to onboard non-technical colleagues. However, its steeper learning curve compared to simpler tools like Snaplogic was also noted, demanding more training and initial investment.Talend's open-source roots and wide range of connectors were lauded, especially for cost-conscious businesses. One user compared it to IBM DataStage, noting "Talend's open-source version offers surprisingly robust functionality, making it a viable alternative for smaller budgets." However, limited native profiling compared to powerful tools like Alteryx was mentioned as a drawback, forcing integration with separate solutions and potentially raising costs.Users appreciated Talend's scalability and cloud-readiness, particularly when contrasted with legacy ETL offerings. "Talend scales seamlessly as our data needs grow," said one reviewer, making it a future-proof investment. However, some found enterprise features locked behind paid editions, like advanced lineage tracking and data quality monitoring, a disadvantage compared to competitors like Boomi that offer these capabilities across the board.Overall, Talend's balance of affordability, user-friendliness, and scalability shines through in user reviews. While it may require deeper initial investment in training and lack certain advanced features out-of-the-box, its flexibility and adaptability make it a strong contender for businesses navigating the evolving data landscape. As one user summed it up, "Talend might not be perfect, but it's a powerful tool that grows with you, and that's what matters most."

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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.

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Screenshots

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