Integrate.io vs InfoSphere Information Server

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Our analysts compared Integrate.io vs InfoSphere Information Server based on data from our 400+ point analysis of ETL Tools, user reviews and our own crowdsourced data from our free software selection platform.

Integrate.io Software Tool

Product Basics

Integrate.io (formerly Xplenty) is an ETL (Extract, Transform, Load) software helping businesses move data between various sources, clean and organize it, and deliver it to analytics platforms. It caters to companies needing to streamline dataflows for insights and reporting. Integrate.io shines with its user-friendly interface, pre-built connectors, and drag-and-drop functionality, making it accessible to non-technical users. Key features include data pipeline building, data transformation tools, and scheduling capabilities. Compared to peers, users praise Integrate.io's intuitive design, ease of use, and vast connector library. However, some mention limited data lineage tracking and high costs for larger data volumes. Pricing varies based on data volume and features needed, typically starting in the hundreds per month and scaling upwards. Consider your data needs and technical expertise when comparing Integrate.io to similar ETL solutions.

Pros
  • User-friendly interface
  • Drag-and-drop functionality
  • Vast connector library
  • Intuitive data mapping
  • Solid customer support
Cons
  • Limited data lineage tracking
  • High costs for larger data volumes
  • Occasional performance issues
  • Customization options can be limited
  • Error handling could be more robust
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InfoSphere Information Server is a data integration powerhouse designed to unify information across complex, diverse systems. It excels at extracting, transforming, and loading data (ETL/ELT) for tasks like building data warehouses, powering analytics, and driving business insights. Best suited for large enterprises with demanding data needs and dedicated IT resources, InfoSphere boasts robust features like comprehensive data source/target connectors, powerful transformation tools, and advanced governance capabilities. User feedback highlights its scalability, security, and job automation as key benefits. However, its complexity and steep learning curve can be daunting for smaller setups. Additionally, the high licensing costs and resource-intensive nature might dissuade budget-conscious organizations. Compared to other data integration tools, InfoSphere leans towards high-volume, mission-critical scenarios, while alternative options might offer simpler setups or cater to broader use cases. Choosing the right fit depends on individual needs and priorities. Ultimately, InfoSphere Information Server shines when organizations need a robust, feature-rich platform to conquer complex data challenges, even at the cost of increased upfront investment and initial learning hurdles.

Pros
  • Powerful ETL & ELT capabilities
  • Wide range of data sources & targets
  • Job scheduling & monitoring
  • Data quality & transformation tools
  • Scalable & secure architecture
Cons
  • Steep learning curve & complexity
  • High licensing costs
  • Limited out-of-the-box connectors
  • Performance bottlenecks with large datasets
  • Resource-intensive for deployment & maintenance
read more...
$15,000 Annually
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Mobile

Product Assistance

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Live Online
Videos
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Email
Phone
Chat
FAQ
Forum
Knowledge Base
24/7 Live Support
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24/7 Live Support

Product Insights

  • Integrate Business Data: Design sophisticated ETL pipelines by connecting to more than 140 files, data warehouses and systems like Amazon Redshift, Snowflake and Oracle, among others. Scales to add more integrations as they become available — no need to create code or manual data flows. 
  • Understand Market Trends: Integrate customer support data with social media, analytics and CRM systems. Prevent churn by personalizing customer outreach messages based on customer interests and lifecycle stage. 
  • Get Marketing Analytics: Build marketing campaigns and reports with enriched, personalized data. Enables targeted customer outreach by moving data to third-party platforms like CRM through reverse ETL. 
  • Boost Sales: Drive conversion with insights into the customer life cycle gleaned from real-time data. Avoid duplicate and out-of-date information by centralizing sales metrics. Integrates with Stripe, Mixpanel, Hubspot, Salesforce and Google Adwords. 
  • Scale Flexibly: Scale as the business grows, extend capabilities and customize as needed by connecting to RESTful services through APIs. 
  • Secure Data Pipelines: Control access permissions within the organization through SSO and 2FA. Enable 2FA on individual accounts from settings. Uses a time-based one-time-password scheme for the second-factor authentication. Request for SSO enablement and then sign in via enterprise identity provider. 
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  • Unified Data Landscape: Break down data silos and seamlessly integrate information from diverse sources, including databases, applications, and cloud platforms, providing a holistic view for improved decision-making.
  • Enhanced Data Quality: Ensure data accuracy and consistency through powerful cleansing, standardization, and transformation tools, minimizing errors and boosting trust in your data assets.
  • Streamlined Data Movement: Automate and orchestrate data movement using flexible ETL/ELT workflows, speeding up data delivery and reducing manual effort for critical business processes.
  • Powerful Data Transformation: Manipulate and enrich data to meet specific needs through a comprehensive set of transformation functions, unlocking its full potential for analytics and reporting.
  • Scalable and Secure Architecture: Handle large data volumes and complex integrations with confidence thanks to a robust and secure architecture, ensuring uninterrupted data flow and safeguarding sensitive information.
  • Improved Operational Efficiency: Automate routine data tasks, reduce IT workload, and optimize resource utilization, freeing up staff and resources for higher-value activities.
  • Enhanced Data Governance: Implement data governance policies and ensure compliance with regulations through features like lineage tracking and access controls, fostering data transparency and responsible usage.
  • Greater Business Agility: Respond rapidly to changing data needs and support new initiatives with agile data integration capabilities, empowering faster time-to-market and increased business flexibility.
  • Improved Collaboration and Decision-Making: Foster greater collaboration across teams by providing everyone with access to reliable and consistent data, leading to better informed decisions and data-driven strategies.
  • Reduced Integration Costs: Streamline data management processes, eliminate data redundancies, and optimize infrastructure usage by consolidating data integration needs into a single platform, potentially leading to cost savings.
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  • Connectivity Library: Convey business information across locations through no-code and low-code connectors for data warehouses, cloud-based SaaS platforms and databases, including NoSQL data repositories. 
    • API Integrations: Secures the ETL process through seamless RESTful API integrations with more than 100 applications. Processes parallelly massive complex datasets; uses Hadoop MapReduce to distribute computing tasks over several server clusters. 
  • Data Replication: Replicates data in real time through change data capture (CDC) in collaboration with FlyData, a data migration system. Loads data securely to Amazon Redshift and Snowflake in a matter of minutes. 
  • Expressions: Use functions to manipulate the results output by component with the Expression Editor. Schedule packages and workflows with cron expressions. Schedule tasks around active and inactive hours, ensure that important packages are executed on time, and remove the need for manual input. 
  • Reverse ETL: Moves data from data warehouses to third-party systems, transforms it and makes it operational. Connects with other data stack components, eliminating the need to manually build API connectors. 
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  • Data Integration: Collect, transform and share large amounts of complex data assets across the organization. Reduce development time, and scale flexibly by leveraging built-in data transformation functions. Deliver data in real time to business applications in bulk, virtually or through change data capture (CDC). 
  • Data Quality: Cleanse and validate data — in batches and real time — then load it into analytical views for consistent monitoring. Establish data quality metrics across the organization by reusing these data views. Ensure consistent information organization-wide by linking related records across systems. 
    • Business Glossary: Create a single source of truth – consolidate disparate data into unique, reliable records and load into repositories and master data applications. Share insights with confidence powered by complete access to proof of lineage and data quality. A centralized hub maintains data governance rules. 
  • Information Governance Catalog: Empower data scientists and analysts to explore and analyze business data in compliance with enterprise governance standards. Create, manage and share a common business language, design and apply rules and track data lineage. Extend on-premise governance investment to the cloud by integrating with IBM Watson Knowledge Catalog. 
  • Metadata Repository: Share imported metadata and other assets in any server component across. the organization. Stores project configurations, reports and results for all the server’s components in one unified repository 
read more...

Product Ranking

#26

among all
ETL Tools

#32

among all
ETL Tools

Find out who the leaders are

Analyst Rating Summary

87
97
57
100
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94
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Platform Security
Data Sources and Targets Connectivity
Data Transformation
Data Quality
Metadata Management
Data Delivery
Metadata Management
Platform Security
Workflow Management
Data Quality

Analyst Ratings for Functional Requirements Customize This Data Customize This Data

Integrate.io
InfoSphere Information Server
+ Add Product + Add Product
Data Delivery Data Quality Data Sources And Targets Connectivity Data Transformation Metadata Management Platform Capabilities Workflow Management 57 87 96 91 86 0 67 100 99 94 95 100 0 100 0 25 50 75 100
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Analyst Ratings for Technical Requirements Customize This Data Customize This Data

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User Sentiment Summary

Great User Sentiment 153 reviews
Good User Sentiment 80 reviews
87%
of users recommend this product

Integrate.io has a 'great' User Satisfaction Rating of 87% when considering 153 user reviews from 4 recognized software review sites.

77%
of users recommend this product

InfoSphere Information Server has a 'good' User Satisfaction Rating of 77% when considering 80 user reviews from 3 recognized software review sites.

4.3 (115)
4.0 (21)
4.59 (17)
n/a
4.6 (16)
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4.1 (5)
4.6 (27)
n/a
3.1 (32)

Awards

No awards.

SelectHub research analysts have evaluated InfoSphere Information Server and concluded it earns best-in-class honors for Workflow Management.

Workflow Management Award

Synopsis of User Ratings and Reviews

User-Friendly Interface: Visual, drag-and-drop interface makes it accessible to users of all technical levels.
Vast Connector Library: Connects to a wide range of popular data sources and destinations, eliminating the need for custom coding.
Intuitive Data Mapping: Easily map fields between sources and destinations with a visual interface, streamlining the data transformation process.
Solid Customer Support: Responsive and helpful customer support team assists with any issues that arise.
Scalability: Handles large data volumes and complex data flows, making it suitable for growing businesses.
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Powerful Data Handling: Handles complex ETL/ELT processes and diverse data sources (relational, flat files, cloud platforms) with ease, streamlining data movement and integration.
Enhanced Data Quality: Ensures data accuracy and consistency through robust cleansing, validation, and transformation tools, boosting trust and reliability in data insights.
Scalability and Security: Supports large data volumes and complex integrations with confidence, safeguarding sensitive information through granular access controls and encryption.
Job Automation and Monitoring: Automates data pipelines and workflows, reducing manual effort and simplifying task management with comprehensive monitoring capabilities.
Improved Operational Efficiency: Centralizes data integration processes, eliminates data silos, and frees up IT resources for higher-value tasks, leading to cost savings and increased productivity.
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Limited Data Lineage Tracking: Lacks robust tracking of data lineage, making it challenging to trace data's journey from source to destination for auditing and compliance purposes.
High Costs for Larger Data Volumes: Pricing can become expensive for businesses with high data volumes, potentially limiting its affordability.
Occasional Performance Issues: Users have reported occasional slowdowns or lags, especially when dealing with large data sets or complex workflows.
Customization Options Can Be Limited: The pre-built connectors and functionalities might not cater to all specific needs, requiring workarounds for unique use cases.
Error Handling Could Be More Robust: Improved error reporting and troubleshooting tools would enhance user experience, making it easier to identify and resolve issues.
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Steep Learning Curve: Complex interface and feature-rich platform require significant training and expertise, even for experienced data professionals.
High Cost of Ownership: Licensing fees, maintenance, and potential hardware/infrastructure upgrades can make it a costly solution for smaller organizations or simpler data needs.
Limited Out-of-the-Box Connectors: May require custom development or third-party tools for integration with certain data sources or applications, increasing implementation complexity and costs.
Performance Bottlenecks: Can experience slowdowns or scalability issues with very large datasets or intricate ETL/ELT processes, demanding careful optimization and resource allocation.
Limited Cloud-Native Functionality: Core features are primarily designed for on-premises deployments, with cloud options requiring additional setup and configuration, potentially hindering agility and flexibility.
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Integrate.io shines amongst ETL tools for its user-friendliness, boasting a visual interface and vast connector library that empowers both technical and non-technical users. This accessibility is a major draw compared to competitors requiring coding expertise, saving time and resources. However, users also cite limitations in data lineage tracking and its higher cost for larger data volumes. While competitors like **Product A** may offer more granular control and customization, users praise Integrate.io's intuitive approach for everyday ETL tasks. This balance between ease of use and functionality is key for businesses needing a streamlined data flow solution without extensive technical overhead. On the other hand, those needing in-depth lineage tracking or handling massive datasets might find competitors like **Product B** more suitable despite their steeper learning curve. Ultimately, user reviews suggest Integrate.io excels in providing an accessible and efficient ETL solution for businesses prioritizing user-friendliness and a wide range of pre-built connectors. If robust data lineage tracking or affordability for massive data volumes are paramount, exploring alternative ETL tools might be necessary.

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User reviews of InfoSphere Information Server paint a picture of a powerful data integration tool, capable of handling complex tasks and diverse data sources. Admiration for its robust ETL/ELT capabilities, data quality tools, and secure architecture echoes frequently, with users citing improved data accuracy and streamlined data movement as major benefits. Automation features and job monitoring are also praised for boosting operational efficiency and freeing up resources. However, the praise comes with caveats. The steep learning curve and demanding resource requirements are consistent gripes, making InfoSphere a better fit for larger organizations with dedicated IT expertise and infrastructure. The high cost of ownership, including licensing, maintenance, and potential hardware upgrades, further strengthens this point. Additionally, the limited out-of-the-box connectors and potential performance bottlenecks with massive datasets are concerns for some users. Compared to competitors, InfoSphere shines in its scalability and security, catering to high-volume, mission-critical scenarios. However, users also acknowledge the presence of simpler, more user-friendly options that might be better suited for smaller setups or less complex data needs. Ultimately, the choice boils down to individual priorities. If data volume, security, and advanced features are paramount, InfoSphere stands out, despite its demanding nature. But for those seeking a smoother learning curve or broader use cases, other solutions might offer a better fit. In essence, user reviews reveal InfoSphere Information Server as a powerful tool for complex data challenges, but its strengths come with a price tag and learning curve. Carefully evaluating data needs and priorities is crucial before choosing this data integration powerhouse.

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