Top AWS Glue Alternatives & Competitors For 2024

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Looking for alternatives to AWS Glue? Many users crave user-friendly and feature-rich solutions for tasks like Data Delivery, Workflow Management, and Data Transformation. Leveraging crowdsourced data from over 1,000 real ETL Tools selection projects based on 400+ capabilities, we present a comparison of AWS Glue to leading industry alternatives like Talend, InfoSphere Information Server, Integrate.io, and SQL Server Integration Services.

Integrate.io Software Tool

Product Basics

AWS Glue is a fully managed, event-driven serverless computing platform that extracts, cleanses and organizes data for insights. Automatic code generation ensures citizen data scientists and power users can create and schedule integration workflows. An event-driven architecture enables setting triggers to launch data integration processes.

A common data catalog with automatic schema generation ensures data is unique and easily accessible. With streaming data integration, it catalogs assets from datastores like Amazon S3, making it available for querying with Amazon Athena and Redshift Spectrum. Developers can access readymade endpoints to edit and test code.

Pros
  • Serverless & Scalable
  • Easy Visual Workflow
  • Built-in Data Connectors
  • Pay-per-Use Pricing
  • AWS Ecosystem Integration
Cons
  • Complex Transformations
  • Limited On-Premise Data
  • Python & Scala Only
  • Potential Cost Overruns
  • AWS Lock-in Concerns
read more...
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
read more...
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...
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
read more...
SQL Server Integration Services (SSIS) is a data integration tool built within Microsoft SQL Server. It excels at orchestrating data movement and transformation tasks between diverse sources and destinations, making it ideal for data warehousing, ETL (Extract, Transform, Load) processes, and database management in Windows environments. Users praise its visual workflow editor, robust data transformation capabilities, and seamless integration with other Microsoft tools. Additionally, SSIS offers built-in security features and scalability for handling large datasets. However, its reliance on the Microsoft ecosystem, limited open-source compatibility, and potentially complex learning curve can be drawbacks. Pricing is part of the SQL Server license, ranging from affordable Express editions to more expensive Enterprise versions depending on user needs and server configurations. Overall, SSIS is a powerful and cost-effective option for organizations heavily invested in the Microsoft suite and primarily focused on Windows server environments. For those seeking open-source flexibility or broader platform compatibility, alternative data integration tools may be worth exploring.

Pros:
  • Visual workflow
  • Strong data transformations
  • Microsoft integration
  • Built-in security
  • Scalable for large volumes
Cons:
  • Windows only
  • Limited open source
  • Steep learning curve
  • Pricing with SQL Server
  • Closed-source ecosystem
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Product Assistance

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Product Ranking

#9

among all
ETL Tools

#10

among all
ETL Tools

#32

among all
ETL Tools

#26

among all
ETL Tools

#8

among all
ETL Tools

Find out who the leaders are

Analyst Rating Summary

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Data Delivery
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Data Transformation
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Data Sources and Targets Connectivity
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Analyst Ratings for Functional Requirements Customize This Data Customize This Data

AWS Glue
Talend
InfoSphere Information Server
Integrate.io
SQL Server Integration Services
+ Add Product + Add Product
Data Delivery Data Quality Data Sources and Targets Connectivity Data Transformation Metadata Management Platform Capabilities Workflow Management 100 92 62 90 96 100 100 100 100 92 100 100 100 89 100 99 94 95 100 0 100 57 87 96 91 86 0 67 88 100 76 100 93 0 91 0 25 50 75 100
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User Sentiment Summary

Great User Sentiment 165 reviews
Great User Sentiment 270 reviews
Good User Sentiment 80 reviews
Great User Sentiment 153 reviews
Great User Sentiment 503 reviews
85%
of users recommend this product

AWS Glue has a 'great' User Satisfaction Rating of 85% when considering 165 user reviews from 3 recognized software review sites.

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.

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.

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.

84%
of users recommend this product

SQL Server Integration Services has a 'great' User Satisfaction Rating of 84% when considering 503 user reviews from 2 recognized software review sites.

4.0 (46)
n/a
4.0 (21)
4.3 (115)
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4.19 (22)
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4.59 (17)
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4.0 (52)
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4.6 (16)
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4.4 (109)
4.1 (145)
4.6 (27)
4.1 (5)
4.3 (279)
3.9 (10)
4.1 (51)
3.1 (32)
n/a
4.1 (224)

Awards

Workflow Management Award
Data Transformation Award
Workflow Management Award
we're gathering data
Data Transformation Award

Synopsis of User Ratings and Reviews

Cost-Effective & Serverless: Pay only for resources used, eliminates server provisioning and maintenance
Simplified ETL workflows: Drag-and-drop UI & auto-generated code for easy job creation, even for non-programmers
Data Catalog: Unified metadata repository for seamless discovery & access across various data sources
Flexible Data Integration: Connects to diverse data sources & destinations (S3, Redshift, RDS, etc.)
Built-in Data Transformations: Apply pre-built & custom transformations within workflows for efficient data cleaning & shaping
Visual Data Cleaning (Glue DataBrew): Code-free data cleansing & normalization for analysts & data scientists
Scalability & Performance: Auto-scaling resources based on job needs, efficient Apache Spark engine for fast data processing
Community & Support: Active user community & helpful AWS support resources for problem-solving & best practices
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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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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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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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Visual Workflow: Drag-and-drop interface simplifies complex data flows, making integration tasks intuitive and manageable, even for users without extensive coding experience.
Robust Data Transformations: Cleanses, transforms, and validates data to ensure accuracy and consistency before integration, improving data quality and trust in downstream analytics.
Microsoft Integration: Seamlessly integrates with other Microsoft tools and platforms like SQL Server and Azure, streamlining data workflows within existing infrastructure and reducing the need for additional software.
Scalability and Performance: Handles large datasets efficiently with parallel processing and optimization techniques, minimizing processing time and ensuring smooth data integration for growing data volumes.
Built-in Security: Supports encryption, data masking, and role-based access controls for secure data handling and compliance with industry regulations, providing peace of mind and reducing security risks.
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Limited Customization & Control: Visual interface and pre-built transformations may not be flexible enough for complex ETL needs, requiring manual coding or custom Spark jobs.
Debugging Challenges: Troubleshooting Glue jobs can be complex due to limited visibility into underlying Spark code and distributed execution, making error resolution time-consuming.
Performance Limitations for Certain Workloads: Serverless architecture may not be optimal for latency-sensitive workloads or large-scale data processing, potentially leading to bottlenecks.
Vendor Lock-in & Portability: Migrating ETL workflows from Glue to other platforms can be challenging due to its proprietary nature and lack of open-source compatibility.
Pricing Concerns for Certain Use Cases: Pay-per-use model can be expensive for long-running ETL jobs or processing massive datasets, potentially exceeding budget constraints.
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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: 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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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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Limited Open Source: Relies heavily on Microsoft technologies and lacks extensive open-source integrations, potentially restricting customization and community support compared to more open platforms.
Steep Learning Curve: While the visual interface is helpful, mastering complex data flows and transformations can require significant training and experience, especially for users unfamiliar with the platform.
Windows Only: Limited to Windows environments, excluding non-Microsoft operating systems like Linux or macOS, hindering platform flexibility and potentially requiring additional infrastructure investment.
Closed-Source Ecosystem: Limited transparency into internal algorithms and processes can make troubleshooting and debugging complex issues challenging, requiring specialized knowledge or relying on Microsoft support.
Cost Tied to SQL Server: Pricing depends on the chosen SQL Server edition, potentially increasing costs for organizations already invested in other database solutions or needing only basic data integration functionalities.
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User reviews of AWS Glue paint a picture of a powerful and user-friendly ETL tool for the cloud, but one with limitations. Praise often centers around its intuitive visual interface, making complex data pipelines accessible even to non-programmers. Pre-built connectors and automated schema discovery further simplify setup, saving users time and effort. Glue's serverless nature and tight integration with the broader AWS ecosystem are also major draws, offering seamless scalability and data flow within a familiar environment. However, some users find Glue's strength in simplicity a double-edged sword. For complex transformations beyond basic filtering and aggregation, custom scripting in Python or Scala is required, limiting flexibility for those unfamiliar with these languages. On-premise data integration is another pain point, with Glue primarily catering to cloud-based sources. This leaves users seeking hybrid deployments or integration with legacy systems feeling somewhat stranded. Cost also arises as a concern. Glue's pay-per-use model can lead to unexpected bills for large data volumes or intricate pipelines, unlike some competitors offering fixed monthly subscriptions. Additionally, Glue's deep integration with AWS can create lock-in anxieties for users worried about switching cloud providers in the future. Overall, user reviews suggest Glue shines in cloud-based ETL for users comfortable with its visual interface and scripting limitations. Its scalability, ease of use, and AWS integration are undeniable strengths. However, for complex transformations, on-premise data needs, or cost-conscious users, alternative tools may offer a better fit.

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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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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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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 SQL Server Integration Services paint a contrasting picture. Proponents praise its intuitive visual workflow, robust data transformation capabilities, and seamless integration with the Microsoft ecosystem. This makes it ideal for organizations already invested in Microsoft tools and requiring efficient data movement within Windows environments. The built-in security features and scalability for handling large datasets are further pluses, offering peace of mind and ensuring smooth performance for growing data volumes. However, critics point to its heavy reliance on Microsoft technologies and limited open-source compatibility as major drawbacks. This can restrict customization and community support compared to more open platforms like Talend or Apache Airflow. The steep learning curve and Windows-only limitation can also be hurdles, requiring dedicated training and potentially hindering platform flexibility. Additionally, the closed-source nature can make troubleshooting complex issues challenging. Finally, pricing tied to SQL Server editions may not be cost-effective for organizations needing only basic data integration functionalities or using other database solutions. Ultimately, SQL Server Integration Services shines for its robust data handling, intuitiveness, and Microsoft integration within Windows environments. However, its limited open-source compatibility, steep learning curve, and reliance on SQL Server licensing make it less ideal for organizations seeking greater flexibility, affordability, or platform independence. Carefully weighing your specific needs and resources against its strengths and limitations is crucial before choosing SSIS for your data integration needs.

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Related Categories

Top Alternatives in ETL Tools


Azure Data Factory

Cloud Data Fusion

Dataflow

DataStage

Fivetran

Hevo

IDMC

Informatica PowerCenter

InfoSphere Information Server

Integrate.io

Oracle Data Integrator

Pentaho

Qlik Talend Data Integration

SAP Data Services

SAS Data Management

Skyvia

SQL Server

SQL Server Integration Services

Talend

TIBCO Cloud Integration

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