# Best ETL Tools

  *By [Shalaka Joshi](https://research.g2.com/insights/author/shalaka-joshi)*

   ETL (extract, transform, and load) tools transfer data between databases and external systems, supporting data replication, warehousing, analytics, data cleansing, and structuring, and increasingly support ELT workflows where transformation occurs within the target system rather than before loading.

### Core Capabilities of ETL Tools

To qualify for inclusion in the ETL category, a product must:

- Facilitate extract, transform, and load processes
- Transform data for quality or visualization
- Audit or record integration data
- Archive data for backup, future reference, or analysis

### Common Use Cases for ETL Tools

Data engineering and analytics teams use ETL tools to move and prepare data for reporting, analysis, and business intelligence. Common use cases include:

- Replicating data from source systems into [data warehouses](https://www.g2.com/categories/data-warehouse) for centralized analytics
- Cleansing and transforming raw data into structured, queryable formats
- Building visual data workflows to automate recurring data transfer and integration processes

### How ETL Tools Differ from Other Tools

ETL tools pre-process and transform data before loading it into the target system, distinguishing them from ELT approaches where the target system handles transformation after loading. While [data integration tools](https://www.g2.com/categories/data-integration-tools) cover a broader range of connectivity scenarios, ETL tools focus specifically on structured data movement pipelines with built-in transformation, auditing, and archiving capabilities.

### Insights from G2 on ETL Tools

Based on category trends on G2, visual workflow builders and pre-built connectors stand out as standout features. These platforms deliver reductions in manual data preparation time and improved data quality as core benefits of ETL adoption.





## Best ETL Tools At A Glance

- **Leader:** [Databricks](https://www.g2.com/products/databricks/reviews)
- **Highest Performer:** [5X](https://www.g2.com/products/5x/reviews)
- **Easiest to Use:** [5X](https://www.g2.com/products/5x/reviews)
- **Top Trending:** [Peliqan](https://www.g2.com/products/peliqan/reviews)
- **Best Free Software:** [Fivetran](https://www.g2.com/products/fivetran/reviews)


---

**Sponsored**

### CData Sync

Unlike volume-based tools with unpredictable pricing, CData Sync offers a single platform for ETL and reverse ETL, with full deployment flexibility and fixed, scalable pricing—so your costs don’t balloon as your data grows. Connect to 250+ enterprise data sources, including: • Salesforce, Microsoft Dynamics, and SAP • SharePoint, NetSuite, Workday, and QuickBooks • ServiceNow, Xero, Sage Intacct, HubSpot, Marketo, Oracle • …and many more Replicate that data into your preferred destinations, such as: • Snowflake, Databricks, SQL Server, Redshift, OneLake, and others Deploy it your way—on-premises, in your own cloud, or in a private-cloud SaaS model. Getting started is simple: 1. Log in 2. Select your source tables 3.Set your sync interval CData Sync handles the rest, using efficient incremental updates that minimize load on your operational systems. The platform includes: • Point-and-click ETL/ELT/reverse ETL • Change Data Capture (CDC) with no elevated database permissions • Complete data control and custom SQL transformations • dbt integration CData Sync centralizes your automated data flows, giving you full control, faster delivery, and the freedom to scale without hidden fees. Download a 30-day free trial of CData Sync or learn more at: www.cdata.com/sync



[Visit company website](https://www.g2.com/external_clickthroughs/record?secure%5Bad_program%5D=paid_promo&secure%5Bad_slot%5D=category_product_list&secure%5Bcategory_id%5D=1181&secure%5Bmedium%5D=sponsored&secure%5Bprioritized%5D=false&secure%5Bproduct_id%5D=124922&secure%5Bresource_id%5D=1181&secure%5Bresource_type%5D=Category&secure%5Bsource_type%5D=category_page&secure%5Bsource_url%5D=https%3A%2F%2Fwww.g2.com%2Fcategories%2Fetl-tools&secure%5Btoken%5D=6ce956c088d99d5af46347309f11cfd33abacc827f01346669e118ff5dff8992&secure%5Burl%5D=https%3A%2F%2Fwww.cdata.com%2Fsync%2F&secure%5Burl_type%5D=paid_promos)

---

## Top-Rated Products (Ranked by G2 Score)
  ### 1. [Databricks](https://www.g2.com/products/databricks/reviews)
  Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and over 60% of the Fortune 500 — rely on Databricks to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified Data Intelligence Platform that includes Agent Bricks, Lakeflow, Lakehouse, Lakebase and Unity Catalog.


  **Average Rating:** 4.6/5.0
  **Total Reviews:** 726

**User Satisfaction Scores:**

- **Has the product been a good partner in doing business?:** 8.9/10 (Category avg: 9.1/10)
- **Automation:** 9.0/10 (Category avg: 8.9/10)
- **Scalability:** 9.1/10 (Category avg: 8.7/10)
- **Auditing:** 8.5/10 (Category avg: 8.1/10)


**Seller Details:**

- **Seller:** [Databricks Inc.](https://www.g2.com/sellers/databricks-inc)
- **Company Website:** https://databricks.com
- **Year Founded:** 2013
- **HQ Location:** San Francisco, CA
- **Twitter:** @databricks (89,234 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/3477522/ (14,779 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Who Uses This:** Data Engineer, Senior Data Engineer
  - **Top Industries:** Information Technology and Services, Financial Services
  - **Company Size:** 44% Enterprise, 40% Mid-Market


#### Pros & Cons

**Pros:**

- Features (288 reviews)
- Ease of Use (278 reviews)
- Integrations (189 reviews)
- Collaboration (150 reviews)
- Data Management (150 reviews)

**Cons:**

- Learning Curve (112 reviews)
- Expensive (97 reviews)
- Steep Learning Curve (96 reviews)
- Missing Features (69 reviews)
- Complexity (64 reviews)

  ### 2. [Google Cloud BigQuery](https://www.g2.com/products/google-cloud-bigquery/reviews)
  BigQuery is a fully managed, AI-ready data analytics platform that helps you maximize value from your data and is designed to be multi-engine, multi-format, and multi-cloud. Store 10 GiB of data and run up to 1 TiB of queries for free per month.


  **Average Rating:** 4.5/5.0
  **Total Reviews:** 1,156

**User Satisfaction Scores:**

- **Has the product been a good partner in doing business?:** 8.6/10 (Category avg: 9.1/10)
- **Automation:** 8.9/10 (Category avg: 8.9/10)
- **Scalability:** 9.3/10 (Category avg: 8.7/10)
- **Auditing:** 8.3/10 (Category avg: 8.1/10)


**Seller Details:**

- **Seller:** [Google](https://www.g2.com/sellers/google)
- **Year Founded:** 1998
- **HQ Location:** Mountain View, CA
- **Twitter:** @google (31,840,340 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/1441/ (336,169 employees on LinkedIn®)
- **Ownership:** NASDAQ:GOOG

**Reviewer Demographics:**
  - **Who Uses This:** Data Engineer, Data Analyst
  - **Top Industries:** Information Technology and Services, Computer Software
  - **Company Size:** 37% Enterprise, 35% Mid-Market


#### Pros & Cons

**Pros:**

- Ease of Use (156 reviews)
- Speed (143 reviews)
- Fast Querying (120 reviews)
- Integrations (118 reviews)
- Query Efficiency (114 reviews)

**Cons:**

- Expensive (127 reviews)
- Query Issues (78 reviews)
- Cost Issues (63 reviews)
- Cost Management (60 reviews)
- Learning Curve (54 reviews)

  ### 3. [Celigo](https://www.g2.com/products/celigo/reviews)
  Celigo is the intelligent automation platform built for the AI era. An enterprise-ready iPaaS, Celigo helps organizations unify applications, automate complex operations, and scale digital ecosystems. The platform supports cloud integration, SaaS integration, enterprise application integration, and agentic automation under a single governance model. The platform is accessible to both business teams and developers — anyone can build, configure, and maintain integrations through natural language, while technical teams retain full control over architecture, security, and extensibility. Through an extensive library of 1,000+ prebuilt connectors, organizations can rapidly integrate systems such as ERP, CRM, ecommerce, finance, and support platforms — including NetSuite, Salesforce, SAP, Microsoft Dynamics, and Shopify — while maintaining flexibility for custom integrations and advanced API management. Celigo supports a wide range of enterprise integration scenarios including ERP integration, CRM integration, B2B integration, and EDI (electronic data interchange) workflows. These capabilities allow organizations to streamline supplier, partner, and customer data exchange while ensuring reliable data integration across internal and external systems. Built-in tools for data mapping, data transformation, and data synchronization ensure that information moves accurately and consistently between applications. What sets Celigo apart is its ability to span the full spectrum of automation — from deterministic, rules-based workflows to AI-driven decision-making — without requiring separate platforms or governance models. Celigo Agent Builder enables teams to create AI agents that reason and act across enterprise systems, with configurable guardrails that enforce business policy at runtime. Human-in-the-loop approvals ensure sensitive actions require explicit authorization before execution, and complete audit trails support compliance across every AI interaction. Celigo's MCP Server exposes enterprise capabilities through the Model Context Protocol, giving any AI agent — built inside Celigo or externally — secure, governed, auditable access to the full enterprise tech stack. This makes Celigo a foundational layer for enterprise AI orchestration, enabling organizations to connect external agents to internal systems without sacrificing control or visibility. Celigo Ora, the platform's natural language interface, makes the entire platform accessible through conversation. Anyone — including business teams without technical training — can build, modify, troubleshoot, and maintain integrations and automations by describing what they need in plain language. This eliminates the specialist bottleneck not just for building automations, but for ongoing maintenance and issue resolution as well. To accelerate deployment, Celigo offers fully managed Integration Apps and reusable integration templates that simplify common use cases such as order-to-cash automation, ecommerce integrations, and financial data flows. Centralized monitoring, runtime governance controls, and scalable architecture give enterprises full visibility into integration and automation processes while maintaining reliability and compliance. Designed for modern IT and operations teams, Celigo empowers enterprises to unify integration, automation, and AI on a single platform — scaling capacity without scaling headcount, and building a durable foundation for digital transformation across the entire application landscape.


  **Average Rating:** 4.6/5.0
  **Total Reviews:** 1,019

**User Satisfaction Scores:**

- **Has the product been a good partner in doing business?:** 9.2/10 (Category avg: 9.1/10)
- **Automation:** 10.0/10 (Category avg: 8.9/10)
- **Scalability:** 10.0/10 (Category avg: 8.7/10)


**Seller Details:**

- **Seller:** [Celigo](https://www.g2.com/sellers/celigo)
- **Company Website:** https://www.celigo.com
- **Year Founded:** 2011
- **HQ Location:** Redwood City, California
- **Twitter:** @celigoinc (1,424 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/275831/ (766 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Who Uses This:** IT Manager, NetSuite Administrator
  - **Top Industries:** Retail, Computer Software
  - **Company Size:** 58% Mid-Market, 37% Small-Business


#### Pros & Cons

**Pros:**

- Ease of Use (469 reviews)
- Integrations (299 reviews)
- Integration Capabilities (290 reviews)
- Easy Integrations (254 reviews)
- Customer Support (222 reviews)

**Cons:**

- Error Handling (108 reviews)
- Expensive (96 reviews)
- Learning Curve (92 reviews)
- Pricing Issues (70 reviews)
- Complexity (69 reviews)

  ### 4. [IBM watsonx.data](https://www.g2.com/products/ibm-watsonx-data/reviews)
  IBM® watsonx.data® helps you access, integrate and understand all your data —structured and unstructured—across any environment. It optimizes workloads for price and performance while enforcing consistent governance across sources, formats and teams. Watch the demo to learn how watsonx.data empowers you to build gen AI apps and powerful AI agents. Free Trial available: https://ibm.biz/Watsonx-data\_Trial


  **Average Rating:** 4.4/5.0
  **Total Reviews:** 149

**User Satisfaction Scores:**

- **Has the product been a good partner in doing business?:** 8.7/10 (Category avg: 9.1/10)
- **Automation:** 6.7/10 (Category avg: 8.9/10)
- **Scalability:** 6.7/10 (Category avg: 8.7/10)
- **Auditing:** 3.3/10 (Category avg: 8.1/10)


**Seller Details:**

- **Seller:** [IBM](https://www.g2.com/sellers/ibm)
- **Company Website:** https://www.ibm.com/us-en
- **Year Founded:** 1911
- **HQ Location:** Armonk, NY
- **Twitter:** @IBM (708,000 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/1009/ (324,553 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Who Uses This:** Software Engineer, CEO
  - **Top Industries:** Information Technology and Services, Computer Software
  - **Company Size:** 33% Small-Business, 33% Enterprise


#### Pros & Cons

**Pros:**

- Ease of Use (67 reviews)
- Features (47 reviews)
- Data Management (41 reviews)
- Integrations (33 reviews)
- Analytics (31 reviews)

**Cons:**

- Learning Curve (38 reviews)
- Complexity (25 reviews)
- Expensive (20 reviews)
- Difficult Setup (17 reviews)
- Difficulty (17 reviews)

  ### 5. [Workato](https://www.g2.com/products/workato/reviews)
  Workato is the #1-rated iPaaS and the leader in Enterprise MCP — the platform enterprises trust to unify integration, automation, and AI in one secure, cloud-native runtime. Trusted by over 12,000 customers including half the Fortune 500, Workato connects every system, process, and data source with 14,000+ pre-built connectors. What sets Workato apart: Enterprise MCP turns proven business processes into governed, agent-ready skills that any AI agent — Claude, ChatGPT, Cursor, or custom-built — can execute safely and predictably. No rip-and-replace required. Whether modernizing legacy integrations or deploying agentic AI at scale, Workato delivers the orchestration, governance, and trust needed in the enterprise.


  **Average Rating:** 4.7/5.0
  **Total Reviews:** 725

**User Satisfaction Scores:**

- **Has the product been a good partner in doing business?:** 9.4/10 (Category avg: 9.1/10)
- **Automation:** 9.2/10 (Category avg: 8.9/10)
- **Scalability:** 9.0/10 (Category avg: 8.7/10)
- **Auditing:** 8.3/10 (Category avg: 8.1/10)


**Seller Details:**

- **Seller:** [Workato](https://www.g2.com/sellers/workato)
- **Company Website:** https://www.workato.com
- **Year Founded:** 2013
- **HQ Location:** Mountain View, California
- **Twitter:** @Workato (3,592 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/3675685 (1,348 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Who Uses This:** Software Engineer, Senior Software Engineer
  - **Top Industries:** Computer Software, Information Technology and Services
  - **Company Size:** 43% Mid-Market, 33% Enterprise


#### Pros & Cons

**Pros:**

- Ease of Use (366 reviews)
- Integrations (245 reviews)
- Easy Integrations (232 reviews)
- Automation (198 reviews)
- Features (195 reviews)

**Cons:**

- Complexity (83 reviews)
- Learning Curve (77 reviews)
- Missing Features (77 reviews)
- Data Limitations (76 reviews)
- Expensive (71 reviews)

  ### 6. [Fivetran](https://www.g2.com/products/fivetran/reviews)
  Shaped by the real-world needs of data analysts, Fivetran technology is the smartest, fastest way to replicate your applications, databases, events and files into a high-performance cloud warehouse. Fivetran connectors deploy in minutes, require zero maintenance, and automatically adjust to source changes — so your data team can stop worrying about engineering and focus on driving insights.


  **Average Rating:** 4.3/5.0
  **Total Reviews:** 774

**User Satisfaction Scores:**

- **Has the product been a good partner in doing business?:** 8.7/10 (Category avg: 9.1/10)
- **Automation:** 9.0/10 (Category avg: 8.9/10)
- **Scalability:** 8.5/10 (Category avg: 8.7/10)
- **Auditing:** 7.4/10 (Category avg: 8.1/10)


**Seller Details:**

- **Seller:** [Fivetran](https://www.g2.com/sellers/fivetran)
- **Company Website:** https://www.fivetran.com/
- **Year Founded:** 2012
- **HQ Location:** Oakland, CA
- **Twitter:** @fivetran (5,717 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/fivetran/ (1,738 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Who Uses This:** Data Engineer, Data Analyst
  - **Top Industries:** Computer Software, Information Technology and Services
  - **Company Size:** 59% Mid-Market, 28% Small-Business


#### Pros & Cons

**Pros:**

- Ease of Use (203 reviews)
- Easy Setup (82 reviews)
- Easy Integration (73 reviews)
- Customer Support (64 reviews)
- User Interface (62 reviews)

**Cons:**

- Sync Issues (60 reviews)
- Expensive (46 reviews)
- Integration Issues (30 reviews)
- Pricing Issues (28 reviews)
- Learning Curve (27 reviews)

  ### 7. [SnapLogic Intelligent Integration Platform (IIP)](https://www.g2.com/products/snaplogic-intelligent-integration-platform-iip/reviews)
  SnapLogic is the leader in generative integration. As a pioneer in AI-led integration, the SnapLogic Platform accelerates digital transformation across the enterprise and empowers everyone to integrate faster and easier. Whether you are automating business processes, democratizing data, or delivering digital products and services, SnapLogic enables you to simplify your technology stack and take your enterprise further. Thousands of enterprises around the globe rely on SnapLogic to integrate, automate and orchestrate the flow of data across their business. Join the generative integration movement at snaplogic.com.


  **Average Rating:** 4.4/5.0
  **Total Reviews:** 371

**User Satisfaction Scores:**

- **Has the product been a good partner in doing business?:** 8.8/10 (Category avg: 9.1/10)
- **Automation:** 8.6/10 (Category avg: 8.9/10)
- **Scalability:** 8.4/10 (Category avg: 8.7/10)
- **Auditing:** 8.1/10 (Category avg: 8.1/10)


**Seller Details:**

- **Seller:** [SnapLogic](https://www.g2.com/sellers/snaplogic)
- **Company Website:** https://www.snaplogic.com
- **Year Founded:** 2006
- **HQ Location:** San Mateo, CA
- **Twitter:** @SnapLogic (7,354 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/210766/ (327 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Who Uses This:** Data Engineer, Consultant
  - **Top Industries:** Information Technology and Services, Computer Software
  - **Company Size:** 46% Enterprise, 36% Mid-Market


#### Pros & Cons

**Pros:**

- Ease of Use (85 reviews)
- Easy Integrations (70 reviews)
- Integrations (54 reviews)
- User Interface (50 reviews)
- Automation (43 reviews)

**Cons:**

- Performance Issues (31 reviews)
- Poor Performance (25 reviews)
- Technical Difficulties (25 reviews)
- Complexity (22 reviews)
- Error Reporting (22 reviews)

  ### 8. [FME Platform](https://www.g2.com/products/fme-platform/reviews)
  FME, made by Safe Software, is the only All-Data, Any-AI Enterprise Integration Platform connecting all your data, applications, and AI services. All Data Velocities - Whether it’s batch, event, or stream processing, FME delivers you no-code business orchestration and automation. All Data Locations - Wherever your data is - in the cloud, on-premises, or both - FME matches your data landscape with processing, increasing scalability, agility, and security. All Data Types - From databases to business systems to IoT, you name it, we connect it. As the only integration platform with support for spatial data, FME delivers new insights so you can make better decisions and stay ahead of the competition. Any AI Technology - Power your workflows with the right data at the right time regardless of modality, location or data velocity. FME powers real-time, context-aware automation, scaling AI where and how you need it.


  **Average Rating:** 4.7/5.0
  **Total Reviews:** 86

**User Satisfaction Scores:**

- **Has the product been a good partner in doing business?:** 8.9/10 (Category avg: 9.1/10)
- **Automation:** 9.5/10 (Category avg: 8.9/10)
- **Scalability:** 8.6/10 (Category avg: 8.7/10)
- **Auditing:** 8.6/10 (Category avg: 8.1/10)


**Seller Details:**

- **Seller:** [Safe Software](https://www.g2.com/sellers/safe-software)
- **Company Website:** https://fme.safe.com/
- **Year Founded:** 1993
- **HQ Location:** British Columbia, Canada
- **Twitter:** @SafeSoftware (4,978 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/50027/ (343 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Who Uses This:** GIS Analyst, GIS Technician
  - **Top Industries:** Computer Software, Information Technology and Services
  - **Company Size:** 39% Mid-Market, 27% Small-Business


#### Pros & Cons

**Pros:**

- Ease of Use (33 reviews)
- Data Management (19 reviews)
- Automation (18 reviews)
- Features (16 reviews)
- Data Transformation (15 reviews)

**Cons:**

- Complexity (10 reviews)
- Expensive (10 reviews)
- Learning Curve (7 reviews)
- Difficult Learning (6 reviews)
- Pricing Issues (6 reviews)

  ### 9. [Domo](https://www.g2.com/products/domo/reviews)
  Domo's AI and Data Products Platform empowers organizations to turn data into actionable insights and solutions. It allows users to seamlessly connect diverse data sources, prepare data for use, and generate dynamic reports and visualizations—all within a single interface. With built-in AI and automation capabilities, teams can easily build and use AI agents, streamline workflows, and create tailored solutions.


  **Average Rating:** 4.3/5.0
  **Total Reviews:** 983

**User Satisfaction Scores:**

- **Has the product been a good partner in doing business?:** 8.8/10 (Category avg: 9.1/10)
- **Automation:** 8.5/10 (Category avg: 8.9/10)
- **Scalability:** 7.9/10 (Category avg: 8.7/10)
- **Auditing:** 7.2/10 (Category avg: 8.1/10)


**Seller Details:**

- **Seller:** [Domo](https://www.g2.com/sellers/domo)
- **Company Website:** https://www.domo.com
- **Year Founded:** 2010
- **HQ Location:** American Fork, UT
- **Twitter:** @Domotalk (63,693 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/25237/ (1,334 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Who Uses This:** Data Analyst, Business Analyst
  - **Top Industries:** Computer Software, Marketing and Advertising
  - **Company Size:** 49% Mid-Market, 29% Enterprise


#### Pros & Cons

**Pros:**

- Ease of Use (248 reviews)
- Data Visualization (116 reviews)
- Intuitive (95 reviews)
- Easy Integrations (93 reviews)
- Integrations (88 reviews)

**Cons:**

- Learning Curve (66 reviews)
- Missing Features (59 reviews)
- Data Management Issues (55 reviews)
- Expensive (45 reviews)
- Complexity (43 reviews)

  ### 10. [5X](https://www.g2.com/products/5x/reviews)
  5X is an end-to-end data and AI platform. The platform organizes your data regardless of source or format. Whether you have a dedicated data team or not, our platform
transforms fragmented data into actionable insights and apps. The customer feedback we get most often is, "This is self-explanatory," and "It's super easy to use." And that is exactly what our goal was—to create a powerful, all-in-one platform that's incredibly easy to use.  The modern data stack has evolved. It's no longer about stitching together vendors. The next-generation modern data stack is an all-in-one platform that offers speed, simplicity, and decreased cost of ownership. That's exactly what we have created at 5X. Companies use 5X for multiple reasons: 1) Speed & productivity. All-in-one data platforms are incredibly efficient. We've seen companies build use cases on day 1.  Contact us to see if you qualify for a free 48 hour jumpstart! 🚀 2) Decrease your total cost of ownership by 30% compared to building your own platform. This doesn't account the people hours needed to support a platform build 🤯 3) Use our full stack data consultancy for support on data engineering & analytics 👨‍💻 5X was founded in 2020 with presence in the USA, Singapore, UK and India. Our global team is 70+ people strong and rapidly growing. We’ve recently raised our seed round from Flybridge Capital and backed by top founders from companies like Datadog, Preset, Astronomer, Mode, Rudderstack and other prominent angel investors. For more information, visit 5X.co We don't just talk about speed and simplicity; we back it up with proof. Speak to us about our 48-hour jumpstart where we can build an end-to-end use case for you in 48 hours for free.


  **Average Rating:** 4.9/5.0
  **Total Reviews:** 81

**User Satisfaction Scores:**

- **Has the product been a good partner in doing business?:** 9.8/10 (Category avg: 9.1/10)
- **Automation:** 9.5/10 (Category avg: 8.9/10)
- **Scalability:** 9.5/10 (Category avg: 8.7/10)
- **Auditing:** 9.4/10 (Category avg: 8.1/10)


**Seller Details:**

- **Seller:** [5X](https://www.g2.com/sellers/5x)
- **Company Website:** https://5x.co
- **Year Founded:** 2020
- **HQ Location:** San Francisco
- **Twitter:** @DataWith5x (49 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/datawith5x/ (128 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Top Industries:** Computer Software, Financial Services
  - **Company Size:** 56% Mid-Market, 40% Small-Business


#### Pros & Cons

**Pros:**

- Ease of Use (28 reviews)
- Customer Support (18 reviews)
- Features (14 reviews)
- Integrations (13 reviews)
- Data Integration (10 reviews)

**Cons:**

- Steep Learning Curve (5 reviews)
- Complex Setup (4 reviews)
- Feature Limitations (4 reviews)
- Learning Curve (4 reviews)
- Difficult Setup (3 reviews)

  ### 11. [Boomi Data Integration](https://www.g2.com/products/boomi-data-integration/reviews)
  Rivery's SaaS platform provides a unified solution for ELT pipelines, workflow orchestration, and data operations. Achieve more with less and create the most efficient, scalable data stack for your organization. Some of Rivery's features and capabilities: - Completely Automated SaaS Platform: Get setup and start connecting data in the Rivery platform in just a few minutes with little to no maintenance required. - Unified Data Ingestion, Transformation, & Orchestration: 100% data source capability, insight-ready data with both SQL and Python transformations, and complete workflow automation. - 200+ Native Connectors: Instantly connect to applications, databases, file storage options, and data warehouses with our fully-managed and always up-to-date connectors, including BigQuery, Redshift, Shopify, Snowflake, Amazon S3, Firebolt, Databricks, Salesforce, MySQL, PostgreSQL, and Rest API to name just a few. - Python Support: Have a data source that requires custom code? With Rivery’s native Python support, you can pull data from any system, no matter how complex the need. - Change Data Capture/Data Replication: Rivery’s best-in-class CDC support provides an easy, reliable and fast solution for replicating data from a database to your data warehouse. - 1-Click Data Apps: With Rivery Kits, deploy complete, production-level workflow templates in minutes with data models, pipelines, transformations, table schemas, and orchestration logic already defined for you based on best practices. - Data Development Lifecycle Support: Separate walled-off environments for each stage of your development, from dev and staging to production, making it easier to move fast without breaking things. Get version control, API, & CLI included. - Data Operations: With Rivery, you get centralized logging & reporting, monitoring & alerts, and data quality as part of a robust data operations layer for your data pipelines. - Solution-Led Support: Consistently rated the best support by G2, receive engineering-led assistance from Rivery to facilitate all your data needs. - Data Security: Industry-leading security and enterprise-grade privacy standards are built into Rivery’s network, product, and policies.


  **Average Rating:** 4.7/5.0
  **Total Reviews:** 120

**User Satisfaction Scores:**

- **Has the product been a good partner in doing business?:** 9.6/10 (Category avg: 9.1/10)
- **Automation:** 9.5/10 (Category avg: 8.9/10)
- **Scalability:** 9.3/10 (Category avg: 8.7/10)
- **Auditing:** 8.8/10 (Category avg: 8.1/10)


**Seller Details:**

- **Seller:** [Boomi](https://www.g2.com/sellers/boomi)
- **Year Founded:** 2000
- **HQ Location:** Chesterbrook, PA
- **Twitter:** @boomi (101,089 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/boomi-inc/ (2,874 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Who Uses This:** Data Engineer
  - **Top Industries:** Information Technology and Services, Computer Software
  - **Company Size:** 42% Mid-Market, 36% Small-Business


#### Pros & Cons

**Pros:**

- Ease of Use (5 reviews)
- Customer Support (4 reviews)
- Data Management (4 reviews)
- Automation (3 reviews)
- Implementation Ease (3 reviews)

**Cons:**

- Data Limitations (1 reviews)
- Information Deficiency (1 reviews)
- Insufficient Information (1 reviews)
- Lacking Features (1 reviews)
- Limited Features (1 reviews)

  ### 12. [Azure Data Factory](https://www.g2.com/products/azure-data-factory/reviews)
  Azure Data Factory (ADF) is a fully managed, serverless data integration service designed to simplify the process of ingesting, preparing, and transforming data from diverse sources. It enables organizations to construct and orchestrate Extract, Transform, Load (ETL) and Extract, Load, Transform (ELT) workflows in a code-free environment, facilitating seamless data movement and transformation across on-premises and cloud-based systems. Key Features and Functionality: - Extensive Connectivity: ADF offers over 90 built-in connectors, allowing integration with a wide array of data sources, including relational databases, NoSQL systems, SaaS applications, APIs, and cloud storage services. - Code-Free Data Transformation: Utilizing mapping data flows powered by Apache Spark™, ADF enables users to perform complex data transformations without writing code, streamlining the data preparation process. - SSIS Package Rehosting: Organizations can easily migrate and extend their existing SQL Server Integration Services (SSIS) packages to the cloud, achieving significant cost savings and enhanced scalability. - Scalable and Cost-Effective: As a serverless service, ADF automatically scales to meet data integration demands, offering a pay-as-you-go pricing model that eliminates the need for upfront infrastructure investments. - Comprehensive Monitoring and Management: ADF provides robust monitoring tools, allowing users to track pipeline performance, set up alerts, and ensure efficient operation of data workflows. Primary Value and User Solutions: Azure Data Factory addresses the complexities of modern data integration by providing a unified platform that connects disparate data sources, automates data workflows, and facilitates advanced data transformations. This empowers organizations to derive actionable insights from their data, enhance decision-making processes, and accelerate digital transformation initiatives. By offering a scalable, cost-effective, and code-free environment, ADF reduces the operational burden on IT teams and enables data engineers and business analysts to focus on delivering value through data-driven strategies.


  **Average Rating:** 4.6/5.0
  **Total Reviews:** 90

**User Satisfaction Scores:**

- **Has the product been a good partner in doing business?:** 9.1/10 (Category avg: 9.1/10)
- **Automation:** 9.2/10 (Category avg: 8.9/10)
- **Scalability:** 9.1/10 (Category avg: 8.7/10)
- **Auditing:** 8.4/10 (Category avg: 8.1/10)


**Seller Details:**

- **Seller:** [Microsoft](https://www.g2.com/sellers/microsoft)
- **Year Founded:** 1975
- **HQ Location:** Redmond, Washington
- **Twitter:** @microsoft (13,090,464 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/microsoft/ (227,697 employees on LinkedIn®)
- **Ownership:** MSFT

**Reviewer Demographics:**
  - **Who Uses This:** Data Engineer, Software Engineer
  - **Top Industries:** Information Technology and Services, Computer Software
  - **Company Size:** 61% Enterprise, 28% Mid-Market


#### Pros & Cons

**Pros:**

- Data Integration (7 reviews)
- Ease of Use (7 reviews)
- Connectors (6 reviews)
- Integrations (6 reviews)
- Scalability (5 reviews)

**Cons:**

- Debugging Difficulty (5 reviews)
- Difficult Debugging (4 reviews)
- Expensive (4 reviews)
- Feature Limitations (4 reviews)
- Complexity (3 reviews)

  ### 13. [IBM StreamSets](https://www.g2.com/products/ibm-streamsets/reviews)
  IBM StreamSets is a robust streaming data integration tool for hybrid, multi-cloud environments that enables real-time decision making. It allows ingestion and in-flight transformation of structured, unstructured, and semi-structured data from streaming sources, and reliably delivers trusted data into diverse destinations. Flexible deployment options promote security, cost-effectiveness and performance. With several pre-built connectors, an intuitive no-code/low-code interface, and automatic adaptability to data drifts, StreamSets accelerates data pipeline operationalization. It integrates with IBM’s broader data integration capabilities, enabling reliable pipelines that unify multiple data integration patterns, underpinned by data observability capabilities for continuous data quality monitoring and remediation. That’s why the largest companies in the world trust StreamSets to power millions of data pipelines for modern analytics, data science, smart applications, and hybrid integration.


  **Average Rating:** 4.0/5.0
  **Total Reviews:** 115

**User Satisfaction Scores:**

- **Has the product been a good partner in doing business?:** 8.2/10 (Category avg: 9.1/10)
- **Automation:** 7.7/10 (Category avg: 8.9/10)
- **Scalability:** 7.6/10 (Category avg: 8.7/10)
- **Auditing:** 7.2/10 (Category avg: 8.1/10)


**Seller Details:**

- **Seller:** [IBM](https://www.g2.com/sellers/ibm)
- **Year Founded:** 1911
- **HQ Location:** Armonk, NY
- **Twitter:** @IBM (708,000 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/1009/ (324,553 employees on LinkedIn®)
- **Ownership:** SWX:IBM

**Reviewer Demographics:**
  - **Who Uses This:** Data Engineer, Software Engineer
  - **Top Industries:** Information Technology and Services, Computer Software
  - **Company Size:** 42% Enterprise, 33% Mid-Market


#### Pros & Cons

**Pros:**

- Ease of Use (30 reviews)
- User Interface (16 reviews)
- Data Management (15 reviews)
- Data Pipelining (15 reviews)
- Integrations (14 reviews)

**Cons:**

- Learning Curve (13 reviews)
- Expensive (10 reviews)
- Learning Difficulty (8 reviews)
- Slow Performance (8 reviews)
- Steep Learning Curve (8 reviews)

  ### 14. [Skyvia](https://www.g2.com/products/skyvia/reviews)
  Skyvia is a no-code cloud data integration and data pipeline platform that enables ETL, ELT, Reverse ETL, data migration, one-way and bi-directional data sync, workflow automation, real-time connectivity, and much more. Benefits of Using Skyvia: • Cost efficiency: With affordable, flexible pricing plans for each product, Skyvia suites for businesses of any size. • Ease of Use: Based on extensive customer feedback, ease of use is Skyvia's strongest quality. • Flexibility: Skyvia provides adaptable, no-code integration tools for both basic and advanced business scenarios. • Trust: Skyvia is trusted by thousands of data-driven organizations around the globe. With a vast library of 200+ connectors, Skyvia provides seamless integration among various cloud applications, databases, and data warehouses, including Salesforce, Dynamics CRM, QuickBooks Online, SQL Server, Amazon Redshift, Google BigQuery, and others.


  **Average Rating:** 4.8/5.0
  **Total Reviews:** 305

**User Satisfaction Scores:**

- **Has the product been a good partner in doing business?:** 9.3/10 (Category avg: 9.1/10)
- **Automation:** 9.4/10 (Category avg: 8.9/10)
- **Scalability:** 9.3/10 (Category avg: 8.7/10)
- **Auditing:** 9.0/10 (Category avg: 8.1/10)


**Seller Details:**

- **Seller:** [Devart](https://www.g2.com/sellers/devart)
- **Year Founded:** 1997
- **HQ Location:** Wilmington, Delaware, USA
- **Twitter:** @DevartSoftware (1,738 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/800325/ (254 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Who Uses This:** CEO, CTO
  - **Top Industries:** Information Technology and Services, Computer Software
  - **Company Size:** 52% Small-Business, 39% Mid-Market


#### Pros & Cons

**Pros:**

- Ease of Use (50 reviews)
- Easy Integrations (34 reviews)
- Easy Setup (33 reviews)
- Setup Ease (31 reviews)
- Data Management (27 reviews)

**Cons:**

- Information Deficiency (8 reviews)
- Difficult Setup (7 reviews)
- Feature Limitations (7 reviews)
- Learning Curve (7 reviews)
- Poor Documentation (7 reviews)

  ### 15. [dbt](https://www.g2.com/products/dbt/reviews)
  dbt is a transformation workflow that lets data teams quickly and collaboratively deploy analytics code following software engineering best practices like modularity, portability, CI/CD, and documentation. Now anyone who knows SQL can build production-grade data pipelines.


  **Average Rating:** 4.7/5.0
  **Total Reviews:** 198

**User Satisfaction Scores:**

- **Has the product been a good partner in doing business?:** 8.6/10 (Category avg: 9.1/10)
- **Automation:** 9.5/10 (Category avg: 8.9/10)
- **Scalability:** 9.2/10 (Category avg: 8.7/10)
- **Auditing:** 8.2/10 (Category avg: 8.1/10)


**Seller Details:**

- **Seller:** [Fivetran](https://www.g2.com/sellers/fivetran)
- **Year Founded:** 2012
- **HQ Location:** Oakland, CA
- **Twitter:** @fivetran (5,717 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/fivetran/ (1,738 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Who Uses This:** Data Engineer, Analytics Engineer
  - **Top Industries:** Information Technology and Services, Computer Software
  - **Company Size:** 57% Mid-Market, 27% Small-Business


#### Pros & Cons

**Pros:**

- Ease of Use (38 reviews)
- Features (22 reviews)
- Automation (19 reviews)
- Transformation (17 reviews)
- Integrations (15 reviews)

**Cons:**

- Limited Functionality (14 reviews)
- Dependency Issues (12 reviews)
- Steep Learning Curve (10 reviews)
- Error Handling (9 reviews)
- Error Reporting (9 reviews)

  ### 16. [Alteryx](https://www.g2.com/products/alteryx/reviews)
  Alteryx, through it's Alteryx One platform, helps enterprises transform complex, disconnected data into a clean, AI-ready state. Whether you’re creating financial forecasts, analyzing supplier performance, segmenting customer data, analyzing employee retention, or building competitive AI applications from your proprietary data, Alteryx One makes it easy to cleanse, blend, and analyze data to unlock the unique insights that drive impactful decisions. AI-Guided Analytics Alteryx automates and simplifies every stage of data preparation and analysis, from validation and enrichment to predictive analytics and automated insights. Incorporate generative AI directly into your workflows to streamline complex data tasks and generate insights faster. Unmatched flexibility, whether you prefer code-free workflows, natural language commands, or low-code options, Alteryx adapts to your needs. Trusted. Secure. Enterprise-Ready. Alteryx is trusted by over half of the Global 2000 and 19 of the top 20 global banks. With built-in automation, governance, and security, your workflows can scale and maintain compliance while delivering consistent results. And it doesn’t matter if your systems are on-premises, hybrid, or in the cloud; Alteryx fits effortlessly into your infrastructure. Easy to Use. Deeply Connected. What truly sets Alteryx apart is our focus on efficiency and ease of use for analysts and our active community of 700,000 Alteryx users to support you at every step of your journey. With seamless integration to data everywhere including platforms like Databricks, Snowflake, AWS, Google, SAP, and Salesforce, our platform helps unify siloed data and accelerate getting to insights. Visit Alteryx.com for more information, and to start your free trial.


  **Average Rating:** 4.6/5.0
  **Total Reviews:** 646

**User Satisfaction Scores:**

- **Has the product been a good partner in doing business?:** 8.9/10 (Category avg: 9.1/10)


**Seller Details:**

- **Seller:** [Alteryx](https://www.g2.com/sellers/alteryx)
- **Company Website:** https://www.alteryx.com
- **Year Founded:** 1997
- **HQ Location:** Irvine, CA
- **Twitter:** @alteryx (26,204 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/903031/ (2,268 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Who Uses This:** Data Analyst, Analyst
  - **Top Industries:** Financial Services, Accounting
  - **Company Size:** 62% Enterprise, 22% Mid-Market


#### Pros & Cons

**Pros:**

- Ease of Use (333 reviews)
- Automation (148 reviews)
- Intuitive (132 reviews)
- Easy Learning (102 reviews)
- Efficiency (102 reviews)

**Cons:**

- Expensive (88 reviews)
- Learning Curve (80 reviews)
- Missing Features (62 reviews)
- Learning Difficulty (55 reviews)
- Slow Performance (41 reviews)

  ### 17. [Coupler.io](https://www.g2.com/products/coupler-io/reviews)
  Coupler.io is a no-code data integration platform that provides instant access to 400+ sources and a world of insights — all in one place. It allows you to collect data from various cloud sources, transform it, and load it into spreadsheets, BI tools, data warehouses, and AI agents. No complex setup or deep technical expertise required. Trusted by 1M+ users, including companies like Uber, Netflix, and Airbus, Coupler.io streamlines data processes for marketers, data analysts, business owners, sales teams, e-commerce businesses, and financial professionals. With 1800+ ready-made integrations, Coupler.io allows you to automatically collect data from Google Analytics, Facebook Ads, GoHighLevel, Shopify, QuickBooks, and many other apps. You can blend data from multiple sources into Google Sheets, Looker Studio, Power BI, BigQuery, Claude, ChatGPT, and other destinations. Coupler.io makes data transformation easy with data joining and appending functions, filtering, formulas, and data set templates. To quick-start with reporting, explore Coupler.io's in-app dashboards and free dashboard templates gallery for third-party tools. You can also build custom dashboards from scratch. AI Insights interprets dashboards in seconds, highlighting trends and anomalies and providing actionable recommendations. Coupler.io's AI integrations enable real-time analysis of large, blended data through natural language conversations in AI chats. These allow businesses to make data-driven decisions, scale operations, and improve reporting efficiency. Coupler.io is a SOC 2-certified, reliable platform that follows the highest data security and privacy standards to keep your data protected. Take full control of your data, identify what works, and scale it with Coupler.io for holistic data management and analysis!


  **Average Rating:** 4.8/5.0
  **Total Reviews:** 101

**User Satisfaction Scores:**

- **Has the product been a good partner in doing business?:** 9.4/10 (Category avg: 9.1/10)
- **Automation:** 9.7/10 (Category avg: 8.9/10)
- **Scalability:** 8.9/10 (Category avg: 8.7/10)
- **Auditing:** 8.3/10 (Category avg: 8.1/10)


**Seller Details:**

- **Seller:** [Railsware](https://www.g2.com/sellers/railsware)
- **Year Founded:** 2007
- **HQ Location:** Kraków
- **Twitter:** @railsware (2,116 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/122084/ (184 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Top Industries:** Non-Profit Organization Management, Marketing and Advertising
  - **Company Size:** 66% Small-Business, 29% Mid-Market


#### Pros & Cons

**Pros:**

- Ease of Use (20 reviews)
- Time-Saving (19 reviews)
- Automation (18 reviews)
- Integrations (15 reviews)
- Data Integration (14 reviews)

**Cons:**

- Difficult Setup (5 reviews)
- Complex Setup (4 reviews)
- Learning Curve (4 reviews)
- Expensive (3 reviews)
- Lack of Information (3 reviews)

  ### 18. [Matia](https://www.g2.com/products/matia/reviews)
  Matia is a data operations platform that enables modern data teams to build, manage, and monitor end-to-end data pipelines in one place. Matia allows data teams to spend time managing their data, instead of their tools. Matia combines ingestion, reverse ETL, data cataloging, and observability into a single, unified interface. Rather than stitching together multiple tools for data movement, observability, and metadata tracking, teams use Matia to streamline their workflow, reduce vendor bloat, and improve data trust across the organization. Common use cases include syncing operational data into warehouse destinations, monitoring pipeline health with built-in alerts, documenting data assets automatically, and aligning data delivery with business-critical SLAs. Teams adopt Matia to simplify their stack, reduce engineering overhead, and create more transparent, reliable data infrastructure.


  **Average Rating:** 4.9/5.0
  **Total Reviews:** 32

**User Satisfaction Scores:**

- **Has the product been a good partner in doing business?:** 10.0/10 (Category avg: 9.1/10)
- **Automation:** 9.9/10 (Category avg: 8.9/10)
- **Scalability:** 9.8/10 (Category avg: 8.7/10)
- **Auditing:** 9.6/10 (Category avg: 8.1/10)


**Seller Details:**

- **Seller:** [Matia](https://www.g2.com/sellers/matia)
- **Company Website:** https://www.matia.io
- **Year Founded:** 2023
- **HQ Location:** Miami, US
- **LinkedIn® Page:** http://linkedin.com/company/matia-data (39 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Top Industries:** Financial Services, Computer Software
  - **Company Size:** 59% Mid-Market, 25% Small-Business


#### Pros & Cons

**Pros:**

- Customer Support (25 reviews)
- Ease of Use (18 reviews)
- Features (18 reviews)
- Integrations (13 reviews)
- Reliability (12 reviews)

**Cons:**

- Limited Connectors (4 reviews)
- Missing Features (4 reviews)
- Limited Features (3 reviews)
- Limited Integrations (3 reviews)
- Not User-Friendly (3 reviews)

  ### 19. [HubSpot Data Hub](https://www.g2.com/products/hubspot-data-hub/reviews)
  Operations Hub connects, cleanses, and automates customer data across the HubSpot CRM, providing operations teams with tools to maintain data quality, ensure system integration, and streamline business processes. Core Value Proposition: Operations Hub addresses critical operational challenges: disconnected data across applications, manual data entry consuming team time, data quality issues undermining business decisions, and complex automation requirements existing tools cannot handle. The platform offers native integrations with other applications to create a more efficient, aligned, and agile business. Key Capabilities: Data Integration: Operations Hub connects contacts, leads, and company data between HubSpot and external applications bidirectionally and in real-time. This creates a unified customer data foundation rather than requiring manual data transfer. Data Quality Management: The platform includes tools that maintain a clean database, allowing operations teams to save hours of manual data validation and correction work. Process Automation: Operations Hub enables complex business process automation across systems, connecting trigger events in one application to automated actions in another. This streamlines internal workflows and reduces manual coordination. Unified Customer View: By connecting all customer data sources to the HubSpot CRM platform, Operations Hub creates a single source of truth that sales, marketing, and service teams can reference for customer interactions. Operations Hub vs. Alternatives: Unlike standalone integration platforms (iPaaS) requiring technical expertise to configure and maintain, Operations Hub provides native HubSpot integration with a visual interface designed for operations professionals rather than developers. This reduces implementation time and ongoing maintenance requirements. Operations Hub eliminates manual data entry and data validation by automating these workflows. The platform guarantees up-to-date data and maintains a clean database without constant manual intervention. Who Should Use Operations Hub: Operations Hub serves operations teams managing data across multiple systems, organizations experiencing data quality issues affecting business decisions, and companies needing to automate complex cross-system workflows without extensive technical resources. The platform enables business agility as organizations grow. Outcome: Operations Hub supercharges your HubSpot CRM with a complete toolkit to connect, clean, and automate customer data, uniting all customer data into one connected platform that results in a friction-free customer experience.


  **Average Rating:** 4.5/5.0
  **Total Reviews:** 557

**User Satisfaction Scores:**

- **Has the product been a good partner in doing business?:** 9.1/10 (Category avg: 9.1/10)
- **Automation:** 8.3/10 (Category avg: 8.9/10)
- **Scalability:** 10.0/10 (Category avg: 8.7/10)
- **Auditing:** 8.9/10 (Category avg: 8.1/10)


**Seller Details:**

- **Seller:** [HubSpot](https://www.g2.com/sellers/hubspot)
- **Company Website:** https://www.HubSpot.com
- **Year Founded:** 2006
- **HQ Location:** Cambridge, MA
- **Twitter:** @HubSpot (785,472 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/68529/ (11,979 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Who Uses This:** CEO, Owner
  - **Top Industries:** Information Technology and Services, Marketing and Advertising
  - **Company Size:** 67% Small-Business, 29% Mid-Market


#### Pros & Cons

**Pros:**

- Ease of Use (119 reviews)
- Automation (90 reviews)
- Data Management (88 reviews)
- Integrations (65 reviews)
- Efficiency (48 reviews)

**Cons:**

- Limitations (58 reviews)
- Missing Features (40 reviews)
- Learning Curve (37 reviews)
- Expensive (33 reviews)
- Complexity (27 reviews)

  ### 20. [Parabola](https://www.g2.com/products/parabola/reviews)
  Parabola is a workflow builder that makes it easy to organize and transform messy data from anywhere—even PDFs, emails, and spreadsheets—so you can automate the work you thought would always be manual. Teams at fast-moving companies like Brooklinen, On Running, and Flexport use Parabola to save hundreds of hours and finally take on the projects that used to feel out of reach. Whether it’s reconciling inventory across multiple 3PLs, auditing invoices, or manually exporting the same report every Monday, Parabola gives teams the power to automate it—all without needing engineering support.


  **Average Rating:** 4.9/5.0
  **Total Reviews:** 51

**User Satisfaction Scores:**

- **Has the product been a good partner in doing business?:** 9.8/10 (Category avg: 9.1/10)
- **Automation:** 9.6/10 (Category avg: 8.9/10)
- **Scalability:** 9.3/10 (Category avg: 8.7/10)
- **Auditing:** 8.0/10 (Category avg: 8.1/10)


**Seller Details:**

- **Seller:** [Parabola](https://www.g2.com/sellers/parabola)
- **Year Founded:** 2017
- **HQ Location:** San Francisco, CA
- **Twitter:** @parabolahq
- **LinkedIn® Page:** https://www.linkedin.com/company/7590028/ (80 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Top Industries:** Consumer Goods, Computer Software
  - **Company Size:** 47% Small-Business, 45% Mid-Market


#### Pros & Cons

**Pros:**

- Automation (18 reviews)
- Ease of Use (15 reviews)
- Intuitive (9 reviews)
- Time-saving (9 reviews)
- Time-Saving (9 reviews)

**Cons:**

- Limitations (5 reviews)
- Learning Curve (3 reviews)
- Time-Consumption (3 reviews)
- Data Inaccuracy (2 reviews)
- Limited Export Options (2 reviews)

  ### 21. [Coefficient](https://www.g2.com/products/coefficient/reviews)
  Coefficient is a new way to work with your company data better, faster, and more accurately without ever leaving your spreadsheet, integrating with the tools you already use. Install the Coefficient Excel or Google Sheets extension and use it in a new or existing sheet in seconds. Once installed, Coefficient lives as a sidebar companion so your company data is only a couple of clicks away at any time. Any data source that you work with is available directly in your Coefficient sidebar – such as Salesforce, HubSpot, Snowflake, NetSuite, QuickBooks, MySQL, and Looker – with the ability to consolidate your data from multiple systems into one spreadsheet. Use Coefficient filters to easily customize your imports to only work with the data you need, keeping your spreadsheets performant. Quickly go back anytime to add more data in the same report. Never rebuild the same analysis twice by keeping your data up to date with scheduled updates. And, use Coefficient alerts to trigger Slack or email messages anytime your spreadsheet updates. Now, you can turn your spreadsheet into the most flexible, powerful monitoring system across all of your company data. Say “goodbye” to manual data workflows and “hello” to connected spreadsheets.


  **Average Rating:** 4.7/5.0
  **Total Reviews:** 175

**User Satisfaction Scores:**

- **Has the product been a good partner in doing business?:** 9.0/10 (Category avg: 9.1/10)
- **Automation:** 9.3/10 (Category avg: 8.9/10)
- **Scalability:** 9.3/10 (Category avg: 8.7/10)
- **Auditing:** 8.6/10 (Category avg: 8.1/10)


**Seller Details:**

- **Seller:** [Coefficient](https://www.g2.com/sellers/coefficient)
- **Company Website:** https://coefficient.io/
- **Year Founded:** 2020
- **HQ Location:** Palo Alto, CA
- **Twitter:** @coefficient_io (351 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/coefficientworks/ (70 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Top Industries:** Computer Software, Information Technology and Services
  - **Company Size:** 49% Mid-Market, 35% Small-Business


#### Pros & Cons

**Pros:**

- Ease of Use (72 reviews)
- Automation (42 reviews)
- Integrations (42 reviews)
- Time-saving (36 reviews)
- Easy Integrations (31 reviews)

**Cons:**

- Limited Features (18 reviews)
- Feature Limitations (17 reviews)
- Limitations (13 reviews)
- Missing Features (12 reviews)
- Integration Issues (11 reviews)

  ### 22. [Clarisights](https://www.g2.com/products/clarisights/reviews)
  Clarisights is the leading marketing analytics platform for Enterprises. Connect, visualize and explore all your marketing data in one place. Go from a cross-channel overview to in-depth campaign deep dives in a few clicks. From questions to insights in minutes. With Clarisights, performance marketers can move freely with data to iterate fast and accelerate testing cycles. Without relying on SQL, waiting for data teams or manual reporting in spreadsheets. Trusted by the most sophisticated Marketing teams, including those at Uber, Delivery Hero, HelloFresh, About You, and On.


  **Average Rating:** 4.9/5.0
  **Total Reviews:** 63

**User Satisfaction Scores:**

- **Has the product been a good partner in doing business?:** 9.5/10 (Category avg: 9.1/10)
- **Automation:** 9.8/10 (Category avg: 8.9/10)
- **Scalability:** 9.7/10 (Category avg: 8.7/10)
- **Auditing:** 9.9/10 (Category avg: 8.1/10)


**Seller Details:**

- **Seller:** [Clarisights](https://www.g2.com/sellers/clarisights)
- **Year Founded:** 2018
- **HQ Location:** Lewes, US
- **Twitter:** @Clarisights (1,119 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/clarisights/ (39 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Top Industries:** Consumer Goods, Apparel & Fashion
  - **Company Size:** 79% Enterprise, 17% Mid-Market


#### Pros & Cons

**Pros:**

- Ease of Use (14 reviews)
- Helpful (10 reviews)
- Intuitive (9 reviews)
- Reporting (8 reviews)
- Analytics (7 reviews)

**Cons:**

- Integration Issues (2 reviews)
- Learning Curve (2 reviews)
- Campaign Management (1 reviews)
- Data Limitations (1 reviews)
- Lack of Customization (1 reviews)

  ### 23. [AWS Glue](https://www.g2.com/products/aws-glue/reviews)
  AWS Glue is a serverless data integration service that makes it easier for analytics users to discover, prepare, move, and integrate data from multiple sources for analytics, machine learning, and application develop-ment. You can discover and connect to 70+ diverse data sources, manage your data in a centralized data catalog, and visually create, run, and monitor ETL pipelines to load data into your data lakes. You can im-mediately search and query catalogued data using Amazon Athena, Amazon EMR, and Amazon Redshift Spectrum.


  **Average Rating:** 4.3/5.0
  **Total Reviews:** 191

**User Satisfaction Scores:**

- **Has the product been a good partner in doing business?:** 8.8/10 (Category avg: 9.1/10)
- **Automation:** 8.8/10 (Category avg: 8.9/10)
- **Scalability:** 8.9/10 (Category avg: 8.7/10)
- **Auditing:** 8.7/10 (Category avg: 8.1/10)


**Seller Details:**

- **Seller:** [Amazon Web Services (AWS)](https://www.g2.com/sellers/amazon-web-services-aws-3e93cc28-2e9b-4961-b258-c6ce0feec7dd)
- **Year Founded:** 2006
- **HQ Location:** Seattle, WA
- **Twitter:** @awscloud (2,220,862 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/amazon-web-services/ (156,424 employees on LinkedIn®)
- **Ownership:** NASDAQ: AMZN

**Reviewer Demographics:**
  - **Who Uses This:** Data Engineer, Software Engineer
  - **Top Industries:** Information Technology and Services, Computer Software
  - **Company Size:** 48% Enterprise, 29% Mid-Market


#### Pros & Cons

**Pros:**

- Ease of Use (6 reviews)
- Data Integration (3 reviews)
- ETL Solutions (3 reviews)
- Features (3 reviews)
- Simple (3 reviews)

**Cons:**

- Slow Performance (3 reviews)
- Debugging Difficulty (2 reviews)
- Difficult Debugging (2 reviews)
- Performance Issues (2 reviews)
- Time-Consuming (2 reviews)

  ### 24. [Singular](https://www.g2.com/products/singular/reviews)
  Singular is the only end-to-end marketing attribution and analytics platform that uncovers true ROI across all marketing channels. We transform complex marketing data into actionable insights by unifying campaign data from thousands of channels with cross-device attribution data. Leading brands like LinkedIn, Nike, WB Games, and Rovio rely on Singular to maximize every marketing dollar, eliminate wasted spend, and drive higher user retention. With superior ROI reporting, advanced fraud prevention, user engagement capabilities, and unmatched data accessibility, marketers can finally drive faster growth with smarter insights.


  **Average Rating:** 4.6/5.0
  **Total Reviews:** 491

**User Satisfaction Scores:**

- **Has the product been a good partner in doing business?:** 9.2/10 (Category avg: 9.1/10)
- **Automation:** 8.9/10 (Category avg: 8.9/10)
- **Scalability:** 8.9/10 (Category avg: 8.7/10)
- **Auditing:** 8.3/10 (Category avg: 8.1/10)


**Seller Details:**

- **Seller:** [Singular](https://www.g2.com/sellers/singular)
- **Company Website:** https://www.singular.net
- **Year Founded:** 2014
- **HQ Location:** Palo Alto, California
- **Twitter:** @TweetSingular (1,314 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/3739623/ (363 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Who Uses This:** User Acquisition Manager, Marketing Manager
  - **Top Industries:** Computer Games, Marketing and Advertising
  - **Company Size:** 52% Mid-Market, 27% Small-Business


#### Pros & Cons

**Pros:**

- Customer Support (80 reviews)
- Ease of Use (64 reviews)
- Helpful (47 reviews)
- Features (46 reviews)
- Reporting (36 reviews)

**Cons:**

- Poor Interface Design (18 reviews)
- Poor UI (18 reviews)
- Limitations (16 reviews)
- Data Limitations (15 reviews)
- Limited Attribution Capabilities (15 reviews)

  ### 25. [ILUM](https://www.g2.com/products/ilum-ilum/reviews)
  Ilum: A Data Platform Built by Data Engineers, for Data Engineers Ilum is a Data Lakehouse platform that unifies data management, distributed processing, analytics, and AI workflows for AI engineers, data engineers, data scientists, and analysts. It belongs to the Data Platform, Data Lakehouse, and Data Engineering software categories and supports flexible deployment across cloud, on-premise, and hybrid environments. Ilum enables technical teams to build, operate, and scale modern data infrastructure using open standards. It integrates tools for batch processing, stream processing, notebook-based exploration, workflow orchestration, and business intelligence, All In a Single Platform. Ilum supports modern open table formats like Delta Lake, Apache Iceberg, Apache Hudi, and Apache Paimon. It also offers native integration with Apache Spark and Trino for compute, with Apache Flink support currently in development. Key features include: - SQL Editor: Query Delta, Iceberg, Hudi, or Spark SQL with autocomplete, result previews, and metadata inspection. - Data Lineage & Catalog: Visualize data flow using OpenLineage and explore datasets through a searchable Data Catalog. - Notebook Integration: Use built-in Jupyter notebooks pre-wired to Spark, metadata, and your data environment for exploration or modeling. - Spark Job Management: Submit, monitor, and debug Spark jobs with integrated logs, metrics, scheduling, and a built-in Spark History Server. - Trino Support: Run federated queries across multiple data sources using Trino directly from within Ilum. - Declarative Pipelines: Define repeatable ETL and analytics pipelines, with dependency tracking and recovery logic. - Automatic ERD Diagrams: Instantly generate ER diagrams from schemas to aid in data understanding and onboarding. - ML Experimentation & Tracking: Includes MLflow for managing experiments, tracking parameters, metrics, and artifacts, fully integrated with notebooks and data pipelines to streamline model development workflows. - AI Integration & Deployment: Supports both classical ML and modern AI use cases, including GenAI workflows, vector search, and embedding-based applications. Models can be registered, versioned, and deployed for inference within declarative pipelines. - Built-in AI Agent Interface: Ilum integrates, providing a GPT-style interface to interact with your data, trigger pipelines, generate SQL, or explore metadata using natural language, bringing GenAI capabilities directly into your data platform. - BI Dashboards: Native support for Apache Superset, with JDBC integration for Tableau, Power BI, and other BI tools. Additional highlights: - Multi-Cluster Management: Connect multiple Spark or Kubernetes clusters to scale and isolate workloads. - Fine-Grained Access Control: LDAP, OAuth2, and Hydra integration for secure, role-based access. - Hybrid Ready: Designed to replace Databricks or Cloudera in environments where cloud adoption is partial, regulated, or not possible.


  **Average Rating:** 4.9/5.0
  **Total Reviews:** 23

**User Satisfaction Scores:**

- **Has the product been a good partner in doing business?:** 9.7/10 (Category avg: 9.1/10)
- **Automation:** 10.0/10 (Category avg: 8.9/10)
- **Scalability:** 10.0/10 (Category avg: 8.7/10)
- **Auditing:** 10.0/10 (Category avg: 8.1/10)


**Seller Details:**

- **Seller:** [Ilum](https://www.g2.com/sellers/ilum)
- **Company Website:** https://ilum.cloud/
- **Year Founded:** 2019
- **HQ Location:** Santa Fe, US
- **Twitter:** @IlumCloud (18 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/ilum-cloud/ (4 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Top Industries:** Telecommunications
  - **Company Size:** 52% Enterprise, 35% Mid-Market


#### Pros & Cons

**Pros:**

- Ease of Use (17 reviews)
- Features (17 reviews)
- Integrations (17 reviews)
- Setup Ease (16 reviews)
- Easy Integrations (15 reviews)

**Cons:**

- Complex Setup (9 reviews)
- Difficult Setup (9 reviews)
- Learning Curve (9 reviews)
- UX Improvement (8 reviews)
- Complexity (7 reviews)



## Parent Category

[Cloud Data Integration Software](https://www.g2.com/categories/cloud-data-integration)



## Related Categories

- [iPaaS Software](https://www.g2.com/categories/ipaas)
- [Big Data Integration Platforms](https://www.g2.com/categories/big-data-integration-platforms)
- [Data Extraction Tools](https://www.g2.com/categories/data-extraction-tools)



---

## Buyer Guide

### What You Should Know About ETL Tools

### ETL software buying insights at a glance

Organizations today manage data across multiple applications, databases, and cloud environments. [ETL tools](https://www.g2.com/categories/etl-tools) help teams extract, transform, and load that data into centralized systems where it can be analyzed and used for reporting or operational decision-making. As companies adopt [cloud data warehouses](https://www.g2.com/categories/data-warehouse) and modern analytics stacks, these solutions play an important role in keeping data pipelines reliable and consistent. 

The best ETL tools help organizations reduce manual scripting, maintain consistent data pipelines, and support large volumes of data across multiple integrations. As data environments grow more complex, ETL providers increasingly focus on simplifying integrations and enabling faster access to analytics-ready data.

Common use cases focus on simplifying how data moves and gets prepared across systems. Teams use these tools to automate pipelines between SaaS apps, databases, and warehouses, consolidate data for unified reporting, and transform raw inputs into analytics-ready datasets for [BI tools](https://www.g2.com/categories/business-intelligence). They also help maintain consistent, reliable data flows across distributed environments, supporting cloud data warehouses and modern analytics platforms.

Pricing varies across the category depending on the number of integrations, pipeline volume, and transformation complexity. Many vendors use usage-based pricing models tied to data volume or connectors. Entry-level plans often support smaller teams or limited pipelines, while enterprise deployments add advanced monitoring, governance, and scalability capabilities.

### Top 5 FAQs from software buyers

- How do ETL tools support modern data stacks and cloud-based data architectures?
- How well do ETL platforms integrate with cloud data warehouses like BigQuery, Snowflake, or Redshift?
- Which ETL tools simplify pipeline management and reduce maintenance overhead for data teams?
- What level of scalability and performance do ETL solutions provide for large-scale data pipelines?
- Which ETL providers offer the broadest integration support across SaaS applications, databases, and APIs?

G2’s top-rated ETL tools, based on verified reviews, include [Google Cloud BigQuery](https://www.g2.com/products/google-cloud-bigquery/reviews), [Databricks](https://www.g2.com/products/databricks/reviews), [Domo](https://www.g2.com/products/domo/reviews), [Workato](https://www.g2.com/products/workato/reviews), and [SnapLogic Intelligent Integration Platform (IIP)](https://www.g2.com/products/snaplogic-intelligent-integration-platform-iip/reviews).

### What are the top-reviewed ETL Tools on G2?

[**Google Cloud BigQuery**](https://www.g2.com/products/google-cloud-bigquery/reviews)

- Number of Reviews: 324
- Satisfaction: 98
- Market Score: 99
- G2 Score: 98

[**Databricks**](https://www.g2.com/products/databricks/reviews)

- Number of Reviews: 279
- Satisfaction: 100
- Market Score: 81
- G2 Score: 90

[**Domo**](https://www.g2.com/products/domo/reviews)

- Number of Reviews: 380
- Satisfaction: 88
- Market Score: 73
- G2 Score: 80

[**Workato**](https://www.g2.com/products/workato/reviews)

- Number of Reviews: 224
- Satisfaction: 94
- Market Score: 62
- G2 Score: 78

[**SnapLogic Intelligent Integration Platform (IIP)**](https://www.g2.com/products/snaplogic-intelligent-integration-platform-iip/reviews)

- Number of Reviews: 172
- Satisfaction: 94
- Market Score: 60
- G2 Score: 77

**Satisfaction** reflects user-reported ratings, including ease of use, support, and feature fit. ([Source 2](https://www.g2.com/reports))

**Market Presence** scores combine review and external signals that indicate market momentum and footprint. ([Source 2](https://www.g2.com/reports))

**G2 Score** is a weighted composite of Satisfaction and Market Presence. ([Source 2](https://www.g2.com/reports))

Learn how G2 scores products. ([Source 1](https://documentation.g2.com/docs/research-scoring-methodologies?_gl=1*5vlk6s*_gcl_au*MTAwMzU5MzUxLjE3NjM0MTg0NzYuNjY0NTIxMTY0LjE3NjQ2MTc0NzcuMTc2NDYxNzQ3Nw..*_ga*NzY1MDU0NjE3LjE3NjM0NzQ3ODM.*_ga_MFZ5NDXZ5F*czE3NjYwODk1MTMkbzY3JGcxJHQxNzY2MDkyMjQyJGo1NyRsMCRoMA..))

### What I Often See in ETL Tools

#### Feedback Pros: What Users Consistently Appreciate

• **Visual pipeline builders simplify complex multi-source data integrations**

_“I love how the SnapLogic Intelligent Integration Platform (IIP) makes building integrations so easy with its AI-powered and low-code interface, which significantly streamlines design and maintenance for both technical and non-technical users. This platform guides the pipeline design and reduces the manual effort, aligning with its AI-driven workflow approach, and it has been instrumental in helping me automate workflows, improve data flow efficiency, and reduce the integration effort significantly. The initial setup was very easy because it's a cloud-based, self-service platform that minimizes installation effort and helps teams get started quickly. I highly recommend SnapLogic IIP for organizations looking to modernize and accelerate their integration strategy, and I would rate it a 9 for its ease of use.”_

- [Sanket N.](https://www.g2.com/products/snaplogic-intelligent-integration-platform-iip/reviews/snaplogic-intelligent-integration-platform-iip-review-12380685), SnapLogic Intelligent Integration Platform (IIP) review

• **Extensive connectors enable fast integration across SaaS and databases**

_“We use this every day as a vital part of an integration between our website and database. Easy to use with a number of different integrations available at your fingertips. Assistance was always an email away.”_

- [Nick E.](https://www.g2.com/products/skyvia/reviews/skyvia-review-12443772), Skyvia review

• **Automation capabilities reduce manual pipeline maintenance and data preparation**

_“Workato is an excellent tool for automating tasks and improving processes. What I find truly impressive is that we no longer have to rely on our ERP vendor for new features or automations; instead, we can handle everything ourselves using Workato. Personally, I have implemented numerous enhancements that have greatly benefited the Finance team, resulting in an estimated annual savings of around 1,000 hours. Also tool is so easy to use that you do not need to have any technical knowledge.”_

- [Manvitha K.](https://www.g2.com/products/workato/reviews/workato-review-12106615), Workato review

#### Cons: Where Many Platforms Fall Short

• **Advanced transformations require deeper technical knowledge and configuration**

_“Some advanced use cases require a deeper technical understanding, especially when building custom flows, handling edge cases, or working with complex APIs. The UI can feel overwhelming for new users, and debugging large integrations could be improved with more developer-style tooling. Pricing can also be a consideration for smaller organizations compared to lightweight automation tools.”_

- [Nuri Vladimir E.](https://www.g2.com/products/celigo/reviews/celigo-review-12356472), Celigo review

• **Limited debugging visibility when pipelines fail during complex workloads**

_“Debugging and troubleshooting pipelines can sometimes be difficult. Error messages are not always very detailed, which can slow down the process of identifying issues. The UI is helpful, but complex pipelines can become harder to manage and visualize as they grow. Additionally, monitoring and cost tracking for large workloads requires careful attention, as pipeline executions and data movement activities can accumulate costs quickly.”_

- [Alan R.](https://www.g2.com/products/azure-data-factory/reviews/azure-data-factory-review-12454264), Azure Data Factory

• **Scaling integrations or data volume increases operational management complexity**

_“The pricing model can become expensive for large-scale queries without proper optimization and cost monitoring. The learning curve for advanced features and query optimization techniques requires time investment. Limited support for certain data types and occasional complexity in debugging nested queries could be improved for a better developer experience.”_

- [Alok K.](https://www.g2.com/products/google-cloud-bigquery/reviews/google-cloud-bigquery-review-12237841), Google Cloud BigQuery review

### My Expert Takeaway on ETL Tools in 2026

Looking across the review data, ETL solutions receive consistently strong sentiment, with an average rating of **4.61/5 stars and a 9.22/10 likelihood to recommend**. That tells me most teams see clear value once their pipelines are operational. ETL tools have quietly become core infrastructure for modern data environments, especially as organizations connect more SaaS applications, warehouses, and analytics systems.

What I notice most in the reviews is that teams rarely evaluate ETL platforms only on integrations. Instead, reliability and automation come up repeatedly. Users want pipelines that run consistently without constant monitoring or manual fixes. When pipelines break or debugging becomes difficult, it quickly impacts reporting workflows and downstream analytics.

Another pattern I see is that successful teams treat ETL software as shared infrastructure rather than an isolated engineering tool. Data engineers may design pipelines, but analysts and operations teams often rely on them daily. Platforms that simplify pipeline visibility, monitoring, and maintenance tend to make collaboration easier across teams.

Industry usage patterns also suggest that organizations with growing data environments benefit the most from mature ETL workflows. For buyers evaluating the best ETL tools, the biggest differentiator often comes down to how well a platform keeps pipelines stable and manageable as data complexity grows.

### ETL Tools FAQs

#### What are the best free ETL tools for developers?

Many platforms offer open-source components, limited free tiers, or trial versions that developers use to build and test pipelines.

Common options include:

- [dbt](https://www.g2.com/products/dbt/reviews) **:** An open-source framework used by data teams to transform and model data directly inside data warehouses.
- [Google Cloud BigQuery](https://www.g2.com/products/google-cloud-bigquery/reviews): Offers a limited free usage tier that allows developers to run queries and build data pipelines at small scale.
- [AWS Glue](https://www.g2.com/products/aws-glue/reviews): A serverless data integration service commonly used for large-scale pipelines, typically accessed through free trial credits or limited testing environments.

Developers often use these tools to prototype data pipelines before scaling to production workloads.

#### What are the best no-code or low-code ETL tools?

No-code and low-code ETL tools simplify pipeline creation through visual workflows and prebuilt integrations.

Examples include:

- [Workato](https://www.g2.com/products/workato/reviews): Known for its automation platform and extensive connector ecosystem that simplifies integration workflows.
- [SnapLogic](https://www.g2.com/products/snaplogic-intelligent-integration-platform-iip/reviews): Uses a visual interface and prebuilt connectors to help teams design data pipelines without heavy coding.
- [Alteryx](https://www.g2.com/products/alteryx/reviews): Offers a drag-and-drop workflow builder designed for analysts working with data preparation and transformation.

These platforms allow data teams to manage pipelines without relying heavily on engineering resources.

#### Which ETL services offer strong security features?

Organizations handling sensitive data often prioritize ETL tools that offer strong governance, access controls, and compliance capabilities.

Platforms commonly used in secure environments include:

- [Azure Data Factory](https://www.g2.com/products/azure-data-factory/reviews): Integrates with Microsoft’s identity and security framework for controlled data pipelines.
- [Google Cloud BigQuery](https://www.g2.com/products/google-cloud-bigquery/reviews): Supports secure data processing with built-in encryption and governance capabilities.
- [AWS Glue](https://www.g2.com/products/aws-glue/reviews): Provides role-based access controls and integration with AWS security services.

These platforms help organizations maintain secure data movement across complex environments.

#### What’s the leading ETL app for big data analysis?

For large-scale analytics workloads, organizations often use ETL tools that integrate directly with modern data platforms.

Common choices include:

- [Databricks](https://www.g2.com/products/databricks/reviews): Designed for large-scale data engineering, analytics, and machine learning pipelines.
- [Google Cloud BigQuery](https://www.g2.com/products/google-cloud-bigquery/reviews): Enables large-scale data processing and analytics within a cloud data warehouse environment.
- [Fivetran](https://www.g2.com/products/fivetran/reviews): Automates high-volume data ingestion into cloud warehouses for analytics and reporting.

These platforms support large datasets and complex transformation workflows.

#### What are the different types of ETL tools?

ETL tools generally fall into four categories:

- **Open-source ETL tools** : Flexible frameworks for custom pipeline development.
- **Cloud-based ETL platforms** : Managed services that automate data pipelines.
- **No-code or low-code ETL tools** : Visual workflow tools for non-engineering teams.
- **Enterprise ETL solutions** : Platforms built for governance, monitoring, and large-scale data environments.

Each category supports different technical needs and levels of pipeline complexity.

#### Sources

- [G2 Scoring Methodologies](https://documentation.g2.com/docs/research-scoring-methodologies?_gl=1*5ky9es*_gcl_au*MTY2NDg2MDY3Ny4xNzU1MDQxMDU4*_ga*MTMwMTMzNzE1MS4xNzQ5MjMyMzg1*_ga_MFZ5NDXZ5F*czE3NTUwOTkzMjgkbzQkZzEkdDE3NTUwOTk3NzYkajU3JGwwJGgw)
- [G2 Winter 2026 Reports](https://company.g2.com/news/g2-winter-2026-reports)

Researched By: [Shalaka Joshi](https://research.g2.com/insights/author/shalaka-joshi)

Last updated on March 16, 2026