Best DataOps Platforms

How Many DataOps Platforms Products Does G2 Track?

Total Products under this Category: 125

Category Stats (Oct 2026)

  • Average Rating: 4.59/5 The average rating of products in this category, based on all submitted ratings
  • Top Trending Product: ANOW! Suite (+1.11%) - Among all products in this category, ANOW! Suite recorded the largest rating increase compared to last month

Last updated: October 01, 2026

How Does G2 Rank DataOps Platforms Products?

Why You Can Trust G2's Software Rankings:

  • 30 Analysts and Data Experts
  • 6,600+ Authentic Reviews
  • 125+ Products
  • Unbiased Rankings

G2's software rankings are built on verified user reviews, rigorous moderation, and a consistent research methodology maintained by a team of analysts and data experts. Each product is measured using the same transparent criteria, with no paid placement or vendor influence. While reviews reflect real user experiences, which can be subjective, they offer valuable insight into how software performs in the hands of professionals. Together, these inputs power the G2 Score, a standardized way to compare tools within every category.

G2 Grid® for DataOps Platforms

G2 Grid® for DataOps Platforms plotting products by satisfaction and market presence

Highlighted products: Databricks, Fivetran, ServiceNow Workflow Data Fabric, Flip, dbt, 5X, Monte Carlo, and Informatica Data Integration and Engineering.

Underlying data: [Grid® JSON](https://www.g2.com/categories/dataops-platforms/grids.json?focus%5B%5D=databricks&focus%5B%5D=fivetran&focus%5B%5D=servicenow-workflow-data-fabric&focus%5B%5D=kanerika-flip&focus%5B%5D=dbt&focus%5B%5D=5x&focus%5B%5D=monte-carlo&focus%5B%5D=informatica-data-integration-and-engineering)

Databricks

Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform 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 platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. Founded in 2013 by the original creators of Apache Spark™, Delta Lake, MLflow and Unity Catalog, Databricks is built on an open lakehouse architecture that brings data, analytics and AI together. The platform is used by data engineers, data scientists, analysts, developers, machine learning teams, AI teams and business users to collaborate across the full data and AI lifecycle. Key Databricks capabilities include: - Data engineering: Build, automate and manage reliable batch, streaming and real-time data pipelines. - Analytics and business intelligence: Run SQL analytics, create dashboards and enable business teams to explore data. - Data governance: Discover, secure and manage data and AI assets across teams, clouds and workloads. - Machine learning and AI: Develop models, build generative AI applications and create production-grade AI agents. - Data applications: Build and deploy data-driven applications using governed enterprise data. Available across AWS, Azure and Google Cloud, Databricks helps organizations work across clouds, reduce data silos and simplify collaboration across teams and tools. Customers use Databricks for use cases such as customer personalization, fraud detection, predictive maintenance, real-time analytics, cybersecurity, healthcare research, financial risk management, supply chain optimization and AI-powered decision-making. Databricks is used across industries including financial services, healthcare and life sciences, retail, manufacturing, energy and the public sector. Organizations use the platform to modernize data infrastructure, accelerate AI adoption and turn enterprise data into business value.

Average Rating: 4.6/5.0

Total Reviews: 1,345

How Do G2 Users Rate Databricks?

  • Data Observability: 8.7/10 (Category avg: 8.9/10)
  • Testing capabilities: 8.7/10 (Category avg: 8.7/10)
  • Ease of Use: 8.8/10 (Category avg: 9.0/10)
  • What is your organization's estimated ROI on the product (payback period in months)?: 10/10 (Category avg: 10/10)

Who Is the Company Behind Databricks?

  • Seller: Databricks Inc.
  • Company Website:
  • Year Founded: 2013
  • HQ Location: San Francisco, CA
  • Twitter: @databricks
    92,269 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    14,336 employees on LinkedIn®

Who Uses This Product?

  • Who Uses This: Data Engineer, Data Analyst
  • Top Industries: Information Technology and Services, Financial Services
  • Company Size: 47% Large, 38% Medium

What Do G2 Reviewers Say About Databricks?

AI-generated summary from verified user reviews

Pros
  • Users enjoy the ease of use and extensive features of Databricks, streamlining data warehousing and machine learning tasks.
  • Users appreciate the ease of use of Databricks, enhancing their experience with its intuitive interface and efficient features.
  • Users value the seamless integrations with AWS services that enhance efficiency and support diverse business needs.
  • Users value the seamless collaboration provided by Databricks, enhancing teamwork on data projects and insights sharing.
  • Users value the wide array of integrated analytical features in Databricks, enhancing efficiency and collaboration in data projects.
Cons
  • Users face a steep learning curve with Databricks, as its complexity can be confusing for newcomers.
  • Users note that the cost of Databricks can be quite high, particularly for large data projects and limited free options.
  • Users find the steep learning curve of Databricks challenging, particularly for those unfamiliar with big data tools.
  • Users find the complexity of Databricks challenging, especially during initial setup and navigation of advanced features.
  • Users encounter complex setup challenges with Databricks initially, but support helps resolve issues quickly.

What Are Recent G2 Reviews of Databricks?

What Are G2 Users Discussing About Databricks?

Fivetran

Fivetran is the data foundation for AI. One platform moves, manages, and transforms data from every application, database, event stream, and file your business runs on into a governed foundation that analytics, operations, and AI can act on. Connectors deploy in minutes, run themselves, and adjust automatically when a source changes, so your data team spends its time building, not maintaining pipelines.

Average Rating: 4.3/5.0

Total Reviews: 825

How Do G2 Users Rate Fivetran?

  • Data Observability: 8.4/10 (Category avg: 8.9/10)
  • Testing capabilities: 8.7/10 (Category avg: 8.7/10)
  • Ease of Use: 9.0/10 (Category avg: 9.0/10)
  • What is your organization's estimated ROI on the product (payback period in months)?: 10/10 (Category avg: 10/10)

Who Is the Company Behind Fivetran?

  • Seller: Fivetran
  • Company Website:
  • Year Founded: 2012
  • HQ Location: Oakland, CA
  • Twitter: @fivetran
    5,767 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    1,902 employees on LinkedIn®

Who Uses This Product?

  • Who Uses This: Data Engineer, Data Analyst
  • Top Industries: Computer Software, Information Technology and Services
  • Company Size: 59% Medium, 27% Small

What Do G2 Reviewers Say About Fivetran?

AI-generated summary from verified user reviews

Pros
  • Users appreciate the ease of integration and maintenance with Fivetran, enhancing their ROI and workflow efficiency.
  • Users value the easy setup of Fivetran, appreciating its seamless integration with existing applications.
  • Users value the easy integration of Fivetran, seamlessly connecting with existing applications and enhancing data access.
  • Users value the responsive customer support from Fivetran, enhancing their overall experience and satisfaction.
  • Users appreciate the intuitive and simple layout of Fivetran, making data management efficient and accessible.
Cons
  • Users report experiencing sync issues that disrupt functionality, causing unpredictable failures and complications in workflow management.
  • Users find Fivetran's pricing to be quite expensive, which limits accessibility and flexibility for wider usage.
  • Users face integration issues with Fivetran, particularly regarding schema ownership and modifying connections amidst platform changes.
  • Users find the learning curve steep, requiring technical knowledge to navigate Fivetran effectively at first.
  • Users find Fivetran's pricing issues hinder accessibility and flexibility, making it less feasible for broader use.

What Are Recent G2 Reviews of Fivetran?

What Are G2 Users Discussing About Fivetran?

ServiceNow Workflow Data Fabric

Workflow Data Fabric is the AI‑ready data foundation of the ServiceNow AI Platform. It connects to any data—structured, unstructured, and streaming—contextualizes it with business meaning and governance, and controls it with lineage and policies so employees and AI agents can confidently act on real‑time information to prevent disruptions, resolve requests faster, and optimize operations—all on one platform. How Workflow Data Fabric turns data into instant action Connect Unify data from systems like Salesforce, SAP, Workday, data lakes, and event streams in real time without duplication or fragile point‑to‑point integrations. With Zero Copy Connectors, Stream Connect, External Content Connectors, and Integration Hub, Workflow Data Fabric simplifies architecture and cuts integration cost and time. Contextualize Give data business meaning and make it trustworthy with an active Data Catalog, embedded governance, and lineage. Use Knowledge Graph to map relationships (e.g., customers, assets, orders) so AI agents and workflows understand context and make accurate decisions in the flow of work. Control Apply policies, permissions, and compliance guards across connected sources so the right people and AI agents access the right data, at the right time, with full auditability and traceability—no more shadow copies or opaque pipelines.

Average Rating: 4.3/5.0

Total Reviews: 152

How Do G2 Users Rate ServiceNow Workflow Data Fabric?

  • Data Observability: 8.2/10 (Category avg: 8.9/10)
  • Testing capabilities: 8.0/10 (Category avg: 8.7/10)
  • Ease of Use: 8.1/10 (Category avg: 9.0/10)
  • What is your organization's estimated ROI on the product (payback period in months)?: 10/10 (Category avg: 10/10)

Who Is the Company Behind ServiceNow Workflow Data Fabric?

  • Seller: ServiceNow
  • Company Website:
  • Year Founded: 2004
  • HQ Location: Santa Clara, CA
  • Twitter: @servicenow
    55,548 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    35,078 employees on LinkedIn®

Who Uses This Product?

  • Who Uses This: Software Engineer
  • Top Industries: Information Technology and Services, Computer Software
  • Company Size: 45% Large, 29% Medium

What Do G2 Reviewers Say About ServiceNow Workflow Data Fabric?

AI-generated summary from verified user reviews

Pros
  • Users find ServiceNow's ease of use enhances workflow management, allowing seamless integration and automation with minimal effort.
  • Users value the seamless integrations of ServiceNow Workflow Data Fabric, enhancing collaboration and streamlining processes across departments.
  • Users appreciate the low-code automation of ServiceNow Workflow Data Fabric, simplifying integrations and enhancing workflow management.
  • Users value the efficiency improvement from ServiceNow Workflow Data Fabric, enhancing operations and reducing manual effort significantly.
  • Users value the unified data access of ServiceNow Workflow Data Fabric, enhancing efficiency and simplifying decision-making across workflows.
Cons
  • Users find the complex setup of ServiceNow Workflow Data Fabric challenging, requiring significant time and expertise for proper configuration.
  • Users find the difficult setup of ServiceNow Workflow Data Fabric time-consuming and challenging, impacting accessibility and integration.
  • Users find the pricing quite expensive, making it challenging for smaller teams to justify the costs.
  • Users experience slow performance when handling large datasets, impacting efficiency and responsiveness during data operations.
  • Users find the complexity of learning and managing features in ServiceNow Workflow Data Fabric challenging for new users.

What Are Recent G2 Reviews of ServiceNow Workflow Data Fabric?

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Flip

FLIP by Kanerika is an AI-powered, low-code/no-code platform that automates enterprise workflows, streamlines data operations, and accelerates migrations — all without the need for technical expertise. It empowers teams to modernize faster, reduce manual effort, and focus on business outcomes. Key Capabilities: Automated Data Reconciliation Low-Code/No-Code DataOps Migration Accelerators AI Workforce Accounts Payable Automation FLIP helps organizations simplify data management, enhance accuracy, and accelerate digital transformation across industries.

Average Rating: 5.0/5.0

Total Reviews: 13

How Do G2 Users Rate Flip?

  • Data Observability: 9.2/10 (Category avg: 8.9/10)
  • Testing capabilities: 10.0/10 (Category avg: 8.7/10)
  • Ease of Use: 10.0/10 (Category avg: 9.0/10)
  • What is your organization's estimated ROI on the product (payback period in months)?: 3.3/10 (Category avg: 10/10)

Who Is the Company Behind Flip?

  • Seller: Kanerika
  • Year Founded: 2015
  • HQ Location: Austin, Texas, United States
  • LinkedIn® Page: www.linkedin.com
    355 employees on LinkedIn®

Who Uses This Product?

  • Who Uses This: Co-Founder
  • Top Industries: Computer Software
  • Company Size: 92% Small, 23% Medium

What Do G2 Reviewers Say About Flip?

AI-generated summary from verified user reviews

Pros
  • Users value the real-time tracking integration, enhancing customer service and operational efficiency in their logistics processes.
  • Users highlight the ease of use of Flip, enabling quick setup and efficient workflow automation for non-technical members.
  • Users love the fast processing of Flip, drastically reducing time spent on data extraction and enhancing operational efficiency.
  • Users value the data syncing capabilities of FLIP, enhancing efficiency and reliability in operations and customer service.
  • Users love the customization options in Flip, allowing tailored solutions for diverse business needs and workflows.
Cons
  • Users face a complex setup process, often experiencing delays with initial data model configurations and custom connectors.
  • Users note that FLIP is expensive and implementation times can significantly exceed initial estimates, impacting planning.
  • Users experience a steep learning curve with Flip, finding initial navigation and advanced features challenging without adequate training.
  • Users note several missing features in Flip, including the need for enhanced templates and improved reporting visuals.
  • Users experience integration issues with smaller retailers and inconsistent data feeds, impacting overall efficiency and performance.

What Are Recent G2 Reviews of Flip?

dbt

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: 208

How Do G2 Users Rate dbt?

  • Data Observability: 8.7/10 (Category avg: 8.9/10)
  • Testing capabilities: 8.9/10 (Category avg: 8.7/10)
  • Ease of Use: 9.0/10 (Category avg: 9.0/10)
  • What is your organization's estimated ROI on the product (payback period in months)?: 10/10 (Category avg: 10/10)

Who Is the Company Behind dbt?

  • Seller: Fivetran
  • Year Founded: 2012
  • HQ Location: Oakland, CA
  • Twitter: @fivetran
    5,767 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    1,902 employees on LinkedIn®

Who Uses This Product?

  • Who Uses This: Data Engineer, Analytics Engineer
  • Top Industries: Information Technology and Services, Computer Software
  • Company Size: 56% Medium, 27% Small

What Do G2 Reviewers Say About dbt?

AI-generated summary from verified user reviews

Pros
  • Users find dbt's ease of use exceptional, with straightforward setup and intuitive features enhancing their data transformation processes.
  • Users appreciate the maintainability and clarity of dbt's SQL code base, enhancing collaboration and data transformations.
  • Users value the automation of data workflows with dbt, enhancing maintainability and collaboration in SQL transformations.
  • Users love the ease of transforming data with dbt, allowing for organized and efficient analytics workflows.
  • Users value the data quality of dbt, praising its effectiveness in ensuring data integrity and operational efficiency.
Cons
  • Users find that dbt has limited functionality due to rigidness and complex debugging, hindering project progress.
  • Users face dependency issues in dbt, as model errors and upstream changes complicate troubleshooting and disrupt workflows.
  • Users find the steep learning curve of dbt daunting, needing mastery of concepts like Jinja and Git.
  • Users encounter poor error handling with unclear messages, making troubleshooting frustrating and complicating the user experience.
  • Users often face confusing error reporting and unclear messages, making troubleshooting and identifying issues challenging.

What Are Recent G2 Reviews of dbt?

What Are G2 Users Discussing About dbt?

5X

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

How Do G2 Users Rate 5X?

  • Data Observability: 9.1/10 (Category avg: 8.9/10)
  • Testing capabilities: 9.0/10 (Category avg: 8.7/10)
  • Ease of Use: 9.5/10 (Category avg: 9.0/10)
  • What is your organization's estimated ROI on the product (payback period in months)?: 6.1/10 (Category avg: 10/10)

Who Is the Company Behind 5X?

  • Seller: 5X
  • Year Founded: 2020
  • HQ Location: San Francisco
  • Twitter: @DataWith5x
    49 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    104 employees on LinkedIn®

Who Uses This Product?

  • Top Industries: Computer Software, Financial Services
  • Company Size: 56% Medium, 40% Small

What Do G2 Reviewers Say About 5X?

AI-generated summary from verified user reviews

Pros
  • Users appreciate the ease of use of 5X, thanks to its intuitive interface and seamless integration with existing tools.
  • Users appreciate the responsive customer support of 5X, enhancing their overall experience with swift feature updates.
  • Users value the seamless integration capabilities of 5X, enhancing efficiency in managing diverse data sources effortlessly.
  • Users value the easy integrations of 5X, which enhance their data ingestion processes and overall operational efficiency.
  • Users value the seamless integration and intuitive design of 5X, enabling efficient data management and automation.
Cons
  • New users face a steep learning curve, but training helps ease the transition to the platform's features.
  • Users find the setup process complex, leading to delays and challenges in implementing advanced features and workflows.
  • Users find a steep learning curve initially, but become proficient with training and support over time.
  • Users find the difficult setup of 5X challenging due to complexity and a steep learning curve.
  • Users note the feature limitations of 5X, as some advanced options are still in development and may require patience.

What Are Recent G2 Reviews of 5X?

Monte Carlo

Monte Carlo is the agent trust platform, trusted by Nasdaq, Cisco, PepsiCo, and hundreds of enterprise organizations worldwide. Founded in 2019 and backed by leading investors, Monte Carlo pioneered data observability and has expanded into the full AI reliability stack. We're consistently ranked #1 in data observability on G2 — and we're built for what comes next. As enterprises scale from dozens to thousands of AI agents across mission-critical use cases, Monte Carlo monitors, troubleshoots, and improves both those agents and the underlying data powering them. Our platform covers the full trust stack — from the data pipelines feeding agents, to the context they retrieve, the decisions they make, and the outputs they produce — across four trust dimensions: context quality, performance, behavior, and outputs. Only Monte Carlo closes the full trust loop across both data and AI, and we meet enterprises wherever they are on the spectrum from human-guided oversight to fully autonomous operations. With 100+ integrations across Snowflake, Databricks, and the rest of your stack, you get full coverage without ripping anything out. Traditional monitoring tools stop at the pipeline or cover only one dimension of reliability — leaving teams to manually investigate, diagnose, and fix failures across disconnected tools. Monte Carlo closes that gap. Teams using Monte Carlo dramatically reduce time to detect and resolve data and AI incidents, scale monitoring coverage without scaling headcount, and build the internal trust that turns AI investments into real business outcomes. If your organization is serious enough about AI to put it in front of customers, executives, and critical decisions — Monte Carlo is the foundation it needs.

Average Rating: 4.3/5.0

Total Reviews: 546

How Do G2 Users Rate Monte Carlo?

  • Data Observability: 9.2/10 (Category avg: 8.9/10)
  • Testing capabilities: 7.7/10 (Category avg: 8.7/10)
  • Ease of Use: 8.3/10 (Category avg: 9.0/10)
  • What is your organization's estimated ROI on the product (payback period in months)?: 10/10 (Category avg: 10/10)

Who Is the Company Behind Monte Carlo?

  • Seller: Monte Carlo
  • Company Website:
  • Year Founded: 2019
  • HQ Location: San Francisco, US
  • Twitter: @montecarlo_ai
    1,576 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    550 employees on LinkedIn®

Who Uses This Product?

  • Who Uses This: Data Engineer, Senior Data Engineer
  • Top Industries: Financial Services, Computer Software
  • Company Size: 50% Large, 41% Medium

What Do G2 Reviewers Say About Monte Carlo?

AI-generated summary from verified user reviews

Pros
  • Users value the intuitive interface of Monte Carlo, finding it easy to navigate and utilize effectively.
  • Users appreciate the custom alerts and integration with Teams, enhancing data monitoring and stakeholder communication efficiently.
  • Users value the effective monitoring of Monte Carlo, catching data issues early and enhancing stakeholder communication.
  • Users value the custom alerting features in Monte Carlo for efficiently monitoring and notifying stakeholders about data issues.
  • Users value the ease of setting up alerts and anomaly detection in Monte Carlo for monitoring data quality.
Cons
  • Users find the lack of manual threshold settings for alerts limiting, impacting customization for their specific needs.
  • Users experience alert overload due to noisy initial settings, prompting the need for sensitivity adjustments and muted alerts.
  • Users find the inefficient alert system problematic, with issues in notification messages and usability improvements needed.
  • Users find the UX improvement necessary due to slow performance and disorganized features leading to confusion.
  • Users find limited functionality in Monte Carlo, especially regarding custom metrics and alert threshold settings.

What Are Recent G2 Reviews of Monte Carlo?

What Are G2 Users Discussing About Monte Carlo?

Informatica Data Integration and Engineering

Cloud Data Integration (CDI) is a comprehensive, AI-powered ETL and ELT solution designed to easily move, transform, and synchronize data between various sources and target systems across any cloud, anywhere, at scale. Built on a modern technology stack, CDI offers easy, efficient and cost-effective data ingestion, transformation, synchronization, and replication for a multi-cloud and serverless world for everyone and everywhere. It covers diverse integration patterns, ensuring you have well-architected and seamlessly automated data pipelines for all your advanced analytics and AI needs.

Average Rating: 4.3/5.0

Total Reviews: 309

How Do G2 Users Rate Informatica Data Integration and Engineering?

  • Data Observability: 5.0/10 (Category avg: 8.9/10)
  • Ease of Use: 8.4/10 (Category avg: 9.0/10)
  • What is your organization's estimated ROI on the product (payback period in months)?: 10/10 (Category avg: 10/10)

Who Is the Company Behind Informatica Data Integration and Engineering?

  • Seller: Informatica
  • Company Website:
  • Year Founded: 1993
  • HQ Location: Redwood City, CA
  • Twitter: @Informatica
    99,643 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    2,473 employees on LinkedIn®

Who Uses This Product?

  • Who Uses This: Data Engineer, Data Analyst
  • Top Industries: Information Technology and Services, Computer Software
  • Company Size: 57% Large, 28% Medium

What Do G2 Reviewers Say About Informatica Data Integration and Engineering?

AI-generated summary from verified user reviews

Pros
  • Users find Informatica Data Integration's ease of use remarkable, favoring its intuitive interface and drag-and-drop functionality.
  • Users value the efficiency of Informatica Data Integration, enabling reliable and scalable ETL processes seamlessly.
  • Users value the ease of use and extensive connectivity of Informatica Cloud Data Integration for efficient ETL processes.
  • Users value the time-saving capabilities of Informatica Data Integration, benefiting from efficient cloud access and automation.
  • Users appreciate the automation features of Informatica Data Integration, enhancing efficiency in data workflows and scheduling.
Cons
  • Users find the complexity of setup and configuration challenging, particularly for beginners navigating the platform.
  • Users find the complex usability of Informatica Data Integration challenging, especially during setup and performance optimization.
  • Users find that debugging can be difficult, as it often requires significant effort and expertise to manage effectively.
  • Users find the difficult setup process challenging, especially for newcomers to the Informatica platform.
  • Users find the error messages frustrating and lacking documentation, complicating their experience with the tool.

What Are Recent G2 Reviews of Informatica Data Integration and Engineering?

What Are G2 Users Discussing About Informatica Data Integration and Engineering?

Astro by Astronomer

For data teams looking to increase the availability of trusted data, Astronomer provides Astro, the modern data orchestration platform, powered by Airflow. Astro enables data engineers, data scientists, and data analysts to build, run, and observe pipelines-as-code. Astronomer is the driving force behind Apache Airflow™, the de facto standard for expressing data flows as code. Airflow is downloaded more than 31 million times each month and is used by hundreds of thousands of teams around the world.

Average Rating: 4.5/5.0

Total Reviews: 135

How Do G2 Users Rate Astro by Astronomer?

  • Data Observability: 8.2/10 (Category avg: 8.9/10)
  • Testing capabilities: 8.0/10 (Category avg: 8.7/10)
  • Ease of Use: 9.0/10 (Category avg: 9.0/10)
  • What is your organization's estimated ROI on the product (payback period in months)?: 10/10 (Category avg: 10/10)

Who Is the Company Behind Astro by Astronomer?

  • Seller: Astronomer
  • Company Website:
  • Year Founded: 2018
  • HQ Location: New York, US
  • Twitter: @astronomerio
    19,697 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    4,513 employees on LinkedIn®

Who Uses This Product?

  • Who Uses This: Data Engineer, Senior Data Engineer
  • Top Industries: Information Technology and Services, Financial Services
  • Company Size: 47% Medium, 38% Large

What Do G2 Reviewers Say About Astro by Astronomer?

AI-generated summary from verified user reviews

Pros
  • Users appreciate the ease of use of Astro, finding it intuitive and effective for managing complex workflows.
  • Users appreciate the efficiency improvements of Astro, simplifying workflows and reducing the need for dedicated DevOps resources.
  • Users appreciate the intuitive user interface of Astro, facilitating easy monitoring and management of complex workflows.
  • Users appreciate the automation capabilities of Astro by Astronomer, streamlining workflows and enhancing data orchestration.
  • Users value the deployment ease of Astro by Astronomer, enhancing productivity with simple, reliable, and efficient setups.
Cons
  • Users highlight that Astro by Astronomer can be quite expensive, posing challenges for smaller teams and budget constraints.
  • Users note a steep learning curve with Astro, requiring significant time for adaptation and training.
  • Users find the steep learning curve of Astro challenging, requiring extra time for new team members to adapt.
  • Users note a steep learning curve with Astro, making adaptation challenging for new team members.
  • Users note the feature limitations of Astro, citing high costs and lack of flexibility compared to self-hosting.

What Are Recent G2 Reviews of Astro by Astronomer?

What Are G2 Users Discussing About Astro by Astronomer?

Orchestra

Orchestra is a lightweight orchestration and observability platform which gives real-time complete visibility for your entire data stack. We automate your orchestration, monitoring, and metadata collection to allow Data Teams spend less time fixing broken things and more time on what matters: building. Orchestra decouples orchestration from the rest of your stack which allows you to get all the power of a fully-featured workflow orchestrator without any of the pain. Build DAGs, connect up your stack, make a ☕ sit-back and relax The platform removes boilerplate orchestration logic and adds powerful metadata so data teams deliver robust, scalable data products backed by enterprise orchestration and observability. Find our more at: https://www.getorchestra.io/

Average Rating: 4.9/5.0

Total Reviews: 20

How Do G2 Users Rate Orchestra?

  • Data Observability: 10.0/10 (Category avg: 8.9/10)
  • Testing capabilities: 10.0/10 (Category avg: 8.7/10)
  • Ease of Use: 9.9/10 (Category avg: 9.0/10)
  • What is your organization's estimated ROI on the product (payback period in months)?: 1.3/10 (Category avg: 10/10)

Who Is the Company Behind Orchestra?

Who Uses This Product?

  • Company Size: 50% Medium, 30% Small

What Do G2 Reviewers Say About Orchestra?

AI-generated summary from verified user reviews

Pros
  • Users value the automation provided by Orchestra, enhancing efficiency in organizing and deploying data pipelines.
  • Users appreciate the simplicity of data pipelining in Orchestra, making automation and scheduling effortless for their teams.
  • Users find that Orchestra provides exceptional ease of use, streamlining data pipeline management and enhancing productivity.
  • Users find the easy setup of Orchestra a game-changer, streamlining their data pipeline processes efficiently.
  • Users value the efficiency of Orchestra, streamlining scheduling and data pipelines, allowing teams to focus on their core tasks.

What Are Recent G2 Reviews of Orchestra?

Peliqan

Peliqan.io is an all-in-one AI-first data integration and automation platform designed for business teams, scale-ups and consultants. Unlike traditional data tools that demand heavy engineering effort, Peliqan enables both business users and technical teams to connect, manage, and activate their data in one collaborative environment - without requiring a dedicated data engineer. With 300+ built-in connectors, Peliqan connects to databases, SaaS business applications (ERP, CRM, Accounting, HRM/ATS etc.), cloud storage, files and APIs as well as on-prem data sources. New connectors are available on demand within 5 business days. Peliqan offers one-click ELT pipelines to the built-in data warehouse, or you can bring your own data warehouse. Peliqan supports all major data warehouses. Thanks to Peliqan’s Excel add-in, business users and consultants can work with real-time data in Excel. Analysts and power users can use Peliqan’s advanced SQL editor with the support of an AI assistant to transform data and prepare business-ready data sets, which can be used in any BI tool such as Microsoft Power BI, Metabase, Tableau, Qlik, Looker etc. Users can also set up Reverse ETL flows. Developers can go even further with Peliqan’s low-code environment, with a built-in virtual AI Data Engineer, where they can: - Build & Publish interactive data apps - Automate writebacks into source systems - Publish API endpoints for data sharing - Implement custom pipelines - Build out internal AI Agents By empowering business users, analysts, consultants and developers, Peliqan dramatically reduces reliance on IT support and speeds up decision-making. Peliqan is not just an ELT data pipeline tool, it’s a complete solution for data orchestration, automation, and activation. Peliqan also acts as the data foundation for Agentic AI, ensuring that AI agents work with trusted, up-to-date 360° views of customers, products, orders, and more - at the speed of a cloud data warehouse. Peliqan’s data warehouse provides an AI-ready data layer out-of-the-box including: - Automatic vectorizing of structured and non-structured data for RAG (Retrieval-Augmented Generation) - Text-to-SQL - MCP Gateway In today’s landscape, a data warehouse is no longer just for BI - it’s the foundation for both BI and AI. With Peliqan.io, organizations can integrate, analyze, and activate their data seamlessly, empowering both humans and AI agents to make smarter, faster decisions.

Average Rating: 4.8/5.0

Total Reviews: 86

How Do G2 Users Rate Peliqan?

  • Data Observability: 9.2/10 (Category avg: 8.9/10)
  • Testing capabilities: 9.6/10 (Category avg: 8.7/10)
  • Ease of Use: 9.4/10 (Category avg: 9.0/10)
  • What is your organization's estimated ROI on the product (payback period in months)?: 4.9/10 (Category avg: 10/10)

Who Is the Company Behind Peliqan?

  • Seller: Peliqan
  • Company Website:
  • Year Founded: 2022
  • HQ Location: Gent
  • Twitter: @Peliqan_io
    9 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    32 employees on LinkedIn®

Who Uses This Product?

  • Top Industries: Computer Software, Information Technology and Services
  • Company Size: 48% Small, 41% Medium

What Do G2 Reviewers Say About Peliqan?

AI-generated summary from verified user reviews

Pros
  • Users value the ease of use of Peliqan, enjoying seamless integration and effortless data management processes.
  • Users value the effortless integrations of Peliqan, enhancing data accessibility and automation in their workflows.
  • Users value the easy integrations of Peliqan, which streamline workflows and enhance operational efficiency across various platforms.
  • Users value the extensive pre-built connectors of Peliqan, enabling efficient data integration and faster client onboarding.
  • Users value the real-time data access and smooth integration capabilities of Peliqan for effective data management.
Cons
  • Users find the learning difficulty of Peliqan challenging, requiring technical expertise for setup and usage.
  • Users find Peliqan requires significant technical skills for setup and data transformation, limiting accessibility for non-tech users.
  • Users highlight feature limitations of Peliqan, requiring external tools for complete BI functionality and custom report creation.
  • Users find that Peliqan's steep learning curve requires expertise for optimal use and initial setup can be time-consuming.
  • Users find a steep learning curve for non-tech individuals due to required Python, SQL, and machine learning knowledge.

What Are Recent G2 Reviews of Peliqan?

Hightouch

Hightouch is the leading data and Agentic Marketing Platform for modern marketing teams. Trusted by brands like Domino’s, Autotrader, cars.com, Superhuman (formerly Grammarly), and PetSmart, Hightouch helps marketers deliver personalized experiences, optimize performance, and move faster with data and AI. With Hightouch, business users can drive revenue, grow brand awareness, and maximize ROI without relying on engineering. Hightouch’s Composable Customer Data Platform (CDP), named a Leader in the 2026 Gartner® Magic Quadrant™ for Customer Data Platforms, collects behavioral data, resolves identities into unified Customer 360 profiles, builds audiences, syncs to 300+ destinations (including leading ad platforms), and measures campaign impact—directly from your cloud data warehouse. On top of this foundation, Hightouch’s Agentic Marketing Platform uses your complete data and all of the context from your marketing and advertising tools to power true end-to-end lifecycle and performance marketing across paid and owned channels. Purpose-built agents help you go from analyzing campaign performance, to ideating new campaigns, to generating creative, to building segments and cross-channel journeys, to activating audiences and optimization signals back into your ad platforms and downstream tools—often in minutes instead of weeks. Hightouch is built for security, compliance, and scale. Your data stays in your environment—Hightouch never becomes a system of record—and the platform meets SOC 2 Type II, HIPAA, ISO-27001, GDPR, CCPA, and Privacy Shield standards, so even the most regulated organizations can confidently use customer data to power marketing. This approach gives global teams a single, trusted foundation for activation while preserving strong governance, clear audit trails, and regional data residency requirements.

Average Rating: 4.6/5.0

Total Reviews: 415

How Do G2 Users Rate Hightouch?

  • Data Observability: 8.4/10 (Category avg: 8.9/10)
  • Testing capabilities: 8.1/10 (Category avg: 8.7/10)
  • Ease of Use: 9.2/10 (Category avg: 9.0/10)
  • What is your organization's estimated ROI on the product (payback period in months)?: 10/10 (Category avg: 10/10)

Who Is the Company Behind Hightouch?

  • Seller: Hightouch
  • Company Website:
  • Year Founded: 2021
  • HQ Location: San Francisco, US
  • LinkedIn® Page: www.linkedin.com
    636 employees on LinkedIn®

Who Uses This Product?

  • Who Uses This: Data Engineer, Software Engineer
  • Top Industries: Computer Software, Information Technology and Services
  • Company Size: 61% Medium, 26% Small

What Do G2 Reviewers Say About Hightouch?

AI-generated summary from verified user reviews

Pros
  • Users love the ease of use of Hightouch, enabling quick data activation and seamless integration with tools.
  • Users appreciate the easy integration of Hightouch, enabling quick setups and seamless connections to multiple platforms.
  • Users appreciate the fantastic customer support from Hightouch, making setup and troubleshooting seamless and efficient.
  • Users value the easy integrations of Hightouch, enabling smooth setups and intuitive audience segmentation with various platforms.
  • Users value the effortless setup of Hightouch, allowing for quick integration and intuitive daily operations.
Cons
  • Users express concerns about Hightouch being expensive, particularly for organizations with large contact volumes and changing conditions.
  • Users find pricing issues with Hightouch due to sudden changes and lack of transparent communication, impacting affordability.
  • Users face integration issues with Hightouch, particularly related to debugging HTTP request connectors and handling errors.
  • Users are frustrated by the slow performance during larger data pulls, impacting their overall experience with Hightouch.
  • Users often face syncing issues that complicate usability, particularly with error messages and list ordering in Hightouch.

What Are Recent G2 Reviews of Hightouch?

What Are G2 Users Discussing About Hightouch?

Cloudera

Cloudera is the only hybrid data and AI platform company that large organizations trust to bring AI to their data anywhere it lives. Unlike other providers, Cloudera delivers a consistent cloud experience that converges public clouds, on-prem data centers, and the edge, leveraging a proven open-source foundation. As the pioneer in big data, Cloudera empowers businesses to apply AI and assert control over 100% of their data, in all forms, improving security, governance, and real-time and predictive insights. The world’s largest brands across all industries rely on Cloudera to transform decision-making and ultimately boost bottom lines, safeguard against threats, and save lives. Cloudera Anywhere Cloud™: Build and scale applications across any environment. The modular hybrid data and AI platform engineered for the agentic era empowers teams to deploy production-grade data and AI workloads across multi-cloud, on-premises, and sovereign environments while maintaining digital sovereignty. The Cloudera data and AI platform includes: Cloudera AI: Deploy and scale any AI model, anywhere. Cloudera brings compute to governed data where it lives for Private AI anywhere by design. Complete control, security, and governance of mission-critical data, models, agents, and inference ensure faster sovereign AI deployments. Cloudera Data-in-Motion: Make fast decisions from real-time data anywhere. Move data with any structure from any source to any destination seamlessly across hybrid environments, enabling in-the-moment business-critical decisions by processing and analyzing real-time data anywhere, from the edge to AI, as business happens. Cloudera Open Data Lakehouse: Process any data, anywhere, for actionable insights. Make smart decisions with an open data lakehouse powered by Apache Iceberg that delivers trusted, reliable, and unified data to fuel agents, AI applications, and analytics, improving collaboration, breaking silos, and simplifying sharing. Cloudera Unified Data Fabric: Unify security and governance across the entire data estate. Move beyond fragmented data management: Break down silos and connect disparate data sources intelligently and securely to provide a unified view of all organizational data and centralized end-to-end control across complex hybrid data environments.

Average Rating: 4.2/5.0

Total Reviews: 190

How Do G2 Users Rate Cloudera?

  • Data Observability: 7.5/10 (Category avg: 8.9/10)
  • Testing capabilities: 10.0/10 (Category avg: 8.7/10)
  • Ease of Use: 8.3/10 (Category avg: 9.0/10)
  • What is your organization's estimated ROI on the product (payback period in months)?: 10/10 (Category avg: 10/10)

Who Is the Company Behind Cloudera?

  • Seller: Cloudera
  • Company Website:
  • Year Founded: 2008
  • HQ Location: Santa Clara, CA
  • Twitter: @cloudera
    106,442 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    3,505 employees on LinkedIn®

Who Uses This Product?

  • Who Uses This: Data Engineer, Software Engineer
  • Top Industries: Information Technology and Services, Banking
  • Company Size: 39% Large, 35% Small

What Do G2 Reviewers Say About Cloudera?

AI-generated summary from verified user reviews

Pros
  • Users praise the user-friendly interface of Cloudera, highlighting its simplicity in managing big data efficiently.
  • Users value the easy scalability of Cloudera, enabling efficient management of large amounts of data effortlessly.
  • Users value the robust security features of Cloudera, ensuring safe and reliable data management across platforms.
  • Users value the comprehensive suite of tools in Cloudera for effective data management and analytics.
  • Users find Cloudera's scalability and centralized administration invaluable for efficient monitoring and management of data processes.
Cons
  • Users express concerns over the high costs of Cloudera, noting it's expensive for its complexity and maintenance.
  • Users find Cloudera's database to be complex, making it challenging for inexperienced professionals to utilize effectively.
  • Users find Cloudera's setup difficult to learn, particularly challenging for beginners without adequate tutorials or guidance.
  • Users find the poor documentation of Cloudera frustrating, complicating navigation and setup for complex data configurations.
  • Users often face access issues with Cloudera, particularly with unauthorized errors in Airflow tasks and limited documentation.

What Are Recent G2 Reviews of Cloudera?

What Are G2 Users Discussing About Cloudera?

kestra

Kestra is an open-source workflow orchestration and automation platform that enables organizations to define, schedule, and monitor both event-driven and time-based workflows. It brings Infrastructure-as-Code principles to orchestration, allowing teams to manage processes through YAML definitions or an intuitive user interface. Kestra is designed for data engineers, developers, and DevOps teams who need to automate data pipelines, integrate distributed systems, or coordinate multi-step workflows across hybrid or cloud environments. Core Capabilities Declarative orchestration: Workflows are defined in YAML and automatically synchronized with changes made through the UI or API. Event-driven and scheduled triggers: Supports automation initiated by timers or external events such as file arrivals, API calls, or message queues (Kafka, Redis, Pulsar, AMQP, MQTT, NATS, AWS SQS, Google Pub/Sub, Azure Event Hubs). Visual workflow design: Build and modify workflows directly in the browser with syntax validation, auto-completion, and real-time DAG visualization. Scalability and resilience: Distributed architecture provides high availability, fault tolerance, retries, and backfill management for millions of executions. Plugin ecosystem: Hundreds of integrations for databases, APIs, cloud platforms, and languages including Python, Node.js, Go, R, and Shell. Key Benefits Unified orchestration layer: Manage scheduled and event-based workflows in one system instead of maintaining separate schedulers or automation tools. Version control integration: Workflows can be stored in Git repositories, supporting CI/CD pipelines and Terraform for Infrastructure-as-Code management. Multi-environment flexibility: Deploy locally, in containers, or across Kubernetes clusters and major cloud providers (AWS, GCP, Azure). Observability and notifications: Track executions, manage inputs and outputs, and send alerts via Slack, PagerDuty, or email. Extensibility: Users can develop custom plugins to extend functionality and standardize internal operations. Typical Use Cases Data orchestration: Build and schedule ETL pipelines, batch or streaming data processes, and big-data workflows with tools like Spark and BigQuery. AI and ML automation: Coordinate model training, evaluation, and deployment workflows. Infrastructure automation: Replace cron jobs or legacy schedulers with declarative, event-driven execution. Microservice coordination: Connect APIs and services into reliable end-to-end processes. Getting Started Kestra can be launched locally in one command using Docker or deployed in production environments with Docker Compose, Kubernetes, or AWS CloudFormation. Users can create and run their first “Hello World” workflow in minutes via the built-in editor or API. Community and Support Kestra is distributed under the Apache 2.0 License and maintained by an active open-source community.

Average Rating: 4.6/5.0

Total Reviews: 24

How Do G2 Users Rate kestra?

  • Data Observability: 9.8/10 (Category avg: 8.9/10)
  • Testing capabilities: 10.0/10 (Category avg: 8.7/10)
  • Ease of Use: 9.6/10 (Category avg: 9.0/10)
  • What is your organization's estimated ROI on the product (payback period in months)?: 1.7/10 (Category avg: 10/10)

Who Is the Company Behind kestra?

Who Uses This Product?

  • Top Industries: Computer Software
  • Company Size: 83% Small, 8% Medium

What Do G2 Reviewers Say About kestra?

AI-generated summary from verified user reviews

Pros
  • Users appreciate the centralized management of Kestra, enhancing collaboration and streamlining workflow across teams effectively.
  • Users commend the responsive customer support of Kestra, enhancing their ability to develop and implement workflows effectively.
  • Users appreciate the customization options in Kestra, facilitating workflow integration and enhancing team collaboration.
  • Users commend Kestra for its exceptional data security and reliability, significantly enhancing their data automation capabilities.
  • Users commend the excellent documentation of Kestra, which facilitates easy growth and development for teams.
Cons
  • Users find the alert overload in Kestra's UI overwhelming, complicating task management and filtering efforts.
  • Users find the Logging/Task Runs menu overwhelming, making it difficult to filter and navigate effectively.

What Are Recent G2 Reviews of kestra?

Y42

Y42’s Turnkey Data Orchestration Platform with embedded Observability gives data practitioners a unified space to reliably build, monitor, and maintain the flow of data to power their business analytics and AI applications. Y42 provides native integration of best-of-breed open-source data tools, comprehensive data governance, and better collaboration for data teams. With Y42, organizations enjoy increased accessibility to data and can make data-driven decisions reliably and efficiently.

Average Rating: 4.9/5.0

Total Reviews: 21

How Do G2 Users Rate Y42?

  • Data Observability: 9.2/10 (Category avg: 8.9/10)
  • Testing capabilities: 9.6/10 (Category avg: 8.7/10)
  • Ease of Use: 9.4/10 (Category avg: 9.0/10)
  • What is your organization's estimated ROI on the product (payback period in months)?: 10/10 (Category avg: 10/10)

Who Is the Company Behind Y42?

  • Seller: Y42
  • Year Founded: 2020
  • HQ Location: Berlin, DE
  • Twitter: @y42dotcom
    276 Twitter followers
  • LinkedIn® Page: www.linkedin.com
    21 employees on LinkedIn®

Who Uses This Product?

  • Company Size: 52% Small, 38% Medium

What Are Recent G2 Reviews of Y42?

What Are G2 Users Discussing About Y42?

Shalaka Joshi
SJ
Researched and written by Shalaka Joshi
Updated October 3, 2024