# Best Data Observability Software - Page 6 *By [Shalaka Joshi](https://research.g2.com/insights/author/shalaka-joshi)* Data observability involves the complete monitoring, managing, and understanding of the modern data tech stack. These tools allow companies to better manage their data by helping them discover and solve real-time data issues and gain complete insight into the system’s data health. Data observability tools help companies accelerate the adoption of data across departments. This helps in making strategic and data-driven decisions that benefit the entire organization. The concept of data observability stems from best practices learned from DevOps software to manage impartial, inaccurate, or erroneous data. These best practices, which include optimizing logs, real-time insights, and so on, enable the creation of error-free and trusted data across the entire data stack, which includes data sources, data warehouses, ETL tools, ML/BI tools, etc. Data observability tools are a part of [DataOps platforms](https://www.g2.com/categories/dataops-platforms). DataOps platforms assemble several types of data management software into an individual, integrated environment. The platform unifies all the development and operations in data workflows. Data observability software focuses on monitoring the health of the data pipelines and the overall system. Data observability tools differ from [monitoring software](https://www.g2.com/categories/monitoring) since the latter focuses on pre-determined metrics to identify bugs, whereas data observability focuses on real-time detection and resolution. Data observability also differs from [data quality software](https://www.g2.com/categories/data-quality), wherein the former focuses on reducing the number of data incidents while accelerating resolution time. Data quality is the result of powerful data observability across the modern data stack. To qualify for inclusion in the Data Observability category, a product must: - Proactively monitor, alert, track, log, compare, and analyze data for any errors or issues across the entire data stack - Monitor data at rest and data in motion, and does not require data extraction from current storage location - Connect to an existing stack without any need to write code or modify data pipelines ## Category Overview **Total Products under this Category:** 60 ## Trust & Credibility Stats **Why You Can Trust G2's Software Rankings:** - 30 Analysts and Data Experts - 2,300+ Authentic Reviews - 60+ 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. ## Best Data Observability Software At A Glance - **Leader:** [Monte Carlo](https://www.g2.com/products/monte-carlo/reviews) - **Highest Performer:** [SquaredUp](https://www.g2.com/products/squaredup-squaredup/reviews) - **Easiest to Use:** [Dash0](https://www.g2.com/products/dash0/reviews) - **Top Trending:** [Sifflet](https://www.g2.com/products/sifflet/reviews) - **Best Free Software:** [Metaplane](https://www.g2.com/products/metaplane/reviews) --- **Sponsored** ### QuerySurge QuerySurge is an enterprise-grade data quality platform that leverages AI to continuously automate data validation across your entire ecosystem ‐ from data warehouses and big data lakes to BI reports and enterprise applications. With AI-powered test creation, scalable architecture, and the leading DevOps for Data CI/CD integration, QuerySurge ensures data integrity at every stage of the pipeline. Automated Data Validation Use Cases: QuerySurge provides a smart, AI-driven, data validation & ETL testing solution for your automated testing needs. - Data Warehouse / ETL Testing - DevOps for Data / Continuous Testing - Data Migration Testing - Business Intelligence (BI) Report Testing - Big Data Testing - Enterprise Application Data Testing What QuerySurge Provides: - Automation of your manual data validation and testing process - Ease-of-use, low-code/no-code features - Generative AI capabilities for test creation - Testing across 200+ data platforms - Integration into your CI/CD DataOps pipeline - Acceleration of your data analysis - Ensurance of regulatory compliance Key Features: - Data Connection Wizard provides an easy way to link to your data stores - Visual Query Wizard builds table-to-table and column-to-column tests without writing SQL - Generative AI module automatically creates transformation tests in bulk - DevOps for Data provides a RESTful API with 110+ calls and Swagger documentation and integrates into CI/CD pipelines - Create Custom Tests and modularize functions with snippets, set thresholds, stage data, check data types & duplicate rows, full text search, and asset tagging - Schedule tests to run immediately, at a predetermined date & time, or after any event from a build/release, CI/CD, DevOps, or test management solution - Multi-project support in a single instance, new Global Admin user, assign users and agents, import and export projects, and user activity log reports - Webhooks provide real-time integrations with DevOps, CI/CD, test management, and alerting tools - Ready-for-Analytics provides seamless integration with QuerySurge and your BI tool or open-source Metabase to create custom reports and dashboards and gain deeper, real-time insights into your data validation and ETL testing workflows - Data Analytics Dashboards and Data Intelligence Reports track, analyze, and communicate data quality [Book a Demo](https://www.g2.com/external_clickthroughs/record?secure%5Bad_program%5D=ppc&secure%5Bad_slot%5D=category_product_list&secure%5Bcategory_id%5D=1003968&secure%5Bdisplayable_resource_id%5D=108&secure%5Bdisplayable_resource_type%5D=Category&secure%5Bmedium%5D=sponsored&secure%5Bplacement_reason%5D=neighbor_category&secure%5Bplacement_resource_ids%5D%5B%5D=74&secure%5Bplacement_resource_ids%5D%5B%5D=2686&secure%5Bprioritized%5D=false&secure%5Bproduct_id%5D=54942&secure%5Bresource_id%5D=1003968&secure%5Bresource_type%5D=Category&secure%5Bsource_type%5D=category_page&secure%5Bsource_url%5D=https%3A%2F%2Fwww.g2.com%2Fcategories%2Fdata-observability%3Fpage%3D11&secure%5Btoken%5D=edbd1d738ac016b1eb9a7f7dd2f0ac04143e9fc8fc80c20ed3231372b1ca34cb&secure%5Burl%5D=https%3A%2F%2Fwww.querysurge.com%2Fget-started%2Fprivate-demo%3Futm_source%3DG2%26utm_medium%3Dcpc%26utm_campaign%3DG2-reviews&secure%5Burl_type%5D=book_demo) --- ## Parent Category [IT Management Software](https://www.g2.com/categories/it-management) ## Related Categories - [Data Quality Tools](https://www.g2.com/categories/data-quality) - [Database Monitoring Tools](https://www.g2.com/categories/database-monitoring) - [DataOps Platforms](https://www.g2.com/categories/dataops-platforms) --- ## Buyer Guide ### What You Should Know About Data Observability Software ### Data Observability Software FAQs ### What’s the most recommended customer success platform for SaaS companies? For software teams prioritizing data accuracy, operational visibility, and rapid issue resolution, top data observability platforms on G2 include: - [Monte Carlo](https://www.g2.com/products/monte-carlo/reviews) focuses exclusively on data observability, providing automated monitoring, anomaly detection, and data lineage to help teams catch and resolve data issues before they impact users. - [Metaplane](https://www.g2.com/products/metaplane/reviews) delivers end-to-end data observability with features like schema change detection, freshness monitoring, and anomaly detection, enabling teams to maintain data quality effectively. - [Acceldata](https://www.g2.com/products/acceldata/reviews) combines data quality monitoring, pipeline performance, and infrastructure health insights in one platform, helping software companies ensure their data operations run smoothly at scale. ### What’s the best data observability software for small businesses? For small businesses aiming to maintain data quality, monitor pipelines, and catch issues early without complex setup, [leading small business data observability solutions](https://www.g2.com/categories/data-observability/small-business) include: - [Bigeye](https://www.g2.com/products/bigeye/reviews) combines automated anomaly detection and root cause analysis in a platform that makes data reliability accessible without requiring deep technical resources, which is great for scaling teams. - [IBM Databand](https://www.g2.com/products/ibm-databand/reviews) delivers proactive monitoring and automated alerts while integrating easily with existing data pipelines, making it approachable for growing businesses with limited engineering support. - [Monte Carlo](https://www.g2.com/products/monte-carlo/reviews) offers a powerful but flexible solution with automated monitoring, data lineage, and incident resolution features. Although enterprise-ready, it also provides packages suitable for fast-growing small companies.