As of May 2026, there are 61 SaaS companies in Data Observability Software. They have combined revenues of $495.6M and employ 3.8K people. They have raised $480.7M and serve 5K customers combined.
Data observability software is designed to help organizations monitor, analyze, and understand the state of their data throughout its lifecycle. These tools provide insights into data quality, data lineage, and the overall health of data pipelines, allowing teams to quickly identify and troubleshoot issues. Typical use cases include enhancing data reliability, improving operational efficiency, and ensuring compliance with data governance standards. Common features of data observability software include automated monitoring of data flows, alerts on anomalies, and analytics dashboards that present key metrics. Many tools also enable collaboration among teams, empowering data engineers, data analysts, and decision-makers to effectively manage data operations. Typical buyers include IT professionals, data engineers, and business intelligence analysts, aiming to enhance their data management capabilities and drive data-driven decisions.
Sorting: Highest -> Lowest
Showing 10 of 12 companies ranked by annual revenue.
New York, New York, United States
Dynamically instrument logs, metrics & traces from your IDE to get context and understand the behavior of your live applications at runtime. No code changes, redeployments, or restarts are needed.
Seattle, Washington, United States
Edge Delta's intelligent Telemetry Pipelines are designed to manage exponential volumes of Observability and Security data — at the edge or in the cloud. It's control for the knowns you understand, AI and automation for the unknowns you can’t.
San Francisco, California, United States
Cube helps organizations modernize how they deliver, consume, and automate data and analytics across teams, tools, and AI agents by bringing consistency, context, and trust to the next generation of data experiences. Cube Cloud is a leading universal semantic layer platform, providing a single source of truth for both humans and Cube D3’s agentic analytics. Any data source can be unified, governed, optimized, and integrated with any data application: AI, BI, spreadsheets, and embedded analytics. Cube is installed on 90,000 servers and used by more than 5 million users. Customers include 20% of the Fortune 1000. Based in San Francisco, Cube is backed by Decibel, Bain Capital Ventures, Eniac Ventures, 645 Ventures, Databricks Ventures, and Betaworks. To learn more, visit cube.dev.
Mountain View, California, United States
DNIF HYPERCLOUD is a cloud native machine data analytics platform to help cybersecurity practitioners with platform, tools and anchoring in meeting their threat detection goals, efficiently.
Tel Aviv, Tel Aviv, Israel
Groundcover is an eBPF-driven observability platform that provides teams with tools to visualize metrics, logs, and traces, designed for monitoring cloud-native systems. It enables teams to monitor everything they build and run in the cloud with a focus on cost-effectiveness.
London, England, United Kingdom
Solidatus gives you trust in your data and confidence in your decisions. Get fast insights with dynamic discovery, game-changing visualization and the ability to sustainably govern your complex data landscape. By revealing hidden opportunities, threats and the impact of change, your Solidatus data blueprint will help you make the unknown known, so you can optimize your infrastructure, operate more efficiently and minimize risk. Learn more at www.solidatus.com or contact us at [email protected].
San Francisco, California, United States
Bigeye is the data observability platform for large enterprises. Only Bigeye brings together data observability, end-to-end lineage, and scalability and security to give enterprise data teams unmatched insight into the reliability of data powering their business—no matter if it's on-prem, in the cloud, or a hybrid architecture. Leading data driven enterprises such as USAA, Zoom, Hertz, Cisco and Freedom Mortgage use Bigeye to find and fix data issues, improve data trust and ensure the data powering their business stays reliable by default.
Cupertino, California, United States
Kloudfuse is a unified observability platform that integrates with over 700 diverse infrastructures, cloud services, and applications, focused on enhancing application performance and digital operations.
Mountain View, California, United States
Provider of cloud-based log management and server monitoring platform designed to search terabytes of logs in seconds. The company's platform offers server monitoring, log management, visualization and analysis tools that aggregate all the server logs and metrics into a centralized system in real time and crunches terabytes of logs in less than a second, enabling development operation teams to find and resolve more incidents in less time, all from one screen troubleshooting.
United States
Netdata collects metrics per second & presents them in low-latency dashboards. It's designed to run on all physical & virtual servers, cloud deployments, Kubernetes clusters & IoT devices, to monitor systems, containers & apps. It scales nicely from a single server to thousands of servers, even in complex multi/mixed/hybrid cloud environments. Given enough disk space it can keep your metrics for years. KEY FEATURES: 💥 Collects metrics from 800+ integrations OS metrics, container metrics, VMs, hardware sensors, applications metrics, OpenMetrics exporters, StatsD, and logs 💪 Real-Time, Low-Latency, High-Resolution All metrics are collected per second & are on the dashboard immediately after data collection 😶🌫️ Unsupervised Anomaly Detection Trains multiple Machine-Learning models for each metric collected and detects anomalies based on the past behavior of each metric individually 🔥 Powerful Visualization Clear and precise visualization that allows you to quickly understand any dataset, but also to filter, slice and dice the data directly on the dashboard, without the need to learn any query language 🔔 Out of box Alerts Hundreds of alerts out of the box to detect common issues and pitfalls, revealing issues that can easily go unnoticed. It supports several notification methods to let you know when your attention is needed 📖 systemd Journal Logs Explorer (beta) systemd journal logs explorer, to view, filter & analyze system & apps logs by directly accessing systemd journal files on individual hosts & infrastructure-wide logs centralization servers 😎 Low Maintenance Fully automated: automated dashboards, out-of-the-box alerts, auto-detection & discovery of metrics, zero-touch ML, easy scalability & CI/CD friendly ⭐ Open & Extensible Netdata is a modular platform that can be extended in all possible ways and it also integrates nicely with other monitoring solutions
- The software must provide real-time monitoring of data quality and health - It should include features for data pipeline visualization and lineage tracking - The product must offer automated alerting mechanisms for data anomalies - Analytics and reporting capabilities to uncover insights about data performance are essential - Solutions should cater to data operations teams, including data engineers and analysts - Not just providing data storage solutions; must also facilitate data quality management and observability - The platform should integrate with existing data infrastructure and tools
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