
San Francisco, California, United States
cloud-based machine learning-powered log analytics and monitoring solutions
- Revenue
- $90.8M
- Customers
- 2K
- Year founded
- 2014
- Funding
- $236.5M
- Team size
- 572
- Growth
- 44.35%
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 61 companies ranked by annual revenue.

San Francisco, California, United States
cloud-based machine learning-powered log analytics and monitoring solutions

Toronto, Ontario, Canada
BlueCat provides core services and solutions that help our customers and their teams deliver change-ready networks. With BlueCat, organizations can build reliable, secure, and agile mission-critical networks that can support transformation initiatives such as cloud adoption and automation. BlueCat’s growing portfolio includes services and solutions for automated and unified DDI management, network security, multicloud management, and network observability and health. BlueCat’s DDI management platform was recognized as a market leader and outperformer in GigaOm’s 2022 and 2023 Radar reports. The company is headquartered in Toronto and New York and has additional offices in Germany, Iceland, Japan, Singapore, Serbia, and the United Kingdom.

United States
Observe provides performance management tools based on a versatile observability platform.

London, London, United Kingdom
Real-time observability platform for financial services and regulated industries. AI-powered automation that prevents IT outages before they happen. ITRS is recognized in the 2025 Gartner® Magic Quadrant™ for Observability Platforms.

Bend, Oregon, United States
Kollective helps businesses unlock the full potential of over 35 enterprise video platforms with our integrated Video Experience and Assurance Platform. Our advanced video observability and optimization tools enable IT teams to highlight and resolve performance challenges, ensuring flawless video experiences. Communication leaders gain powerful insights from content trend analysis, helping them make data-driven decisions to improve message effectiveness. Built around our proven Observe, Analyze, Optimize framework, our platform ensures proactive issue resolution, full network visibility, and the ability to cut through excessive data, enabling businesses to consistently deliver high-quality, uninterrupted video experiences that boost engagement and productivity.

San Francisco, California, United States
Provider of software that offers full-stack observability designed to solve the hard problems that arise from operating a modern software stack with event-driven debugging. The company's software is designed for high cardinality data and collaborative problem solving, enabling engineers to deeply understand and debug production software together as well as instrument and query the behavior of their system.

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.
- 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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