1
Coralogix
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
Top 10 Data Observability Software Companies (November 2026)
As of November 2026, Latka tracks 57 data observability software companies. They have combined revenues of $443M and employ 3.1K people. They have raised $524.6M and serve 5.4K customers combined.
Every company below sells data observability software to other businesses and is ranked by its most recent annual revenue. Revenue, funding, headcount and customer figures come from CEO interviews on the Latka podcast, public company filings, and Latka estimates where a company has not disclosed a number.
What Data Observability Software Companies do
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.
- Companies
- 57
- Revenue
- $443M
- Funding
- $524.6M
- Employees
- 3.1K
Filters
Sorting: Highest -> Lowest
Top Data Observability Software Companies by revenue
Showing 10 of 57 companies ranked by annual revenue.
2
Observe
United States
Observe provides performance management tools based on a versatile observability platform.
- Revenue
- $55M
- Year founded
- 2017
- Funding
- $35M
- Team size
- 227
- Revenue
- $48M
- Customers
- 1.2K
- Year founded
- 2014
- Funding
- $121.6M
- Team size
- 200
4
ITRS
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.
- Revenue
- $41.3M
- Year founded
- 1997
- Team size
- 375
- Revenue
- $33.8M
- Year founded
- 2015
- Team size
- 96
6
Kollective Technology
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.
- Revenue
- $11.1M
- Year founded
- 2001
- Funding
- $43M
- Team size
- 101
7
Honeycomb
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.
- Revenue
- $10.8M
- Year founded
- 2016
- Funding
- $46.9M
- Team size
- 238
- Revenue
- $10.6M
- Year founded
- 2014
- Funding
- $422.5K
- Team size
- 53
9
Lightrun
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.
- Revenue
- $9.8M
- Year founded
- 2019
- Team size
- 89
10
Edge Delta
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.
- Revenue
- $8.3M
- Year founded
- 2018
- Team size
- 75
Frequently asked questions about Data Observability Software Companies
How many data observability software companies are there?
Latka tracks 57 data observability software companies with reported revenue. Together they generate $443M in annual revenue and employ 3.1K people.
Which data observability software company is the largest?
Coralogix is the largest, with $90.8M in annual revenue, founded in 2014.
How much revenue does a typical data observability software company make?
The average data observability software company in this list makes $7.8M a year, across 57 companies with reported revenue. They serve 5.4K customers combined.
Who are the leading Data Observability software vendors?
Ranked by annual revenue, the leaders are Coralogix, Observe, Logz.io, ITRS and Mezmo.
How much funding have data observability software companies raised?
The 57 data observability software companies tracked here have raised $524.6M in disclosed funding between them.
Related IT Management Software categories
Inclusion Criteria
- 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