The Coolest DataOps And Data Observability Companies Of The 2025 Big Data 100
Part 6 of CRN’s Big Data 100 takes a look at the vendors solution providers should know in the data operations and data observability space.
Upon Closer Observation
Data teams within businesses and organizations strive to provide internal business users and external customers with analytical insights. But those efforts often fall short because the data and analytic systems and processes that support those initiatives produce low-quality results.
More recently, the wave of artificial intelligence and generative AI applications now being developed and implemented is creating even greater demands for huge volumes of high-quality data.
With so much riding on big data today, problems with data quality and reliability can be as disruptive to business operations as an IT system outage—or worse because the damage may not be discovered until after the fact, such as with a marketing campaign that failed due to faulty data.
Data observability tools are focused on the data itself and an organization’s data operations (DataOps) – the flow of data from its source to the end-consumer of analytical results. They monitor and manage the quality and reliability of data, data pipelines and data infrastructure, and are used to investigate and remediate data-related problems. Such efforts are critical for maintaining high-quality data for internal operations, data engineering projects, and for building and operating data products and services.
As part of the CRN 2025 Big Data 100, we’ve put together the following list of data operations and data observability software companies—from well-established vendors to those in startup mode—that solution providers should be familiar with.
Note: The observability space within the IT industry includes many players who provide observability systems for a range of IT management, application performance management and cybersecurity tasks. This being the Big Data 100 list, we have focused here on the company’s that market software for data observability as part of data governance and data management operations.
This week CRN is running the 2025 Big Data 100 list in a series of slideshows, organized by technology category, spotlighting vendors of business analytics software, database systems, data warehouse and data lake systems, data management and integration software, data observability tools, and big data systems and cloud platforms.
Some vendors have big data product portfolios that span multiple technology categories. They appear in the slideshow for the technology segment in which they are most prominent.
Acceldata
Top Executive: Rohit Choudhary, CEO
The Acceldata Data Observability Cloud platform provides observability capabilities that cover data quality, data pipelines, data infrastructure, data users and data costs. The system works with data across on-premises, cloud, and hybrid environments.
In December the Campbell, Calif.-based company expanded its platform’s functionality with new AI-powered data reconciliation capabilities that the company said automate and scale data integrity for revenue growth, operational efficiency, and proactive compliance.
In February Acceldata launched Agentic Data Management (Agentic DM), “a pioneering, AI-first data management platform,” the company said, that will “revolutionize” how enterprises govern, optimize and operationalize data for AI initiatives. Agentic DM is currently in private beta.
Bigeye
Top Executive: Kyle Kirwan, CEO
Bigeye’s “lineage-enabled” data observability tools help data teams quickly identify, triage and resolve data incidents. Bigeye’s software provides data monitoring and anomaly detection capabilities, and track data lineage to automate root cause and impact analysis.
In March the San Francisco-based company launched bigAI, a suite of AI-powered capabilities that the company said go beyond data problem detection to problem resolution and prevention. The new software pinpoints root causes, provides AI-driven guidance to resolve issues faster, and proactively recommends changes to prevent future failures.
In June 2024 Bigeye launched its Systems Integrator Partner Program with dedicated partner managers, sales leads to customers in need of implementation support, referral incentives, and training and support resources.
Cisco/Splunk
Top Executive: Chuck Robbins, CEO
Data observability was one of the key applications for Splunk’s big data platform prior to Cisco Systems’ acquisition of Splunk in March 2024 for $28 billion.
Since then Cisco, which continues to operate Splunk as a subsidiary company, has worked to leverage Splunk’s data analytics and observability capabilities alongside Cisco’s networking and security technology portfolios. Some of Cisco’s observability development work was transferred to Splunk following the acquisition.
In November, Splunk unveiled a number of new capabilities to its observability portfolio that the company said provide ITOps and engineering teams with more options to unify visibility across their IT environment, “harness control over data,” and improve digital resilience.
Cribl
Top Executive: Clint Sharp, CEO
Cribl calls itself “the universal translator for data,” simplifying the process of collecting and managing telemetry data that serves as “the engine for IT and security.”
Cribl’s product portfolio includes Cribl Stream for collecting and routing telemetry data, Cribl Edge intelligent agent for collecting data from endpoints, Cribl Search for discovering and exploring data, and Cribl Lake for storing, accessing and replaying telemetry data.
In February Cribl launched Cribl Lakehouse, an extension of Cribl Lake purpose-built for storing, managing and analyzing massive volumes of telemetry data at scale.
In January fast-growing Cribl, headquartered in San Franciso, said it had surpassed $200 million in annual recurring revenue, growing ARR by more than 70 percent year over year. The company raised $319 million in Series E funding in October 2023.
DataKitchen
Top Executive: Christopher Bergh, CEO
DataKitchen develops open-source software for data quality assessments, data observability and data operations (DataOps) tasks.
The company’s product portfolio includes DataOps Data Quality TestGen for generative data quality testing, execution and scoring; DataOps Observability for monitoring data pipelines and quickly identifying problems; and DataOps Automation for automating and orchestrating data toolchains.
Founded in 2013, DataKitchen is based in Lexington, Mass.
Grafana Labs
Top Executive: Raj Dutt, CEO
Grafana Labs develops data observability, monitoring and visualization software, offering many of the tools on an open-source basis as well as in commercial Grafana Enterprise and the fully managed Grafana Cloud editions. The products are based on the open-source Prometheus tool for monitoring systems and services.
In August 2024, the New York-based company said it had surpassed $250 million in annual recurring revenue and had more than 5,000 customers. The company also said it had successfully completed a “a primary and secondary transaction” extension of its Series D financing, totaling approximately $270 million, that valued the company at more than $6 billion.
Hydrolix
Top Executive: Marty Kagan, CEO
The Hydrolix Platform develops streaming data lake technology optimized for real-time and historical analysis of log data at petabyte scale. The system provides analytical insights around observability and security systems, along with media/entertainment and advertising tech systems.
Hydrolix also offers a number of products and services based on its platform including an observability service for AWS and an observability solution for Akamai Connect Cloud.
Earlier this month Hydrolix closed an $80 million Series C funding round that will allow the Portland, Ore.-based company to develop its product for additional cloud platforms.
Monte Carlo
Top Executive: Barr Moses, CEO
Monte Carlo develops its Data + AI Observability platform that the company says not only detects data anomalies and problems, but triages incidents, discovers the root cause, determines who was impacted and recommends how to fix the problems.
The Monte Carlo platform also optimizes the cost and performance of big data systems and infrastructure, as well as customer-facing data services and products.
In March Monte Carlo partnered with data cloud company Snowflake to provide data observability capabilities for structured and unstructured data pipelines that power agentic AI applications in Snowflake Cortex AI.
Earlier this month Monte Carlo launched a suite of AI observability agents designed to accelerate monitoring and troubleshooting workflows to improve data and AI system reliability. Monitoring Agent recommends data quality monitoring rules and thresholds and deploys Troubleshooting Agent to investigate data quality issues.
Sumo Logic
Top Executive: Mark Ties, CEO
Sumo Logic’s platform collects and analyzes machine-generated big data with an emphasis on operational IT (including monitoring infrastructure, application and Kubernetes systems), security operations use cases and business intelligence systems.
In December, Sumo Logic, based in Redwood City, Calif., unveiled Sumo Logic Mo Copilot, a DevSecOps AI copilot for development, security and IT operations teams.
Unravel Data
Top Executive: Kunal Agarwal, CEO
Unravel provides an AI-powered data observability platform (what the company is more recently calling a data “actionability” platform) built for the modern data stack. The company places particular emphasis on financial system operational (FinOps) data.
The Unravel Platform’s automation and AI insights capabilities monitor and detect data problems, triage problems and issue alerts, investigate problems and their potential impacts, and provide recommendations for fixes – all with the goal of resolving data problems and prevent them from recurring.
In June 2024 Unravel launched three new AI Agents: the Unravel DataOps Agent, the Unravel FinOps Agent and the Unravel Data Engineering Agent. The agents leverage domain-specific knowledge graphs and advanced automation to tackle specific problems faced by data teams. The agents are part of the Unravel Platform.
