The Coolest Data Observability And DataOps Companies Of The 2024 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.

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.

This week CRN is running the CRN 2024 Big Data 100 in a series of slide shows, organized by technology category, spotlighting vendors of business analytics software, database systems, data warehouse and data lake systems, data management and integration software, data operations and observability tools, and big data systems and cloud platforms.

Here's a look at 10 companies with products in the data operations and data observability space.

This list includes vendors who develop data observability tools used to monitor and manage data quality and vendors of observability software primarily used to monitor system performance.

Some vendors have big data product portfolios that span multiple technology categories. They appear in the Big Data 100 slideshow for the technology segment in which they are most prominent.


Top Executive: CEO Rohit Choudhary

Acceldata says its all-in-one observability platform provides insights into data stacks to improve data quality, pipeline reliability, platform performance and spending efficiency across enterprise data systems in the cloud, on premises and in hybrid systems.

In February Acceldata boosted its data observability offerings with the launch of new AI technology that uses advanced machine learning algorithms to analyze huge volumes of data for automated anomaly detection, root cause analysis and predictive analytics.

That followed Acceldata’s September acquisition of AI engine developer Bewgle, a move Acceldata said would allow it to expand its observability capabilities into AI and large language models.

Campbell, Calif.-based Acceldata was founded in 2018.


Top Executive: CEO Kyle Kirwan

Bigeye’s data observability and data monitoring platform provides enterprise-grade data observability, including AI-driven anomaly detection and comprehensive data lineage, for both modern and legacy data stacks.

Bigeye was founded in 2019 by CEO Kyle Kirwan and CTO Egor Gryaznov who both worked at Uber on the data pipelines for the company’s in-house A/B testing tool.

In December Bigeye received a strategic investment from data analytics platform company Alteryx. The amount was undisclosed, but Bigeye said it brought its total funding to $68.5 million.


Top Executive: CEO Clint Sharp

Cribl describes its technology as “the data engine for IT and security.” The company’s product portfolio, including Cribl Stream, Cribl Edge and Cribl Search, collects data from any source, processes billions of events per second, automatically routes data to optimize storage, and analyzes the data.

Earlier this month Cribl launched Cribl Lake, a turnkey data lake system that is provisioned from Cribl.Cloud and allows IT and security teams to collect and control their data.

In March San Francisco-based Cribl said the startup recorded “record-breaking” growth in annual recurring revenue, triple-digit customer growth, more than 140 percent net dollar retention, and greater adoption of Crible.Cloud and its multi-product suite of data management software.


Top Executive: CEO Christopher Bergh

DataKitchen says its DataOps software provides a way for data and analytic teams to observe complex end-to-end processes, generate and execute tests, and validate data, tools, processes and environments across their entire data analytics organizations.

DataKitchen, based in Lexington, Mass., develops its DataOps Observability, DataOps Automation and DataOps TestGen software for data production teams and data science and data engineering professionals.

Grafana Labs

Top Executive: CEO Raj Dutt

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 Grafana Cloud editions. The products are based on the open-source Prometheus tool for monitoring systems and services.

Earlier this month Grafana Labs, based in New York, debuted Grafana 11.0 with a new Explore Metric capability for identifying a problem’s root cause. The release also provides improved visualizations, simpler alerting and support for additional data sources.

The company also launched Grafana Alloy, the company’s distribution of the open-source OpenTelemetry software.

Monte Carlo

Top Executive: CEO Barr Moses

Monte Carlo’s Data Observability Platform is an end-to-end system for monitoring data stacks and providing alerts for data issues across data warehouses, data lakes, ETL (extract, transform and load) systems and business analytics tools.

The system automatically and immediately identifies the root cause of data problems using machine learning-based incident monitoring and resolution capabilities.

Monte Carlo and Fivetran, developer of a cloud-based automated data movement platform, recently collaborated to integrate their software, allowing organizations that use both products to better monitor data quality at time of ingestion.

Monte Carlo, based in San Francisco, raised $135 million in Series D funding in May 2022.


Top Executive: EVP and General Manager Gary Steele

Splunk has been one of the long-time leaders in data observability with its platform for collecting, indexing and managing machine-generated data.

Splunk offers Splunk Enterprise and Splunk Cloud Platform for working with machine data. In addition, it provides a number of specific tools for observability and security – the two most popular use cases for the Splunk platform.

On March 18 networking tech giant Cisco Systems completed its $28 billion acquisition of Splunk. Cisco plans to incorporate Splunk’s technology into its own security and observability product portfolio. Look for more details at upcoming Splunk .conf24 and Cisco Live 2024 events.

For its fiscal 2024 (ended Jan. 31) Splunk, headquartered in San Francisco, reported revenue of $4.22 billion.


Sumo Logic

Top Executive: President and CEO Joe Kim

Sumo Logic’s cloud-based log analytics platform provides log data management, monitoring and analytics services using machine-generated big data. The AI-powered system is used for a number of observability and security use cases including infrastructure monitoring, security operations and DevSecOps.

Sumo Logic, based in Redwood City, Calif., was acquired by global investment firm Francisco Partners in May 2023 and Joe Kim was named president and CEO shortly after.


Top Executive: CEO Mona Rakibe

Telmai, founded in 2020 and headquartered in San Francisco, is one of the more recent startups in the data observability arena. Telmai’s AI-driven data observability platform helps data teams automate the process of monitoring data pipelines, using a range of data quality metrics and KPIs, and proactively detect and investigate data anomalies in real time.

Telmai released a new edition of its software in September 2023 with a number of features designed to simplify and accelerate data observability adoption. New functionality included “time travel” retrospective analysis of historical data, private cloud options across the three major public clouds, and end-to-end observability for heterogeneous data pipelines.

The company raised $5.5 million in seed funding in June, 2023.

Unravel Data

Top Executive: CEO Kunal Agarwal

Unravel Data provides an AI-powered DataOps and FinOps observability platform for data teams, helping DataOps professionals maintain control of their cloud data.

Unravel’s platform provides the data quality management, data cost governance, data application optimization and troubleshooting capabilities that data teams need for cloud migration initiatives and cost-effectively operating data-intensive cloud applications.

Over the last year Unravel, based in Palo Alto, Calif., has been partnering with leading cloud platform companies to bring its observability capabilities to those systems including data lakehouse observability and FinOps for Databricks, cloud data cost optimization for Snowflake, and cloud data cost observability and optimization for Google Cloud BigQuery.