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Top 7 DataOps Platforms SaaS Companies in May 2026

As of May 2026, there are 7 SaaS companies in DataOps Platforms. They have combined revenues of $37.1M and employ 320 people. They have raised $33M and serve - customers combined.

DataOps Platforms are designed to streamline and enhance the management of data workflows, enabling organizations to deliver high-quality data products more efficiently. These platforms facilitate the integration of data from various sources, automate data preparation, and ensure that data is accessible for analytics and decision-making. By promoting collaboration across teams, DataOps Platforms help organizations maintain data integrity while accelerating the data lifecycle from conception to deployment. Common use cases for DataOps Platforms include data integration, data quality monitoring, and automating data pipeline processes. Typical features may include version control for data, automated testing and deployment, and dashboards for monitoring data flows. Various personas, such as data engineers, data analysts, and IT managers, engage with these platforms to optimize their data strategies and ensure their projects align with organizational goals.

Companies
7
Revenue
$37.1M
Funding
$33M
Employees
320

Filters

Sorting: Highest -> Lowest

Filters

Top DataOps Platforms Companies

Showing 10 of 2 companies ranked by annual revenue.

1
Invu Technology

Oakland, California, United States

Invu Technology is technology providing software products and services to startups and corporate enterprises with an emphasis on FinTech. Invu has most recently developed the Invu Data Platform (IDP) with a single objective in mind–to make data science teams more productive in delivering business value. Using IDP, and our extensive experience, we set up and manage highly customized cloud environments for data science teams. IDP is a data ops platform that automates the set-up and management of cloud environments for data science teams. It allows teams to focus their valuable time developing analytical models instead of the cumbersome and tedious work of cloud infrastructure. IDP uses modern technologies like Kubernetes, Terraform, GitOps, and CI/CD to ensure environments are secure, scalable, and fully automated. IDP also includes native integrations with Jupyter, Apache Airflow, Apache Spark, GitHub, Redshift, and Office 365 to provide data science teams with a suite of tools that support their full workflows straight out of the gate.

Revenue
$330K
Customers
-
Year founded
-
Funding
-
Team size
3
Growth
-
2
snapblocs Inc

Seattle, Washington, United States

No-code, Self-Service Infrastructure Platforms on Kubernetes in your Cloud. Build & Scale Data Platforms on K8s, including Microservices in the Cloud. Spend your effort leveraging your data platforms, not building them. snapblocs radically reduces the time and effort required to design, build and operate data platform infrastructure: more innovation, less reinvention. Call us to accelerate your data-driven innovation in the Cloud.

Revenue
$220K
Customers
-
Year founded
2020
Funding
-
Team size
2
Growth
-

Inclusion Criteria

- Must provide capabilities for automating data workflows - Should support integration of diverse data sources and formats - Must include features for monitoring data quality and access control - Should offer collaboration tools for cross-team communication - Not just focused on data storage; must also facilitate data processing and analytics - Must enable version control and traceability for data products