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DataOps Tools

DataOps Tools Reviews and Ratings

What are DataOps Tools?

Gartner defines DataOps as the collaborative data management practice focusing on improving communication, continuous integration, automation, observability and operations of data flows between data managers, data consumers, and their teams across the organization. DataOps tools connect and orchestrate data pipelines across heterogeneous systems. Data and analytics leaders are the buyers in this emerging market. The primary audience for DataOps tools is “data manager” personas like, data engineers, data integration developers, operations/incident analysts, database administrators and data architects. The secondary audience is “data consumer” personas like business analysts, business intelligence developers, data scientists and citizen roles (departmental users who are domain experts, but less technical).

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Logo of Databricks Data Intelligence Platform

Databricks Data Intelligence Platform

By Databricks

4.6
(19 Ratings)

Databricks is a global company focusing on data and AI. At the core of Databricks is the Databricks Data Intelligence Platform which allows entire organizations to use data and AI to power a wide range of business use cases. It's built on a lakehouse to provide an open, unified foundation for all data and governance and is powered by a Data Intelligence Engine that understands the uniqueness of the organizations’ data. Databricks simplifies and accelerates enterprises' data and AI goals by unifying data, analytics and AI on one platform. Its key mission is to assist data teams in addressing some of the world's most challenging problems.

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Logo of Unravel

Unravel

By Unravel

4.6
(13 Ratings)

Unravel provides a data observability platform aimed at enhancing the efficiency of data teams. Its main focus is on intelligently optimizing, automatic troubleshooting, and cost control of data applications and pipelines. The platform is compatible with modern data stacks and the company's technology can analyze, capture, and correlate detailed insights that are crucial to maximizing business value from data. Unravel's capabilities also extend to hybrid and multi-cloud functionalities across all major cloud providers. It is compatible with various modern data stack systems like Databricks, Amazon EMR, Google BigQuery, and Snowflake. The company has its main office located in Palo Alto, California, along with other offices globally.

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Logo of Astro

Astro

By Astronomer

5
(6 Ratings)

Astronomer is the company behind Astro, a unified DataOps platform powered by Apache Airflow. Astro enables data teams to build, run, observe, and manage mission-critical data pipelines for data-, analytics-, and AI-driven applications. It supports the development of reliable data products by enabling workflow orchestration, observability, and automation. With built-in data observability features such as logging, metrics, and lineage tracking, Astronomer helps teams monitor and troubleshoot workflows in production. Organizations across industries use Astronomer to operationalize data across cloud, hybrid, and on-premises environments.

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Logo of AnalyticsCreator

AnalyticsCreator

By AnalyticsCreator

4.5
(4 Ratings)

AnalyticsCreator focuses on automating the design, development, deployment, and change processes of data and analytics strategies. It allows teams to manage data for analytical needs efficiently, saving time and reducing costs and project risks. The tool enhances transparency and compliance, facilitating rapid prototyping to showcase results quickly. AnalyticsCreator generates code for data management through analytical frontends such as Power BI, compatible with Azure SQL DB, Azure data warehouse, and on-premises MS SQL, offering streamlined data management solutions.

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Logo of DataOps.live platform

DataOps.live platform

By DataOps.live

5
(4 Ratings)

DataOps.live is an enterprise that aims to strike the right balance between governance and agility in data pipelines on Snowflake. The main problem it solves is streamlining the DataOps lifecycle, leveraging its platform for agile DevOps automation. It fundamentally provides end-to-end orchestration, environment management, CI/CD, and automated testing. The platform is designed to aid faster development, foster parallel collaboration, enhance efficiencies, and cut down costs, while ensuring data assurance. Its prime focus is to help businesses achieve agility and data governance at an affordable total cost of ownership without making any compromises.

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Logo of SuprSend

SuprSend

By SuprSend

5
(2 Ratings)

SuprSend operates as an all-in-one communication platform with an API-first approach, specializing in the creation, management, and delivery of notifications to final users over multiple channels with smart and reliable mechanisms in place like idempotency, channel/ vendor routing/ managing volume spikes, and all of it at a scale of more than 1 billion notifications.

This takes away the necessity for in-house development of any notification service for engagement or transactional notifications, focusing on superior user experiences.

Some other features include batching, digests, multi-tenancy i.e, sending white-labeled notifications, and user preferences in an embedded and hosted manner. For security and compliance, SuprSend is HIPPA, SOC 2, and GDPR compliant.

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Logo of Apica Observe

Apica Observe

By Apica

4
(1 Rating)

Apica provides solutions for observability cost optimization, enabling IT teams to manage and control telemetry data economics. Apica Ascent is designed to process a wide range of observability data types, including metrics, logs, traces, and events, while addressing the challenges of cost efficiency and data management. The platform supports integration with any data lake and offers both on-premises and cloud deployment options.

Apica Ascent uses modular solutions to help organizations streamline their observability tools and reduce complexity. Its InstaStore storage technology is engineered for high-cardinality data environments, supporting large-scale data storage and advanced root cause analysis. The product is built to help organizations make strategic observability investments that align with budgetary goals and operational needs.

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Logo of HighByte Intelligence Hub

HighByte Intelligence Hub

By HighByte

4
(1 Rating)

HighByte is an industrial software company founded in 2018 in Portland, Maine USA. The company builds solutions that address the data architecture and integration challenges faced by manufacturers and industrial companies as they digitally transform. HighByte Intelligence Hub, the company’s edge-native Industrial DataOps software, provides modeled, ready-to-use datasets to the Cloud and AI Agents using a codeless interface that speeds integration time and reduces cost. The Intelligence Hub has been deployed in dozens of countries by mid-size to large industrial companies spanning a wide range of vertical markets, including automotive, energy, food and beverage, life sciences, and mining and metals.

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Logo of IBM Databand

IBM Databand

By IBM

5
(1 Rating)

IBM is a well-established entity focused on technology and development. The primary mission revolves around fostering technological growth and enhancing infrastructure, achieved through focused developments and consulting services. By encouraging inventiveness and innovation, it is geared towards facilitating the transition of theoretical ideas into practical realities, thus improving global functionalities. IBM brings about transformation by creating advanced solutions that reshape and redefine the world.

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Logo of iCEDQ Data Testing and Monitoring

iCEDQ Data Testing and Monitoring

By iCEDQ

4
(1 Rating)
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Logo of Saagie

Saagie

By Saagie

3
(1 Rating)

Saagie is a company focused on providing a link between established IT and data science sectors. Its paramount goal revolves around aiding large-scale organizations to modernize their businesses through the application of significant Data and Artificial Intelligence (AI). Saagie serves as an essential toolkit featuring salient open-source technologies intended for data extraction and refinement along with the building and operation of AI-rooted applications within a secure and compliant structure. Predominantly used in the Banking and Insurance industries, the platform is fully managed and expedites the implementation time of big data projects. Furthermore, it draws focus away from expensive, critical administrative processes, allowing businesses to concentrate on creating impactful solutions such as churn reduction and fraud detection, thereby enhancing their competitive standing. Saagie stands for Data Intelligence that is accessible to all.

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Logo of Universal Automation Center

Universal Automation Center

By Stonebranch

3
(1 Rating)

Stonebranch is an enterprise focused on devising and providing IT orchestration and automation solutions. The main aim is to assist companies in transitioning their IT environments from basic IT task automation to complex, real-time business service automation. The Stonebranch Universal Automation Platform makes it possible for organizations to smoothly orchestrate workloads and data across various technological systems and silos. With its central location in Atlanta, Georgia, Stonebranch has established points of contact and support around the world, thus serving a diverse range of sectors including financial, manufacturing, healthcare, travel, transportation, energy and technology.

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Logo of Ascend Data Automation Cloud

Ascend Data Automation Cloud

By Ascend.io

Ascend centers its efforts on providing a single platform for Data Pipeline Automation, an integral component in the creation of intelligent data pipelines. Its primary business concern is dealing with change detection and propagation throughout a client's ecosystem. Ascend aims to guarantee data precision and calculate the expenditure associated with various data merchandise.

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Logo of Cognite Data Fusion

Cognite Data Fusion

By Cognite

Cognite is an industrial Software-as-a-Service (SaaS) provider that facilitates the digitalisation of the industrial sector. The firm has developed a unique class of industrial software that enhances operation security, efficiency, and sustainability in asset-intensive industries. The principal software product is Cognite Data Fusion (CDF), created to swiftly contextualize OT/IT data to build and expand company solutions. Cognite's technology incorporates elements such as hybrid AI, big data, machine learning, and 3D modelling. The company's services cater to industries such as oil and gas, power and utilities, renewable energy, manufacturing, and other heavy-asset sectors. Cognite aims to support industries in sustainable transition and scaling without affecting their financial performance, focusing on turning data into accessible, insightful, and open resource. The firm was established in 2016 and has a diverse team consisting of software developers, data scientists, designers, and 3D specialists.

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Logo of Composable DataOps

Composable DataOps

By Composable Analytics

Composable Analytics, Inc. specializes in the creation of software tailored to suit the modern data strategies for enterprises. The Composable DataOps Platform, a product crafted through central technology designed at MIT for the U.S. Department of Defense, expedites the process of developing data-dependent applications. This platform provides a streamlined framework for data-laden applications and Enterprise AI solutions.

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Logo of DataKitchen DataOps

DataKitchen DataOps

By DataKitchen

DataKitchen offers software solutions designed to track and automate all data processes within an organization, from the source to the final customer interaction point. This feature extends to both the development and production stages, aiding teams in supplying their clients with precise insights while minimizing potential errors. Their platform additionally allows data and analytics teams to monitor, examine, and control the mechanisms, processes, and surroundings throughout the entirety of their data analytics division, consequently contributing to notable improvements in quality, turnaround time, and overall team efficiency.

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Logo of IBM StreamSets

IBM StreamSets

By IBM

IBM is a well-established entity focused on technology and development. The primary mission revolves around fostering technological growth and enhancing infrastructure, achieved through focused developments and consulting services. By encouraging inventiveness and innovation, it is geared towards facilitating the transition of theoretical ideas into practical realities, thus improving global functionalities. IBM brings about transformation by creating advanced solutions that reshape and redefine the world.

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Logo of Lumada DataOps Suite (Legacy)

Lumada DataOps Suite (Legacy)

By Hitachi Vantara

Hitachi Vantara, a subsidiary of Hitachi Ltd., offers modern data storage and infrastructure systems, intelligent data management and AI-powered hybrid cloud solutions. The company empowers customers to build a data foundation for sustainable business growth.

Logo of Matia DataOps Platform

Matia DataOps Platform

By Matia

Matia is a data operations platform specializing in the streamlining of data management processes. The company offers a range of services including unified data ingestion, reverse ETL, observability, and catalog construction. These capabilities are built to complement the modern data stack. With a strong focus on promoting effortless collaboration, Matia provides the necessary tools that enable organizations and their data teams to make quicker and more informed decisions.

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Logo of Nexla Data Integration Platform

Nexla Data Integration Platform

By Nexla

Nexla is an enterprise data integration platform. The company's main product is a platform that caters to diverse levels of data handling competencies. It enables easy integration, transformation, monitoring and provisioning of data for an array of uses. Moreover, this platform promotes collaborative data preparation, resulting in ready-to-use data products. Nexla's focus lies in offering governed and agile data operations with minimized complexities.

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Features of DataOps Tools

Updated November 2025

Mandatory Features:

  • Data pipeline observability: Optimizes pipelines, monitors and detects data quality issues, collects data usage patterns, traces data flow lineage, and spots data anomalies using native and/or integrated live and historical metadata that is harvested from orchestrated pipelines and related data assets. This includes monitoring, logging, business-rule detection and metadata capture

  • Data pipeline orchestration: Automates, coordinates and monitors existing and new data pipelines from a single integrated platform simplifying the management of end-to-end data flow complexity through a common control plane. It manages, integrates, schedules and automates tasks across diverse sets of data pipelines. Includes connector management, workflow impact analysis, and data pipeline audit logs

Optional Features:

  • Data pipeline deployment automation: Automates the version-control processes, DevOps integration, release of pipelines, and change management approvals of data-related components across release cycles via a continuous integration/continuous deployment (CI/CD) methodology

  • Data pipeline test automation: Practices executions of pipeline code “dry runs,” business rules validation, test scripts management, regression testing packs and test data management

  • Environment management: Minimize the repeated manual effort creating, maintaining, and optimizing the deployment of pipelines across environments (development, testing (including user acceptance testing), staging and production, for example). This uses an infrastructure-as-code model to execute repeatable testing patterns including resource provisioning, environment templating and secure credentials. DataOps can reliably and repeatedly instantiate build specs across all data pipeline life cycle stages ensuring that environment runtime conditions are consistently applied

Gartner Research

Market Guide for DataOps Tools

Top Trending Products

Databricks Data Intelligence PlatformUniversal Automation CenterDataOps.live platformApica Observe

Popular Product Comparisons

DataOps.live platform vs UnravelDatabricks Data Intelligence Platform vs SuprSendDatabricks Data Intelligence Platform vs DataOps.live platform

Gartner Peer Insights content consists of the opinions of individual end users based on their own experiences, and should not be construed as statements of fact, nor do they represent the views of Gartner or its affiliates. Gartner does not endorse any vendor, product or service depicted in this content nor makes any warranties, expressed or implied, with respect to this content, about its accuracy or completeness, including any warranties of merchantability or fitness for a particular purpose.

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