Alternatives to DataKitchen DataOps Automation
Compare DataKitchen DataOps Automation alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to DataKitchen DataOps Automation in 2026. Compare features, ratings, user reviews, pricing, and more from DataKitchen DataOps Automation competitors and alternatives in order to make an informed decision for your business.
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1
DataBuck
FirstEigen
DataBuck is an AI-powered data validation platform that automates risk detection across dynamic, high-volume, and evolving data environments. DataBuck empowers your teams to: ✅ Enhance trust in analytics and reports, ensuring they are built on accurate and reliable data. ✅ Reduce maintenance costs by minimizing manual intervention. ✅ Scale operations 10x faster compared to traditional tools, enabling seamless adaptability in ever-changing data ecosystems. By proactively addressing system risks and improving data accuracy, DataBuck ensures your decision-making is driven by dependable insights. Proudly recognized in Gartner’s 2024 Market Guide for #DataObservability, DataBuck goes beyond traditional observability practices with its AI/ML innovations to deliver autonomous Data Trustability—empowering you to lead with confidence in today’s data-driven world. -
2
Kili Technology
Kili Technology
Kili Technology is one unique tool to label, find and fix issues, simplify DataOps, and dramatically accelerate the build of reliable AI. At Kili Technology, we believe the foundation of better AI is excellent data. Kili Technology's complete training data platform empowers all businesses to transform unstructured data into high quality data to train their AI and deliver successful AI projects. By using Kili Technology to build training datasets, teams will improve their productivity, accelerate go-to-production cycles of their AI projects and deliver quality AI. -
3
dbt
dbt Labs
dbt helps data teams transform raw data into trusted, analysis-ready datasets faster. With dbt, data analysts and data engineers can collaborate on version-controlled SQL models, enforce testing and documentation standards, lean on detailed metadata to troubleshoot and optimize pipelines, and deploy transformations reliably at scale. Built on modern software engineering best practices, dbt brings transparency and governance to every step of the data transformation workflow. Thousands of companies, from startups to Fortune 500 enterprises, rely on dbt to improve data quality and trust as well as drive efficiencies and reduce costs as they deliver AI-ready data across their organization. Whether you’re scaling data operations or just getting started, dbt empowers your team to move from raw data to actionable analytics with confidence.Starting Price: $100 per user/ month -
4
Composable DataOps Platform
Composable Analytics
Composable is an enterprise-grade DataOps platform built for business users that want to architect data intelligence solutions and deliver operational data-driven products leveraging disparate data sources, live feeds, and event data regardless of the format or structure of the data. With a modern, intuitive dataflow visual designer, built-in services to facilitate data engineering, and a composable architecture that enables abstraction and integration of any software or analytical approach, Composable is the leading integrated development environment to discover, manage, transform and analyze enterprise data.Starting Price: $8/hr - pay-as-you-go -
5
MetricSign
MetricSign
MetricSign monitors your entire data stack and detects incidents before your stakeholders do. Connect Power BI via Microsoft OAuth in 2 minutes. MetricSign immediately starts detecting refresh failures, slow datasets, and missed schedules — classifying each with the exact error code and a root cause hint. Beyond Power BI, MetricSign monitors Azure Data Factory, Databricks, dbt Cloud, dbt Core, and Microsoft Fabric. When an ADF pipeline fails and cascades into a Power BI refresh failure, you get one incident — not five separate alerts from five different tools. Key capabilities: - Refresh failure detection with 98+ error code classifications - End-to-end lineage: source → pipeline → dataset → report - Slow refresh and missed schedule detection - Alerts via email, Telegram, webhook - Free plan available — no credit card requiredStarting Price: 69€/3 workspaces -
6
Tengu
Tengu
TENGU is a DataOps Orchestration Platform that works as a central workspace for data profiles of all levels. It provides data integration, extraction, transformation, loading all within it’s graph view UI in which you can intuitively monitor your data environment. By using the platform, business, analytics & data teams need fewer meetings and service tickets to collect data, and can start right away with the data relevant to furthering the company. The Platform offers a unique graph view in which every element is automatically generated with all available info based on metadata. While allowing you to perform all necessary actions from the same workspace. Enhance collaboration and efficiency, with the ability to quickly add and share comments, documentation, tags, groups. The platform enables anyone to get straight to the data with self-service. Thanks to the many automations and low to no-code functionalities and built-in assistant. -
7
Datagaps DataOps Suite
Datagaps
Datagaps DataOps Suite is a comprehensive platform designed to automate and streamline data validation processes across the entire data lifecycle. It offers end-to-end testing solutions for ETL (Extract, Transform, Load), data integration, data management, and business intelligence (BI) projects. Key features include automated data validation and cleansing, workflow automation, real-time monitoring and alerts, and advanced BI analytics tools. The suite supports a wide range of data sources, including relational databases, NoSQL databases, cloud platforms, and file-based systems, ensuring seamless integration and scalability. By leveraging AI-powered data quality assessments and customizable test cases, Datagaps DataOps Suite enhances data accuracy, consistency, and reliability, making it an essential tool for organizations aiming to optimize their data operations and achieve faster returns on data investments. -
8
QuerySurge
RTTS
QuerySurge is the enterprise-grade data quality platform that continuously automates the validation of data across your entire ecosystem ‐ from data warehouses and big data lakes to BI reports and enterprise applications. With AI-powered test creation, a scalable architecture, and seamless CI/CD integration, QuerySurge consistently ensures data integrity at every stage of the pipeline: accelerating delivery, reducing risk, and enabling confident decision-making. Use Cases - Data Warehouse & ETL Testing - Big Data Testing - DevOps for Data / DataOps / Continuous Testing - Data Migration Testing - BI Report Testing - Enterprise App/ERP Testing QuerySurge Features - Data Validation: enterprise-grade platform - AI: Automatically create data validation tests - BI Report Testing: Fully automated, no-code approach - DevOps for Data (DataOps): API w/60+ calls & Swagger docs, integrate continuous testing into your CI/CD pipelines - Data Connectors: For 200+ platforms -
9
Matia
Matia
Matia is a unified DataOps platform designed to simplify modern data management by combining multiple core functions into a single, integrated system. It brings together ETL, reverse ETL, data observability, and a data catalog, eliminating the need for multiple disconnected tools and reducing the complexity of managing fragmented data stacks. It enables teams to move data quickly and reliably from various sources into data warehouses using advanced ingestion capabilities, including real-time updates and error handling, while also allowing them to push trusted data back into operational tools for business use. Matia emphasizes built-in observability at every stage of the data pipeline, providing monitoring, anomaly detection, and automated quality checks to ensure data accuracy and reliability before issues impact downstream systems. -
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Chaos Genius
Chaos Genius
Chaos Genius is a DataOps Observability platform for Snowflake. Enable Snowflake Observability to reduce Snowflake costs and optimize query performance.Starting Price: $500 per month -
11
DataOps DataFlow
Datagaps
A holistic component-based platform for automating Data Reconciliation tests in modern Data Lake and Cloud Data Migration projects using Apache Spark. DataOps DataFlow is a modern, web browser-based solution for automating the testing of ETL, Data Warehouse, and Data Migration projects. Use Dataflow to inject data from any of the varied data sources, compare data, and load differences to S3 or a database. With fast and easy to set up, create and run dataflow in minutes. A best in the class testing tool for Big Data Testing DataOps DataFlow can integrate with all modern and advanced data sources including RDBMS, NoSQL, Cloud, and File-Based.Starting Price: Contact us -
12
Accelario
Accelario
Take the load off of DevOps and eliminate privacy concerns by giving your teams full data autonomy and independence via an easy-to-use self-service portal. Simplify access, eliminate data roadblocks and speed up provisioning for dev, testing, data analysts and more. Accelario Continuous DataOps Platform is a one-stop-shop for handling all of your data needs. Eliminate DevOps bottlenecks and give your teams the high-quality, privacy-compliant data they need. The platform’s four distinct modules are available as stand-alone solutions or as a holistic, comprehensive DataOps management platform. Existing data provisioning solutions can’t keep up with agile demands for continuous, independent access to fresh, privacy-compliant data in autonomous environments. Teams can meet agile demands for fast, frequent deliveries with a comprehensive, one-stop-shop for self-provisioning privacy-compliant high-quality data in their very own environments.Starting Price: $0 Free Forever Up to 10GB -
13
Y42
Datos-Intelligence GmbH
Y42 is the first fully managed Modern DataOps Cloud. It is purpose-built to help companies easily design production-ready data pipelines on top of their Google BigQuery or Snowflake cloud data warehouse. Y42 provides native integration of best-of-breed open-source data tools, comprehensive data governance, and better collaboration for data teams. With Y42, organizations enjoy increased accessibility to data and can make data-driven decisions quickly and efficiently. -
14
Delphix
Perforce
Delphix is the industry leader in DataOps and provides an intelligent data platform that accelerates digital transformation for leading companies around the world. The Delphix DataOps Platform supports a broad spectrum of systems, from mainframes to Oracle databases, ERP applications, and Kubernetes containers. Delphix supports a comprehensive range of data operations to enable modern CI/CD workflows and automates data compliance for privacy regulations, including GDPR, CCPA, and the New York Privacy Act. In addition, Delphix helps companies sync data from private to public clouds, accelerating cloud migrations, customer experience transformation, and the adoption of disruptive AI technologies. Automate data for fast, quality software releases, cloud adoption, and legacy modernization. Source data from mainframe to cloud-native apps across SaaS, private, and public clouds. -
15
Zaloni Arena
Zaloni
End-to-end DataOps built on an agile platform that improves and safeguards your data assets. Arena is the premier augmented data management platform. Our active data catalog enables self-service data enrichment and consumption to quickly control complex data environments. Customizable workflows that increase the accuracy and reliability of every data set. Use machine-learning to identify and align master data assets for better data decisioning. Complete lineage with detailed visualizations alongside masking and tokenization for superior security. We make data management easy. Arena catalogs your data, wherever it is and our extensible connections enable analytics to happen across your preferred tools. Conquer data sprawl challenges: Our software drives business and analytics success while providing the controls and extensibility needed across today’s decentralized, multi-cloud data complexity. -
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Agile Data Engine
Agile Data Engine
Agile Data Engine is a comprehensive DataOps platform designed to streamline the development, deployment, and operation of cloud-based data warehouses. It integrates data modeling, transformations, continuous deployment, workflow orchestration, monitoring, and API connectivity within a single SaaS solution. The platform's metadata-driven approach automates SQL code generation and data load workflows, enhancing productivity and agility in data operations. Supporting multiple cloud database platforms, including Snowflake, Databricks SQL, Amazon Redshift, Microsoft Fabric (Warehouse), Azure Synapse SQL, Azure SQL Database, and Google BigQuery, Agile Data Engine offers flexibility in cloud environments. Its modular data product framework and out-of-the-box CI/CD pipelines facilitate seamless integration and continuous delivery, enabling data teams to adapt swiftly to changing business requirements. The platform also provides insights and statistics on data platform performance. -
17
iceDQ
iceDQ
iceDQ is the #1 data reliability platform offering powerful, unified capabilities for Data Testing, Data Monitoring, and Data Observability. Designed for modern data environments, iceDQ automates complex data pipelines and data migration testing to ensure accuracy, integrity, and trust in your data systems. Its AI-based observability engine continuously monitors data in real-time, quickly detecting anomalies and minimizing business risks. With robust cross-platform connectivity, iceDQ supports seamless data validation, data profiling, and data reconciliation across diverse sources — including databases, files, data lakes, SaaS applications, and cloud environments. Whether you're migrating data, ensuring ETL/ELT process quality, or monitoring live data streams, iceDQ helps enterprises deliver high-quality, reliable data at scale. From financial services to healthcare and beyond, organizations rely on iceDQ to make confident, data-driven decisions backed by trusted data pipelines.Starting Price: $1000 -
18
HighByte Intelligence Hub
HighByte
HighByte Intelligence Hub is a DataOps software solution purpose-built for industrial data. The Intelligence Hub enables manufacturers to securely collect, model, and stream industrial datasets to and from IT systems without writing or maintaining code. The software is deployed at the Edge to merge real-time, transactional, and time-series data into a single payload for consuming applications. With the Intelligence Hub, users can speed system integration time, rapidly leverage contextualized data for analytics, ML, and AI agents, and govern data standards across the enterprise. HighByte Intelligence Hub provides the critical data infrastructure for Industry 4.0. HighByte Intelligence Hub is a software solution that solves data architecture and integration problems at scale for industrial operations. The Intelligence Hub combines Edge operations, advanced data contextualization, and the ability to deliver unique and specific data to multiple end applications in a code-free solution.Starting Price: 18,500 per year -
19
GRAX
GRAX
GRAX is the leader in Salesforce Data Protection throughout its lifecycle, where you can own and control 100% of your Salesforce data. GRAX is disrupting the Salesforce data protection industry by combining Salesforce data backup, recovery, and archiving with scalable data operations (Data Management - DataOps) for a true Salesforce Data Lifecycle Management solution. The same tool that lets you backup, archive, and recover your Salesforce historical data is also the best way to capture, ingest, and pipe those historical versions of your data into your DataOps ecosystem. Reuse and consume your CRM data in industry tools, such as AWS SageMaker, Power BI by Azure, AWS Redshift, Tableau, AWS QuickSight, Snowflake, Google BigQuery, and many others.Starting Price: $9,000/mo per Salesforce Org -
20
DataOps.live
DataOps.live
DataOps.live, the Data Products company, delivers productivity and governance breakthroughs for data developers and teams through environment automation, pipeline orchestration, continuous testing and unified observability. We bring agile DevOps automation and a powerful unified cloud Developer Experience (DX) to modern cloud data platforms like Snowflake. DataOps.live, a global cloud-native company, is used by Global 2000 enterprises including Roche Diagnostics and OneWeb to deliver 1000s of Data Product releases per month with the speed and governance the business demands. -
21
Datonix
Datonix
datonix minimizes data movement, offers native compliance support, and has real-time dataops, Moving data to a server, for example a data warehouse, is often necessary but at the same time it is a real-time barrier and is expensive. datonix, based on the GRID architecture, does not need to move data to process it. Today, it is necessary to make substantial investments and intense and long-lasting evolutionary maintenance to bring data management systems "up to standard". datonix fully supports all the functions necessary to bring a database or an archive up to standard. The data management solutions oriented to real-time analytics that are based on traditional DBMS require complex dataops and the availability of large processing capacities. The datonix algorithms minimize the need for processing capacity and simplify dataops. -
22
Datafold
Datafold
Prevent data outages by identifying and fixing data quality issues before they get into production. Go from 0 to 100% test coverage of your data pipelines in a day. Know the impact of each code change with automatic regression testing across billions of rows. Automate change management, improve data literacy, achieve compliance, and reduce incident response time. Don’t let data incidents take you by surprise. Be the first one to know with automated anomaly detection. Datafold’s easily adjustable ML model adapts to seasonality and trend patterns in your data to construct dynamic thresholds. Save hours spent on trying to understand data. Use the Data Catalog to find relevant datasets, fields, and explore distributions easily with an intuitive UI. Get interactive full-text search, data profiling, and consolidation of metadata in one place. -
23
Unravel
Unravel Data
Unravel is an AI-native data observability platform designed to help modern enterprises detect, resolve, and prevent data issues at scale. It uses intelligent, automated agents that work alongside data teams to surface insights, guide decisions, and reduce operational toil. Unravel brings data observability and FinOps together, enabling organizations to improve performance, ensure reliability, and optimize cloud data spending. The platform provides end-to-end visibility across pipelines, workloads, and infrastructure. With agent-driven actionability™, Unravel can take action on behalf of teams, integrate directly with existing tools, or recommend next-best actions. It supports major data platforms including Databricks, Snowflake, and Google Cloud BigQuery. By combining automation with human control, Unravel transforms data observability into a collaborative, always-on partner. -
24
Orchestra
Orchestra
Orchestra is a Unified Control Plane for Data and AI Operations, designed to help data teams build, deploy, and monitor workflows with ease. It offers a declarative framework that combines code and GUI, allowing users to implement workflows 10x faster and reduce maintenance time by 50%. With real-time metadata aggregation, Orchestra provides full-stack data observability, enabling proactive alerting and rapid recovery from pipeline failures. It integrates seamlessly with tools like dbt Core, dbt Cloud, Coalesce, Airbyte, Fivetran, Snowflake, BigQuery, Databricks, and more, ensuring compatibility with existing data stacks. Orchestra's modular architecture supports AWS, Azure, and GCP, making it a versatile solution for enterprises and scale-ups aiming to streamline their data operations and build trust in their AI initiatives. -
25
Piperr
Saturam
Produce high quality data using Piperr’s pre-built data algorithms for multiple enterprise stakeholders: From IT to Analytics, From Tech & Data Science to LoBs. No Worries. If your Data platform is not already accommodated, we will build connectors at no cost. Piperr™ has a default dashboard with an elegant chart base. We also support Tableau, PowerBI, and other visualization tools. You can use our ML-augmented data algorithms or choose to bring your own trained ML models. No more Dataops turnaround. While your team focusses on AI Models, the data life-cycle can be left upto Piperr. Minimise your data operations turn-around time: From Acquisition to Test Data Management: with Piperr’s pre-packaged data apps. Piperr™ provides necessary tools to tame data chaos within an enterprise. Look no further than Piperr™ to solve all your data processing needs. -
26
IBM DataStage
IBM
Accelerate AI innovation with cloud-native data integration on IBM Cloud Pak for data. AI-powered data integration, anywhere. Your AI and analytics are only as good as the data that fuels them. With a modern container-based architecture, IBM® DataStage® for IBM Cloud Pak® for Data delivers that high-quality data. It combines industry-leading data integration with DataOps, governance and analytics on a single data and AI platform. Automation accelerates administrative tasks to help reduce TCO. AI-based design accelerators and out-of-the-box integration with DataOps and data science services speed AI innovation. Parallelism and multicloud integration let you deliver trusted data at scale across hybrid or multicloud environments. Manage the data and analytics lifecycle on the IBM Cloud Pak for Data platform. Services include data science, event messaging, data virtualization and data warehousing. Parallel engine and automated load balancing. -
27
Varada
Varada
Varada’s dynamic and adaptive big data indexing solution enables to balance performance and cost with zero data-ops. Varada’s unique big data indexing technology serves as a smart acceleration layer on your data lake, which remains the single source of truth, and runs in the customer cloud environment (VPC). Varada enables data teams to democratize data by operationalizing the entire data lake while ensuring interactive performance, without the need to move data, model or manually optimize. Our secret sauce is our ability to automatically and dynamically index relevant data, at the structure and granularity of the source. Varada enables any query to meet continuously evolving performance and concurrency requirements for users and analytics API calls, while keeping costs predictable and under control. The platform seamlessly chooses which queries to accelerate and which data to index. Varada elastically adjusts the cluster to meet demand and optimize cost and performance. -
28
Estuary Flow
Estuary
Estuary Flow is a new kind of DataOps platform that empowers engineering teams to build real-time, data-intensive applications at scale with minimal friction. This platform unifies a team’s databases, pub/sub systems, and SaaS around their data, without requiring new investments in infrastructure or development.Starting Price: $200/month -
29
Sifflet
Sifflet
Automatically cover thousands of tables with ML-based anomaly detection and 50+ custom metrics. Comprehensive data and metadata monitoring. Exhaustive mapping of all dependencies between assets, from ingestion to BI. Enhanced productivity and collaboration between data engineers and data consumers. Sifflet seamlessly integrates into your data sources and preferred tools and can run on AWS, Google Cloud Platform, and Microsoft Azure. Keep an eye on the health of your data and alert the team when quality criteria aren’t met. Set up in a few clicks the fundamental coverage of all your tables. Configure the frequency of runs, their criticality, and even customized notifications at the same time. Leverage ML-based rules to detect any anomaly in your data. No need for an initial configuration. A unique model for each rule learns from historical data and from user feedback. Complement the automated rules with a library of 50+ templates that can be applied to any asset. -
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Huawei Cloud ModelArts
Huawei Cloud
ModelArts is a comprehensive AI development platform provided by Huawei Cloud, designed to streamline the entire AI workflow for developers and data scientists. It offers a full-lifecycle toolchain that includes data preprocessing, semi-automated data labeling, distributed training, automated model building, and flexible deployment options across cloud, edge, and on-premises environments. It supports popular open source AI frameworks such as TensorFlow, PyTorch, and MindSpore, and allows for the integration of custom algorithms tailored to specific needs. ModelArts features an end-to-end development pipeline that enhances collaboration across DataOps, MLOps, and DevOps, boosting development efficiency by up to 50%. It provides cost-effective AI computing resources with diverse specifications, enabling large-scale distributed training and inference acceleration. -
31
Acceldata
Acceldata
Acceldata is an Agentic Data Management company helping enterprises manage complex data systems with AI-powered automation. Its unified platform brings together data quality, governance, lineage, and infrastructure monitoring to deliver trusted, actionable insights across the business. Acceldata’s Agentic Data Management platform uses intelligent AI agents to detect, understand, and resolve data issues in real time. Designed for modern data environments, it replaces fragmented tools with a self-learning system that ensures data is accurate, governed, and ready for AI and analytics. -
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Datagaps ETL Validator
Datagaps
DataOps ETL Validator is the most comprehensive data validation and ETL testing automation tool. Comprehensive ETL/ELT validation tool to automate the testing of data migration and data warehouse projects with easy-to-use low-code, no-code component-based test creation and drag-and-drop user interface. ETL process involves extracting data from various sources, transforming it to fit operational needs, and loading it into a target database or data warehouse. ETL testing involves verifying the accuracy, integrity, and completeness of data as it moves through the ETL process to ensure it meets business rules and requirements. Automating ETL testing can be achieved using tools that automate data comparison, validation, and transformation tests, significantly speeding up the testing cycle and reducing manual labor. ETL Validator automates ETL testing by providing intuitive interfaces for creating test cases without extensive coding. -
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Decube
Decube
Decube is a data management platform that helps organizations manage their data observability, data catalog, and data governance needs. It provides end-to-end visibility into data and ensures its accuracy, consistency, and trustworthiness. Decube's platform includes data observability, a data catalog, and data governance components that work together to provide a comprehensive solution. The data observability tools enable real-time monitoring and detection of data incidents, while the data catalog provides a centralized repository for data assets, making it easier to manage and govern data usage and access. The data governance tools provide robust access controls, audit reports, and data lineage tracking to demonstrate compliance with regulatory requirements. Decube's platform is customizable and scalable, making it easy for organizations to tailor it to meet their specific data management needs and manage data across different systems, data sources, and departments. -
34
Apache Airflow
The Apache Software Foundation
Airflow is a platform created by the community to programmatically author, schedule and monitor workflows. Airflow has a modular architecture and uses a message queue to orchestrate an arbitrary number of workers. Airflow is ready to scale to infinity. Airflow pipelines are defined in Python, allowing for dynamic pipeline generation. This allows for writing code that instantiates pipelines dynamically. Easily define your own operators and extend libraries to fit the level of abstraction that suits your environment. Airflow pipelines are lean and explicit. Parametrization is built into its core using the powerful Jinja templating engine. No more command-line or XML black-magic! Use standard Python features to create your workflows, including date time formats for scheduling and loops to dynamically generate tasks. This allows you to maintain full flexibility when building your workflows. -
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Manta
Manta
Manta is an automated data lineage platform that helps organizations record, track, visualize, and optimize how data flows from its origin through transformation to consumption across their entire data environment, delivering full visibility and control of data pipelines that manual methods can’t match. It automatically scans metadata, SQL code, ETL workflows, BI/report definitions, and other data sources with support for dozens of technologies to build detailed, end-to-end lineage maps showing where data comes from, how it’s transformed, and where it’s used, enabling accurate impact analysis, root-cause tracing, and error detection. It provides rich visualizations with dynamic filtering, granular lineage at table and column levels, and APIs for integration with metadata catalogs, CI/CD workflows, and governance systems, reducing manual effort and accelerating DataOps, migrations, compliance, and governance initiatives.Starting Price: $29.99 per month -
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Genesis Computing
Genesis Computing
Genesis Computing provides an enterprise AI platform built around autonomous “AI data agents” that automate complex data engineering and analytics workflows across an organization’s existing technology stack. It introduces a new category of AI knowledge workers that operate as autonomous agents capable of executing full data workflows rather than simply suggesting code or analysis. These agents can research data sources, ingest and transform datasets, map raw data from source systems to structured analytical targets, generate and run data pipeline code, create documentation, perform testing, and monitor pipelines in production environments. By handling these tasks end-to-end, the platform reduces the manual workload typically required to build and maintain data pipelines and analytics infrastructure.Starting Price: Free -
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definity
definity
Monitor and control everything your data pipelines do with zero code changes. Monitor data and pipelines in motion to proactively prevent downtime and quickly root cause issues. Optimize pipeline runs and job performance to save costs and keep SLAs. Accelerate code deployments and platform upgrades while maintaining reliability and performance. Data & performance checks in line with pipeline runs. Checks on input data, before pipelines even run. Automatic preemption of runs. definity takes away the effort to build deep end-to-end coverage, so you are protected at every step, across every dimension. definity shifts observability to post-production to achieve ubiquity, increase coverage, and reduce manual effort. definity agents automatically run with every pipeline, with zero footprints. Unified view of data, pipelines, infra, lineage, and code for every data asset. Detect in run-time and avoid async checks. Auto-preempt runs, even on inputs. -
38
Pantomath
Pantomath
Organizations continuously strive to be more data-driven, building dashboards, analytics, and data pipelines across the modern data stack. Unfortunately, most organizations struggle with data reliability issues leading to poor business decisions and lack of trust in data as an organization, directly impacting their bottom line. Resolving complex data issues is a manual and time-consuming process involving multiple teams all relying on tribal knowledge to manually reverse engineer complex data pipelines across different platforms to identify root-cause and understand the impact. Pantomath is a data pipeline observability and traceability platform for automating data operations. It continuously monitors datasets and jobs across the enterprise data ecosystem providing context to complex data pipelines by creating automated cross-platform technical pipeline lineage. -
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DataTrust
RightData
DataTrust is built to accelerate test cycles and reduce the cost of delivery by enabling continuous integration and continuous deployment (CI/CD) of data. It’s everything you need for data observability, data validation, and data reconciliation at a massive scale, code-free, and easy to use. Perform comparisons, and validations, and do reconciliation with re-usable scenarios. Automate the testing process and get alerted when issues arise. Interactive executive reports with quality dimension insights. Personalized drill-down reports with filters. Compare row counts at the schema level for multiple tables. Perform checksum data comparisons for multiple tables. Rapid generation of business rules using ML. Flexibility to accept, modify, or discard rules as needed. Reconciling data across multiple sources. DataTrust solutions offers the full set of applications to analyze source and target datasets. -
40
Anomalo
Anomalo
Anomalo helps you get ahead of data issues by automatically detecting them as soon as they appear in your data and before anyone else is impacted. Detect, root-cause, and resolve issues quickly – allowing everyone to feel confident in the data driving your business. Connect Anomalo to your Enterprise Data Warehouse and begin monitoring the tables you care about within minutes. Our advanced machine learning will automatically learn the historical structure and patterns of your data, allowing us to alert you to many issues without the need to create rules or set thresholds. You can also fine-tune and direct our monitoring in a couple of clicks via Anomalo’s No Code UI. Detecting an issue is not enough. Anomalo’s alerts offer rich visualizations and statistical summaries of what’s happening to allow you to quickly understand the magnitude and implications of the problem. -
41
Blaize AI Studio
Blaize
AI Studio delivers AI-driven, application end-to-end data operations (DataOps), development operations (DevOps), and Machine Learning operations (MLOps) tools. Our AI Software Platform reduces your dependency on critical resources like Data Scientists and Machine Learning (ML) engineers, reduces the time from development to deployment, and makes it easier to manage edge AI systems over the product’s lifetime. AI Studio is designed for deployment to edge inference accelerators, on-premises edge servers, systems, and AI-as-a-Service (AIaaS) for cloud-based applications. Reducing the time between data capture and AI deployment at the Edge with powerful data-labeling and annotation functions. Automated process leveraging AI knowledge base, MarketPlace and guided strategies, enabling Business Experts with AI expertise and solutions adds. -
42
SYNQ
SYNQ
SYNQ is a data observability platform that helps modern data teams define, monitor, and manage their data products. It brings together ownership, testing, and incident workflows so teams can stay ahead of issues, reduce data downtime, and deliver trusted data faster. With SYNQ, every critical data product has clear ownership and real-time visibility into its health. When something breaks, the right people are alerted—with the context they need to understand and resolve the issue quickly. At the center of SYNQ is Scout, your autonomous, always-on data quality agent. Scout proactively monitors data products, recommends what and where to test, does root-cause analysis and fixes issues. It connects lineage, issue history, and contextual data to help teams fix problems faster. SYNQ integrates with the tools you already use and is trusted by leading scale-ups and enterprises such as VOI, Avios, Aiven and Ebury.Starting Price: $0 -
43
Metaplane
Metaplane
Monitor your entire warehouse in 30 minutes. Identify downstream impact with automated warehouse-to-BI lineage. Trust takes seconds to lose and months to regain. Gain peace of mind with observability built for the modern data era. Code-based tests take hours to write and maintain, so it's hard to achieve the coverage you need. In Metaplane, you can add hundreds of tests within minutes. We support foundational tests (e.g. row counts, freshness, and schema drift), more complex tests (distribution drift, nullness shifts, enum changes), custom SQL, and everything in between. Manual thresholds take a long time to set and quickly go stale as your data changes. Our anomaly detection models learn from historical metadata to automatically detect outliers. Monitor what matters, all while accounting for seasonality, trends, and feedback from your team to minimize alert fatigue. Of course, you can override with manual thresholds, too.Starting Price: $825 per month -
44
Radicalbit
Radicalbit
Radicalbit Natural Analytics (RNA) is a DataOps platform for Streaming Data Integration and Real-time Advanced Analytics. Choose the easiest way to deliver data at the right time in the right hands. RNA provides users with the latest technologies – in self service mode – for real-time data processing, taking advantage of Artificial Intelligence solutions for extracting value from data. It automates the labor-intensive process of data analysis and helps convey important findings and insights in understandable formats. Have a Real-time situational awareness and timely insights to respond quickly and appropriately. Achieve new levels of efficiency and optimization and guarantee collaboration between siloed teams. Manage and monitor the models from a centralized view, and deploy your evolving models in seconds. No downtime. -
45
Integrate.io
Integrate.io
Unify Your Data Stack: Experience the first no-code data pipeline platform and power enlightened decision making. Integrate.io is the only complete set of data solutions & connectors for easy building and managing of clean, secure data pipelines. Increase your data team's output with all of the simple, powerful tools & connectors you’ll ever need in one no-code data integration platform. Empower any size team to consistently deliver projects on-time & under budget. We ensure your success by partnering with you to truly understand your needs & desired outcomes. Our only goal is to help you overachieve yours. Integrate.io's Platform includes: -No-Code ETL & Reverse ETL: Drag & drop no-code data pipelines with 220+ out-of-the-box data transformations -Easy ELT & CDC :The Fastest Data Replication On The Market -Automated API Generation: Build Automated, Secure APIs in Minutes - Data Warehouse Monitoring: Finally Understand Your Warehouse Spend - FREE Data Observability: Custom -
46
Great Expectations
Great Expectations
Great Expectations is a shared, open standard for data quality. It helps data teams eliminate pipeline debt, through data testing, documentation, and profiling. We recommend deploying within a virtual environment. If you’re not familiar with pip, virtual environments, notebooks, or git, you may want to check out the Supporting. There are many amazing companies using great expectations these days. Check out some of our case studies with companies that we've worked closely with to understand how they are using great expectations in their data stack. Great expectations cloud is a fully managed SaaS offering. We're taking on new private alpha members for great expectations cloud, a fully managed SaaS offering. Alpha members get first access to new features and input to the roadmap. -
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Managed Service for Apache Airflow is a fully managed workflow orchestration platform from Google Cloud built on the open-source Apache Airflow project. It allows users to author, schedule, and monitor data pipelines using Python-based workflows known as DAGs. The platform eliminates the need to manage infrastructure, enabling teams to focus on building and running pipelines. It integrates seamlessly with Google Cloud services such as BigQuery, Dataflow, and Managed Service for Apache Spark. It also supports hybrid and multi-cloud environments, allowing workflows to span across different systems. Users benefit from built-in monitoring, logging, and troubleshooting tools for reliability. The service is designed to simplify complex data workflows, including ETL, MLOps, and automation tasks. Overall, it provides a scalable and flexible solution for orchestrating modern data pipelines.Starting Price: $0.074 per vCPU hour
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FLIP
Kanerika
Flip, Kanerika's AI-powered Data Operations Platform, simplifies the complexity of data transformation with its low-code/no-code approach. Designed to help organizations build data pipelines seamlessly, Flip offers flexible deployment options, a user-friendly interface, and a cost-effective pay-per-use pricing model. Empowering businesses to modernize their IT strategies, Flip accelerates data processing and automation, unlocking actionable insights faster. Whether you aim to streamline workflows, enhance decision-making, or stay competitive, Flip ensures your data works harder for you in today’s dynamic landscape.Starting Price: $1614/month -
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K2View
K2View
At K2View, we believe that every enterprise should be able to leverage its data to become as disruptive and agile as the best companies in its industry. We make this possible through our patented Data Product Platform, which creates and manages a complete and compliant dataset for every business entity – on demand, and in real time. The dataset is always in sync with its underlying sources, adapts to changes in the source structures, and is instantly accessible to any authorized data consumer. Data Product Platform fuels many operational use cases, including customer 360, data masking and tokenization, test data management, data migration, legacy application modernization, data pipelining and more – to deliver business outcomes in less than half the time, and at half the cost, of any other alternative. The platform inherently supports modern data architectures – data mesh, data fabric, and data hub – and deploys in cloud, on-premise, or hybrid environments. -
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Bruin
Bruin Data
Bruin is a data platform for data and analytics engineering teams that combines data ingestion, transformation, orchestration and analytics workflows. Teams define pipelines as code in a Git repository using SQL, Python or R, with dependencies, materializations and data-quality checks managed alongside assets. Built-in connectors move data from databases, warehouses, SaaS tools, files and APIs into supported destinations; transformations run in the connected warehouse. Bruin Cloud adds managed scheduling, run monitoring, lineage, a data catalog, access controls and usage tracking, while the open-source CLI can run locally, in CI, in a team's cloud environment or on-premises. An AI data analyst answers questions from governed warehouse data in chat or the browser and can show the SQL behind its answers. Teams can also create dashboards, data apps and scheduled agents from shared data.Starting Price: $0.01/credit
