Best Data Observability Tools for Looker

Find and compare the best Data Observability tools for Looker in 2026

Use the comparison tool below to compare the top Data Observability tools for Looker on the market. You can filter results by user reviews, pricing, features, platform, region, support options, integrations, and more.

  • 1
    DataHub Reviews
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    In the realm of contemporary data platforms, the ability to see and understand your data is crucial—it's what separates proactive management from reactive crisis handling. DataHub offers an all-encompassing data observability solution that empowers teams to identify, analyze, and rectify data-related challenges before they disrupt business operations. With features that allow you to oversee data freshness, volume, schema alterations, and quality metrics throughout your entire data landscape, DataHub employs smart anomaly detection to recognize typical patterns and notify you of any irregularities. When problems do surface, the lineage graph in DataHub serves as a powerful debugging resource, allowing you to trace issues from their symptoms back to their origin within intricate multi-hop data pipelines. Gain immediate insight into the impact of an upstream failure: which dashboards, reports, and machine learning models are affected? Seamlessly integrate with incident management processes to assign issues to the appropriate stakeholders and monitor the progress of their resolution.
  • 2
    Sifflet Reviews
    Effortlessly monitor thousands of tables through machine learning-driven anomaly detection alongside a suite of over 50 tailored metrics. Ensure comprehensive oversight of both data and metadata while meticulously mapping all asset dependencies from ingestion to business intelligence. This solution enhances productivity and fosters collaboration between data engineers and consumers. Sifflet integrates smoothly with your existing data sources and tools, functioning on platforms like AWS, Google Cloud Platform, and Microsoft Azure. Maintain vigilance over your data's health and promptly notify your team when quality standards are not satisfied. With just a few clicks, you can establish essential coverage for all your tables. Additionally, you can customize the frequency of checks, their importance, and specific notifications simultaneously. Utilize machine learning-driven protocols to identify any data anomalies with no initial setup required. Every rule is supported by a unique model that adapts based on historical data and user input. You can also enhance automated processes by utilizing a library of over 50 templates applicable to any asset, thereby streamlining your monitoring efforts even further. This approach not only simplifies data management but also empowers teams to respond proactively to potential issues.
  • 3
    DQOps Reviews

    DQOps

    DQOps

    $499 per month
    DQOps is a data quality monitoring platform for data teams that helps detect and address quality issues before they impact your business. Track data quality KPIs on data quality dashboards and reach a 100% data quality score. DQOps helps monitor data warehouses and data lakes on the most popular data platforms. DQOps offers a built-in list of predefined data quality checks verifying key data quality dimensions. The extensibility of the platform allows you to modify existing checks or add custom, business-specific checks as needed. The DQOps platform easily integrates with DevOps environments and allows data quality definitions to be stored in a source repository along with the data pipeline code.
  • 4
    Decube Reviews
    Decube is a comprehensive data management platform designed to help organizations manage their data observability, data catalog, and data governance needs. Our platform is designed to provide accurate, reliable, and timely data, enabling organizations to make better-informed decisions. Our data observability tools provide end-to-end visibility into data, making it easier for organizations to track data origin and flow across different systems and departments. With our real-time monitoring capabilities, organizations can detect data incidents quickly and reduce their impact on business operations. The data catalog component of our platform provides a centralized repository for all data assets, making it easier for organizations to manage and govern data usage and access. With our data classification tools, organizations can identify and manage sensitive data more effectively, ensuring compliance with data privacy regulations and policies. The data governance component of our platform provides robust access controls, enabling organizations to manage data access and usage effectively. Our tools also allow organizations to generate audit reports, track user activity, and demonstrate compliance with regulatory requirements.
  • 5
    Masthead Reviews

    Masthead

    Masthead

    $899 per month
    Experience the implications of data-related problems without the need to execute SQL queries. Our approach involves a thorough analysis of your logs and metadata to uncover issues such as freshness and volume discrepancies, changes in table schemas, and errors within pipelines, along with their potential impacts on your business operations. Masthead continuously monitors all tables, processes, scripts, and dashboards in your data warehouse and integrated BI tools, providing immediate alerts to data teams whenever failures arise. It reveals the sources and consequences of data anomalies and pipeline errors affecting consumers of the data. By mapping data problems onto lineage, Masthead enables you to resolve issues quickly, often within minutes rather than spending hours troubleshooting. The ability to gain a complete overview of all operations within GCP without granting access to sensitive data has proven transformative for us, ultimately leading to significant savings in both time and resources. Additionally, you can achieve insights into the expenses associated with each pipeline operating in your cloud environment, no matter the ETL method employed. Masthead is equipped with AI-driven recommendations designed to enhance the performance of your models and queries. Connecting Masthead to all components within your data warehouse takes just 15 minutes, making it a swift and efficient solution for any organization. This streamlined integration not only accelerates diagnostics but also empowers data teams to focus on more strategic initiatives.
  • 6
    ThinkData Works Reviews
    ThinkData Works provides a robust catalog platform for discovering, managing, and sharing data from both internal and external sources. Enrichment solutions combine partner data with your existing datasets to produce uniquely valuable assets that can be shared across your entire organization. The ThinkData Works platform and enrichment solutions make data teams more efficient, improve project outcomes, replace multiple existing tech solutions, and provide you with a competitive advantage.
  • 7
    Metaplane Reviews

    Metaplane

    Metaplane

    $825 per month
    In 30 minutes, you can monitor your entire warehouse. Automated warehouse-to-BI lineage can identify downstream impacts. Trust can be lost in seconds and regained in months. With modern data-era observability, you can have peace of mind. It can be difficult to get the coverage you need with code-based tests. They take hours to create and maintain. Metaplane allows you to add hundreds of tests in minutes. Foundational tests (e.g. We support foundational tests (e.g. row counts, freshness and schema drift), more complicated tests (distribution shifts, nullness shiftings, enum modifications), custom SQL, as well as everything in between. Manual thresholds can take a while to set and quickly become outdated as your data changes. Our anomaly detection algorithms use historical metadata to detect outliers. To minimize alert fatigue, monitor what is important, while also taking into account seasonality, trends and feedback from your team. You can also override manual thresholds.
  • 8
    DataTrust Reviews
    DataTrust is designed to speed up testing phases and lower delivery costs by facilitating continuous integration and continuous deployment (CI/CD) of data. It provides a comprehensive suite for data observability, validation, and reconciliation at an extensive scale, all without the need for coding and with user-friendly features. Users can conduct comparisons, validate data, and perform reconciliations using reusable scenarios. The platform automates testing processes and sends alerts when problems occur. It includes interactive executive reports that deliver insights into quality dimensions, alongside personalized drill-down reports equipped with filters. Additionally, it allows for comparison of row counts at various schema levels across multiple tables and enables checksum data comparisons. The rapid generation of business rules through machine learning adds to its versatility, giving users the option to accept, modify, or discard rules as required. It also facilitates the reconciliation of data from multiple sources, providing a complete array of tools to analyze both source and target datasets effectively. Overall, DataTrust stands out as a powerful solution for enhancing data management practices across different organizations.
  • 9
    Orchestra Reviews
    Orchestra serves as a Comprehensive Control Platform for Data and AI Operations, aimed at empowering data teams to effortlessly create, deploy, and oversee workflows. This platform provides a declarative approach that merges coding with a graphical interface, enabling users to develop workflows at a tenfold speed while cutting maintenance efforts by half. Through its real-time metadata aggregation capabilities, Orchestra ensures complete data observability, facilitating proactive alerts and swift recovery from any pipeline issues. It smoothly integrates with a variety of tools such as dbt Core, dbt Cloud, Coalesce, Airbyte, Fivetran, Snowflake, BigQuery, Databricks, and others, ensuring it fits well within existing data infrastructures. With a modular design that accommodates AWS, Azure, and GCP, Orchestra proves to be a flexible option for businesses and growing organizations looking to optimize their data processes and foster confidence in their AI ventures. Additionally, its user-friendly interface and robust connectivity options make it an essential asset for organizations striving to harness the full potential of their data ecosystems.
  • 10
    Integrate.io Reviews
    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. 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 Pipeline Alerts to Monitor Data in Real-Time
  • 11
    Pantomath Reviews
    Organizations are increasingly focused on becoming more data-driven, implementing dashboards, analytics, and data pipelines throughout the contemporary data landscape. However, many organizations face significant challenges with data reliability, which can lead to misguided business decisions and a general mistrust in data that negatively affects their financial performance. Addressing intricate data challenges is often a labor-intensive process that requires collaboration among various teams, all of whom depend on informal knowledge to painstakingly reverse engineer complex data pipelines spanning multiple platforms in order to pinpoint root causes and assess their implications. Pantomath offers a solution as a data pipeline observability and traceability platform designed to streamline data operations. By continuously monitoring datasets and jobs within the enterprise data ecosystem, it provides essential context for complex data pipelines by generating automated cross-platform technical pipeline lineage. This automation not only enhances efficiency but also fosters greater confidence in data-driven decision-making across the organization.
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