Compare the Top Data Observability Tools that integrate with Slack as of August 2026

This a list of Data Observability tools that integrate with Slack. Use the filters on the left to add additional filters for products that have integrations with Slack. View the products that work with Slack in the table below.

What are Data Observability Tools for Slack?

Data observability tools help organizations monitor the health, quality, and performance of data systems throughout the entire data lifecycle. They automatically track metrics such as freshness, volume, schema changes, and anomaly detection to identify issues before they impact analytics or business processes. These tools often provide dashboards, alerts, and root-cause insights that make it easier for data engineers and analysts to troubleshoot problems quickly. Many data observability solutions integrate with data warehouses, data lakes, ETL/ELT pipelines, and BI platforms for comprehensive visibility. By improving transparency and reliability, data observability tools help teams maintain trust in their data and accelerate delivery of accurate insights. Compare and read user reviews of the best Data Observability tools for Slack currently available using the table below. This list is updated regularly.

  • 1
    DataHub

    DataHub

    DataHub

    You can't fix what you can't see—and in modern data platforms, visibility is the difference between proactive management and crisis response. DataHub provides comprehensive data observability that helps teams detect, diagnose, and resolve data issues before they impact business operations. Monitor data freshness, volume, schema changes, and quality metrics across your entire data estate with intelligent anomaly detection that learns normal patterns and alerts on deviations. When issues arise, DataHub's lineage graph becomes your debugging tool, tracing problems from symptoms back to root causes across complex multi-hop pipelines. Understand blast radius instantly: which dashboards, reports, and ML models are affected by this upstream failure? Integrate with incident management workflows to route issues to the right owners and track resolution.
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  • 2
    NeuBird

    NeuBird

    NeuBird AI

    NeuBird AI is the creator of The Production Ops Agent, a unified platform of specialized agents engineered to maintain continuous enterprise uptime so engineers don't have to. Because modern production has outgrown human understanding, NeuBird AI reasons over a customer's live environment rather than a stale snapshot, operating entirely within their native infrastructure to proactively prevent anomalies, autonomously resolve incidents, and manage ongoing operations. Backed by top-tier investors including Xora Innovation, Mayfield and M12, NeuBird AI is headquartered in Redwood City, California.
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  • 3
    Code-Cube.io

    Code-Cube.io

    Code-Cube.io

    Code-Cube.io is the full-stack data collection observability platform that protects your dataLayer, tags and conversion data. It detects tracking issues instantly and provides real-time alerts to prevent data loss and performance drops. The platform eliminates the need for manual QA by continuously auditing tracking implementations across websites and applications. Users gain full visibility into how tags and events behave across both client-side and server-side environments. Code-Cube.io ensures that marketing data remains accurate, enabling better decision-making, preventing wasted ad spend and maximizing campaign performance.
    Starting Price: €150/month
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  • 4
    Sifflet

    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.
  • 5
    Rollbar

    Rollbar

    Rollbar

    Discover, predict, and resolve errors in real-time. Go beyond crash reporting, error tracking, logging and error monitoring. Get instant and accurate alerts — plus a real-time feed — of all errors, including unhandled exceptions. Our automation-grade grouping uses machine learning to reduce noise and gives you error signals you can trust.
    Starting Price: $19.00/month
  • 6
    Edge Delta

    Edge Delta

    Edge Delta

    Edge Delta is a new way to do observability that helps developers and operations teams monitor datasets and create telemetry pipelines. We process your log data as it's created and give you the freedom to route it anywhere. Our primary differentiator is our distributed architecture. We are the only observability provider that pushes data processing upstream to the infrastructure level, enabling users to process their logs and metrics as soon as they’re created at the source. We combine our distributed approach with a column-oriented backend to help users store and analyze massive data volumes without impacting performance or cost. By using Edge Delta, customers can reduce observability costs without sacrificing visibility. Additionally, they can surface insights and trigger alerts before data leaves their environment.
    Starting Price: $0.20 per GB
  • 7
    DQOps

    DQOps

    DQOps

    DQOps is an open-source data quality platform designed for data quality and data engineering teams that makes data quality visible to business sponsors. The platform provides an efficient user interface to quickly add data sources, configure data quality checks, and manage issues. DQOps comes with over 150 built-in data quality checks, but you can also design custom checks to detect any business-relevant data quality issues. The platform supports incremental data quality monitoring to support analyzing data quality of very big tables. Track data quality KPI scores using our built-in or custom dashboards to show progress in improving data quality to business sponsors. DQOps is DevOps-friendly, allowing you to define data quality definitions in YAML files stored in Git, run data quality checks directly from your data pipelines, or automate any action with a Python Client. DQOps works locally or as a SaaS platform.
    Starting Price: $499 per month
  • 8
    Dash0

    Dash0

    Dash0

    Dash0 is an OpenTelemetry-native observability platform that unifies metrics, logs, traces, and resources into one intuitive interface, enabling fast and context-rich monitoring without vendor lock-in. It centralizes Prometheus and OpenTelemetry metrics, supports powerful filtering of high-cardinality attributes, and provides heatmap drilldowns and detailed trace views to pinpoint errors and bottlenecks in real time. Users benefit from fully customizable dashboards built on Perses, with support for code-based configuration and Grafana import, plus seamless integration with predefined alerts, checks, and PromQL queries. Dash0's AI-enhanced tools, such as Log AI for automated severity inference and pattern extraction, enrich telemetry data without requiring users to even notice that AI is working behind the scenes. These AI capabilities power features like log classification, grouping, inferred severity tagging, and streamlined triage workflows through the SIFT framework.
    Starting Price: $0.20 per month
  • 9
    Mezmo

    Mezmo

    Mezmo

    Mezmo (formerly LogDNA) enables organizations to instantly centralize, monitor, and analyze logs in real-time from any platform, at any volume. We seamlessly combine log aggregation, custom parsing, smart alerting, role based access controls, and real-time search, graphs, and log analysis in one suite of tools. Our cloud based SaaS solution sets up within two minutes to collect logs from AWS, Docker, Heroku, Elastic and more. Running Kubernetes? Start logging in two kubectl commands. Simple, pay-per-GB pricing without paywalls, overage charges, or fixed data buckets. Simply pay for the data you use on a month-to-month basis. We are SOC2, GDPR, PCI, and HIPAA compliant and are Privacy Shield certified. Our military grade encryption ensures your logs are secure in transit and storage. We empower developers with user-friendly, modernized features and natural search queries. With no special training required, we save you even more time and money.
  • 10
    Bigeye

    Bigeye

    Bigeye

    Bigeye is the data observability platform that helps teams measure, improve, and communicate data quality clearly at any scale. Every time a data quality issue causes an outage, the business loses trust in the data. Bigeye helps rebuild trust, starting with monitoring. Find missing and busted reporting data before executives see it in a dashboard. Get warned about issues in training data before models get retrained on it. Fix that uncomfortable feeling that most of the data is mostly right, most of the time. Pipeline job statuses don't tell the whole story. The best way to ensure data is fit for use, is to monitor the actual data. Tracking dataset-level freshness ensures pipelines are running on schedule, even when ETL orchestrators go down. Find out about changes to event names, region codes, product types, and other categorical data. Detect drops or spikes in row counts, nulls, and blank values to ensure everything is populating as expected.
  • 11
    Metaplane

    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
  • 12
    DataTrust

    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.
  • 13
    Matia

    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.
  • 14
    Datafold

    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.
  • 15
    Great Expectations

    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.
  • 16
    Integrate.io

    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
  • 17
    Pantomath

    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.
  • 18
    Validio

    Validio

    Validio

    See how your data assets are used: popularity, utilization, and schema coverage. Get important insights about your data assets such as popularity, utilization, quality, and schema coverage. Find and filter the data you need based on metadata tags and descriptions. Get important insights about your data assets such as popularity, utilization, quality, and schema coverage. Drive data governance and ownership across your organization. Stream-lake-warehouse lineage to facilitate data ownership and collaboration. Automatically generated field-level lineage map to understand the entire data ecosystem. Anomaly detection learns from your data and seasonality patterns, with automatic backfill from historical data. Machine learning-based thresholds are trained per data segment, trained on actual data instead of metadata only.
  • 19
    Apica

    Apica

    Apica

    Apica is the observability cost optimization leader helping IT teams gain complete control over their telemetry data economics. Apica Ascent processes all observability data types including metrics, logs, traces, and events while optimizing observability costs by 40% compared to traditional approaches. Unlike solutions that lock users into proprietary formats, Ascent offers true flexibility with support for any data lake of choice, on-premises or cloud deployment options, and elimination of expensive tool sprawl through modular solutions. Built to handle high-cardinality data that overwhelms competitive solutions, Ascent includes the patented InstaStore™ optimized storage technology for maximum efficiency and advanced root cause analysis capabilities. Organizations choose us to make observability investments that reduce costs instead of spiraling them out of control.
  • 20
    Soda

    Soda

    Soda

    Soda drives your data operations by identifying data issues, alerting the right people, and helping teams diagnose and resolve root causes. With automated and self-serve data monitoring capabilities, no data—or people—are ever left in the dark. Get ahead of data issues quickly by delivering full observability through easy instrumentation across your data workloads. Empower data teams to discover data issues that automation will miss. Self-service capabilities deliver the broad coverage that data monitoring needs. Alert the right people at the right time to help teams across the business diagnose, prioritize, and fix data issues. With Soda, your data never leaves your private cloud. Soda monitors data at the source and only stores metadata in your cloud.
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