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

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

What are Data Observability Tools for Datadog?

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 Datadog currently available using the table below. This list is updated regularly.

  • 1
    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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  • 2
    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.
  • 3
    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
  • 4
    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
  • 5
    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.
  • 6
    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.
  • 7
    Observo AI

    Observo AI

    Observo AI

    ​Observo AI is an AI-native data pipeline platform designed to address the challenges of managing vast amounts of telemetry data in security and DevOps operations. By leveraging machine learning and agentic AI, Observo AI automates data optimization, enabling enterprises to process AI-generated data more efficiently, securely, and cost-effectively. It reduces data processing costs by over 50% and accelerates incident response times by more than 40%. Observo AI's features include intelligent data deduplication and compression, real-time anomaly detection, and dynamic data routing to appropriate storage or analysis tools. It also enriches data streams with contextual information to enhance threat detection accuracy while minimizing false positives. Observo AI offers a searchable cloud data lake for efficient data storage and retrieval.
  • 8
    Canopy

    Canopy

    Canopy

    Enable your development team to save massive amounts of time, simplify operations, and deliver experiences fast with Canopy. Connect securely to best-of-breed SaaS platforms, relational databases, spreadsheets, and csv files. Build new connectors to any data set in minutes, including internal data, niche & long-tail SaaS platforms, and complex integrations. Prepare your data in the perfect format for any experience or action. Deliver data through your curated API with the right communication and caching strategy for optimal performance. Quickly view, manage, and troubleshoot everything you care about with real-time insights, actions, and controls. Engineered to exceed enterprise demands with unmatched security, compliance, scalability, and speed.
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