Best Data Observability Tools in the USA

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.

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.

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.

See the impact of data issues without running SQL. We analyze your logs and metadata to identify freshness and volume anomalies, schema changes in tables, pipeline errors, and their blast radius effects on your business. Masthead observes every table, process, script, and dashboard in the data warehouse and connected BI tools for anomalies, alerting data teams in real time if any data failures occur. Masthead shows the origin and implications of data anomalies and pipeline errors on data consumers. Masthead maps data issues on lineage, so you can troubleshoot within minutes, not hours. We get a comprehensive view of all processes in GCP without giving access to our data was a game-changer for us. It saved us both time and money. Gain visibility into the cost of each pipeline running in your cloud, regardless of ETL. Masthead also has AI-powered recommendations to help you optimize your models and queries. It takes 15 min to connect Masthead to all assets in your data warehouse.

Axoflow, the Security Data Layer is the foundation for your SIEM and analytics tools enabling the use of AI, up to 70% faster investigations, and more than 50% reduction in SIEM spend by feeding them with actionable data. Axoflow Platform is built up of the following parts: A pipeline acting as the transportation layer for your security data and also acting as an automated ‘translator’ between data schemas. AI - If you prefer to run your detection content locally - whether it’s an AI or ML model, a threat intel lookup, or another type of enrichment - we’ve got you covered. Storage solutions to facilitate the cost-effective storage of security data and also acting as local storage to run your decentralized detection. Orchestration to weave all of the parts together in an easy-to-use GUI that lets youmonitor and manage, and control and search your data.

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.

Data is the backbone of effective decision-making. However, employees spend more time managing it than using it. 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. Unlock the value of your data investment by making data teams more efficient, improving project outcomes, replacing multiple existing tech solutions, and providing you with a competitive advantage.

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.

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.