SQL Server
Oracle
MySQL
PostgreSQL
Amazon Redshift
Azure SQL Database
DBT
Google Big Query
IBM DB2
MariaDB
SAP HANA
Snowflake
SQLite
Teradata
Vertica
Data observability tools for Amazon S3
Data observability tools help the company track and understand the state of its data at any given time and provide it with full insight into their data pipelines. They also allow them to identify, monitor and troubleshoot errors in order to minimize data issues and improve high data quality.
Monte Carlo
Monte Carlo's Data Observability platform uses machine learning to infer and learn what your data looks like, proactively identify data downtime, assess its impact, and notify those who need to know. It automatically and immediately identifies the root cause and lets you see all your data dependencies in one place, thereby allowing you to collaborate and resolve issues faster.
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Acceldata
Acceldata is a multi-layer data observability platform that empowers data teams with deep insights into compute, spend,
data reliability, pipelines, and users. It offers fully-automated reliability checks, which help immediately know about missing, late, or erroneous data on thousands of tables. From modern cloud data platforms to traditional databases to complex files, it helps you apply enterprise data reliability standards across your company.
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Dataedo
Dataedo is a data governance & data catalog software with data observability features such as data lineage, data profiling, and schema change tracking.
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Amazon CloudWatch
Amazon CloudWatch is a monitoring and observability service built for DevOps engineers, developers, site reliability engineers, and IT managers. CloudWatch provides you with data and actionable insights to monitor your applications, respond to system-wide performance changes, optimize resource utilization, and get a unified view of operational health. Moreover, it collects monitoring and operational data as logs, metrics, and events, providing you with a unified view of AWS resources, applications, and services that run on AWS and on-premises servers.
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Anodot
Anodot provides granular observability into the health of your data and identifies data quality issues in real-time. Anodot’s AI analytics can analyze 100% of the data you collect, detect anomalies and business incidents in real time and identify their root cause, enabling you to remedy problems faster and capture opportunities sooner.
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Lightstep
Lightstep is a complete, unified, and primary observability platform for the enterprise that provides complete system visibility and context at scale. It automatically detects changes to your application, infrastructure, and user experience — and surface the specific causes. Moreover, Understand and improve performance across millions of devices, users, and customers. Overall, visualize, aggregate, and analyze planet-scale application and infrastructure metrics at a fraction of the cost
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Data observability tools help the company track and understand the state of its data at any given time and provide it with full insight into their data pipelines. They also allow them to identify, monitor and troubleshoot errors in order to minimize data issues and improve high data quality.
By monitoring data across multi-layered IT architecture, data observability tools enable identifying bottlenecks and data issues no matter where they originate. Thanks to new insights into how the data is moving through your IT infrastructure, it's possible to improve identification and resolution of the errors and search for the issues that could potentially be missed.
To help you select the best solution for monitoring the data health in your company, we've prepared a list of data observability tools that will enable your team to understand your data systems to fix and prevent data problems.