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
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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Databand
Databand is a proactive data observability platform that ties directly into all stages of your data pipelines, starting with your source data. It automatically collects metadata from your modern data stack, builds historical baselines based on common data pipeline behavior, and lets you get visibility into every data flow from source to destination. It pinpoints unknown data incidents and reduces mean time to detection (MTTD) from days to minutes.
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Datafold
Datafold automatically imports and unifies data descriptions from all sources, including data warehouses and ELT tools such as dbt and Airflow, providing a holistic view with full-text search. It lets you get a high-level overview of your pipelines, zoom in on tables or columns, trace the flow end to end from raw data to BI dashboards. Moreover, it automatically constructs the field-level lineage graph by parsing every query ever executed in your data warehouses.
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Soda
Soda is a data observability platform that automatically monitors and manages the health of your data through anomaly detection and dashboards. It allows everyone on your data team to find, analyze, and resolve data issues. It helps you use a common language to check and manage data quality across all data sources, from ingestion to consumption.
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Dynatrace
Being named a leader among products in Database Monitoring Software, Dynatrace database observability helps you track and measure your database metrics in real-time to optimize application performance. It monitors and analyzes the database activity of your services, providing you with observability down to individual SQL and NoSQL statements.
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New Relic
New Relic is a simple, powerful platform for observability that collects and contextualizes all operational data from any source and simplifies instrumentation, data ingestion, exploration, correlation, and machine learning-powered analysis to support observability. Its full-stack observability lets you easily visualize, analyze, and troubleshoot your entire software stack in one connected experience.
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Datadog
Datadog is a unified observability platform that provides full visibility into the health and performance of each layer of your environment. It is an easy-to-navigate observability platform to explore and analyze your data, create and customize dashboards and other visualizations for data from across your systems, and leverage observability platform features like actionable alerts, threat detection rules, and the Datadog API. Overall, it brings together end-to-end traces, metrics, and logs to make your applications, infrastructure, and third-party services entirely observable.
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Splunk Observability
Splunk Observability is the only full-stack, analytics-powered, and OpenTelemetry-native observability solution. It provides end-to-end visibility across your entire hybrid technology landscape, from application performance monitoring, infrastructure monitoring, and real user monitoring, to synthetic monitoring, log observer, and IT service intelligence.
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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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Elastic Observability
Elastic Observability transforms your data into actionable observability. It is built on the proven ELK Stack to converge metrics, logs, and traces, delivering unified visibility and actionable insights. With Elastic Observability, you can easily ingest metrics, logs, and traces quickly and easily from applications and infrastructure hosted in a data center or on cloud providers.
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Grafana Cloud
Grafana Cloud is a composable observability platform, integrating metrics, traces, and logs with Grafana. It leverages the best open-source observability software, including Prometheus, Loki, and Tempo, without the overhead of installing, maintaining, and scaling your observability stack. With Grafana Cloud you can go from zero to beautiful graphs, insightful logs, and valuable alerts in minutes.
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Instana
Instana's Enterprise Observability Platform ingests all performance metrics, traces all requests, and profiles every process, along with the capabilities needed to make observability work for the enterprise. Its automatic discovery, monitoring, root cause analysis, and feedback reduce the amount of stress when deploying new code or making changes to the system with immediate feedback on the performance and quality of your applications at each step of the software delivery pipeline.
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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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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.