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 Databricks
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.
| Data Lineage: |
|
|---|---|
| Data Monitoring: |
|
| Data Profiling: |
|
| Export: | - |
| Free edition: |
|
| Machine Learning: |
|
| Notifications: |
|
| Schema Change Tracking: |
|
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.
| Data Lineage: |
|
|---|---|
| Data Monitoring: |
|
| Data Profiling: |
|
| Export: | CSV,JSON,ORC,PARQUET |
| Free edition: |
|
| Machine Learning: |
|
| Notifications: |
|
| Schema Change Tracking: |
|
Dataedo
Dataedo is a data governance & data catalog software with data observability features such as data lineage, data profiling, and schema change tracking.
| Data Lineage: |
|
|---|---|
| Data Monitoring: |
|
| Data Profiling: |
|
| Export: | HTML,MS Excel,PDF |
| Free edition: |
|
| Machine Learning: |
|
| Notifications: |
|
| Schema Change Tracking: |
|
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.
| Data Lineage: |
|
|---|---|
| Data Monitoring: |
|
| Data Profiling: |
|
| Export: | - |
| Free edition: |
|
| Machine Learning: |
|
| Notifications: |
|
| Schema Change Tracking: |
|
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.
| Data Lineage: |
|
|---|---|
| Data Monitoring: |
|
| Data Profiling: |
|
| Export: | CSV,XML,FDF |
| Free edition: |
|
| Machine Learning: |
|
| Notifications: |
|
| Schema Change Tracking: |
|
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.
| Data Lineage: |
|
|---|---|
| Data Monitoring: |
|
| Data Profiling: |
|
| Export: | CSV |
| Free edition: |
|
| Machine Learning: |
|
| Notifications: |
|
| Schema Change Tracking: |
|
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.
| Data Lineage: |
|
|---|---|
| Data Monitoring: |
|
| Data Profiling: |
|
| Export: | CSV,JSON,PDF,XML |
| Free edition: |
|
| Machine Learning: |
|
| Notifications: |
|
| Schema Change Tracking: |
|
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.
| Data Lineage: |
|
|---|---|
| Data Monitoring: |
|
| Data Profiling: |
|
| Export: | - |
| Free edition: |
|
| Machine Learning: |
|
| Notifications: |
|
| Schema Change Tracking: |
|
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.