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Amazon MSK

Streaming

Greenplum

Databases

Supabase

Databases

Azure Delta Lake

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Chroma

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Pinecone

Vector database

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Streaming

Kafka

Streaming

SAP Hana

Warehouse

Webex

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Azure Data Factory

Orchestration Join the waitlist

Azure Synapse

Warehouse

MongoDB

Databases Join the waitlist

Azure SQL Database

Databases

Teradata

Warehouse

Oracle DB

Databases

Fivetran

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ServiceNow

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Apache Airflow

Orchestration

Atlan

Catalogs

Amazon Athena

Lake/Lakehouse

Google Big Query

Warehouse

Databricks

Lake/Lakehouse

dbt

Orchestration

Amazon EMR

Lake/Lakehouse

aws Glue

Lake/Lakehouse

Apache Hive

Lake/Lakehouse

Looker

BI tools

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BI tools

PostgreSQL

Databases

Opsgenie

Collaboration channels

PagerDuty

Collaboration channels

Power BI

BI tools

Prefect

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Presto

Lake/Lakehouse

Amazon Redshift

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Amazon S3

Lake/Lakehouse

Sisense

BI tools

Slack

Collaboration channels

Snowflake

Warehouse

Apache Spark

Lake/Lakehouse

Tableau

BI tools

Microsoft Teams

Collaboration channels

Webhooks

Collaboration channels

Alation

Catalogs

Sigma Computing

BI tools

MySQL

Databases

Microsoft SQL Server

Databases

Jira Software

Collaboration channels

Github

Code/model repository

data.world

Catalogs

  • Monte Carlo makes it easy to customize your environment with our API, API Explorer, SDK, CLI, and Webhooks. You can also create new monitors and notifications programmatically with Monitors as Code.

    Learn more

  • Customize your data observability workflows, monitors, notifications, and platform features via our simple yet powerful SDK.

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  • Use Monte Carlo’s CLI to configure your data observability platform programmatically.

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Fits into your development workflows.

Deploy Monte Carlo’s automated monitors and custom rules as part of your CI/CD process with YAML-based monitors configuration.

Learn how

Prevent painful backfills.

Stop bad data in its tracks to avoid inaccurate reporting and costly backfills by embedding data quality checks into your pipelines.

Read our docs

Related resources

2023: The state of data quality

Did you know that bad data impacts 31% of a company’s revenue? And that 74% of data engineers say data quality issues are surfaced first by stakeholders? These stats and more in our recent survey with Wakefield Research.

Learn more

3 simple steps for Snowflake cost optimization without getting too crazy.

Snowflake cost optimization efforts need to be right sized. Learn how to get the most savings with investing too much of your team’s time.

Learn more

Data testing vs. data quality monitoring vs. data observability: What's right for your team?

In the fight against bad data and broken pipelines, there are a few popular options. But what makes the most sense for your data quality needs? We’ve got the answers.

Learn more