Connectors

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Datadog

Data replication

Sync Datadog data anywhere.

Datadog is a monitoring and analytics tool for information technology (IT) and DevOps teams that can be used for performance metrics as well as event monitoring for infrastructure and cloud services. The software can monitor services such as servers, databases and appliances Datadog monitoring software is available for on-premises deployment or as Software as a Service (SaaS). Datadog supports Windows, Linux and Mac operating systems. Support for cloud service providers includes AWS, Microsoft Azure, Red Hat OpenShift, and Google Cloud Platform.

  • Standard
  • Alpha
  • 12 streams
Sync Datadog dataRead the docs
Datadog

One connector

Everything Datadog can do in Airbyte

  • Sync to your warehouse

    Land 12 Datadog tables in 50+ destinations on a schedule you control.

  • Incremental syncs

    Pull only the records that changed since the last run instead of reloading everything.

  • One authorization

    Authenticate Datadog once and Airbyte keeps every scheduled sync running on it.

  • Cloud or self-hosted

    Run the Datadog connector on Cloud, Self-Managed Enterprise.

Specifications

What to know before you sync Datadog

  • Support levelStandard
  • Available onCloud, Self-Managed Enterprise
  • Connector version2.0.24
  • Release stageAlpha

Sync capabilities

  • Full Refresh SyncSupported
  • Incremental SyncSupported
  • NamespacesNot supported
  • Destinations50+ Airbyte connectors

Set up in 11 steps

  1. First, navigate to the Airbyte dashboard and click on "Sources" in the left-hand menu.
  2. Click on the "New Source" button in the top right corner of the screen.
  3. Select "Datadog" from the list of available sources.4. Enter a name for your Datadog source connector and click "Next".
  4. Enter your Datadog API key and application key in the appropriate fields.
  5. Click "Test Connection" to ensure that your credentials are correct and that Airbyte can connect to your Datadog account.
  6. Once the connection is successful, click "Create" to save your Datadog source connector.
  7. You can now use your Datadog source connector to create a new Airbyte pipeline or add it to an existing one.
  8. To create a new pipeline, click on "Pipelines" in the left-hand menu and then click "New Pipeline".
  9. Select your Datadog source connector as the source and choose your destination connector.
  10. Follow the prompts to configure your pipeline and start syncing data between Datadog and your destination.
  11. ‍

12 streams

Every table you can sync from Datadog

  • AuditLogs

  • Dashboards

  • Downtimes

  • IncidentTeams

  • Incidents

  • Logs

  • Metrics

  • Monitors

  • ServiceLevelObjectives

  • SyntheticTests

  • Users

  • Series

Authentication

Authenticate Datadog once

  • API credentials

    Requires API Key and Application Key.

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Common questions

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ETL, an acronym for Extract, Transform, Load, is a vital data integration process. It involves extracting data from diverse sources, transforming it into a usable format, and loading it into a database, data warehouse or data lake. This process enables meaningful data analysis, enhancing business intelligence.

Datadog's API provides access to a wide range of data related to monitoring and analytics of IT infrastructure and applications. The following are the categories of data that can be accessed through Datadog's API:

1. Metrics: Datadog's API provides access to a vast collection of metrics related to system performance, network traffic, application performance, and more.
2. Logs: The API allows users to retrieve logs generated by various applications and systems, which can be used for troubleshooting and analysis.
3. Traces: Datadog's API provides access to distributed traces, which can be used to identify performance bottlenecks and optimize application performance.
4. Events: The API allows users to retrieve events generated by various systems and applications, which can be used for alerting and monitoring purposes.
5. Dashboards: Users can retrieve and manage dashboards created in Datadog, which can be used to visualize and analyze data from various sources.
6. Monitors: The API allows users to create, update, and manage monitors, which can be used to alert on specific conditions or events.
7. Synthetic tests: Datadog's API provides access to synthetic tests, which can be used to simulate user interactions with applications and systems to identify performance issues.

Overall, Datadog's API provides a comprehensive set of data that can be used to monitor and optimize IT infrastructure and applications.

1. First, navigate to the Airbyte dashboard and click on "Sources" in the left-hand menu.
2. Click on the "New Source" button in the top right corner of the screen.
3. Select "Datadog" from the list of available sources.4. Enter a name for your Datadog source connector and click "Next".
5. Enter your Datadog API key and application key in the appropriate fields.
6. Click "Test Connection" to ensure that your credentials are correct and that Airbyte can connect to your Datadog account.
7. Once the connection is successful, click "Create" to save your Datadog source connector.
8. You can now use your Datadog source connector to create a new Airbyte pipeline or add it to an existing one.
9. To create a new pipeline, click on "Pipelines" in the left-hand menu and then click "New Pipeline".
10. Select your Datadog source connector as the source and choose your destination connector.
11. Follow the prompts to configure your pipeline and start syncing data between Datadog and your destination.

‍

The most prominent ETL tools to transfer data to include: Airbyte, Fivetran, StitchData, Matillion, Talend Data Integration. These tools help in extracting data from various sources (APIs, databases, and more), transforming it efficiently, and loading it into and other databases, data warehouses and data lakes, enhancing data management capabilities.

ELT, standing for Extract, Load, Transform, is a modern take on the traditional ETL data integration process. In ELT, data is first extracted from various sources, loaded directly into a data warehouse, and then transformed. This approach enhances data processing speed, analytical flexibility and autonomy.

ETL and ELT are critical data integration strategies with key differences. ETL (Extract, Transform, Load) transforms data before loading, ideal for structured data. In contrast, ELT (Extract, Load, Transform) loads data before transformation, perfect for processing large, diverse data sets in modern data warehouses. ELT is becoming the new standard as it offers a lot more flexibility and autonomy to data analysts.

Start moving Datadog data today

Free for 14 days on Airbyte Cloud. Set up the Datadog connector once and let Airbyte keep it in sync.

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