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Open-source ELT from Postgres destination to any destination

Open-source ELT from Postgres destination to any destination

Open-source database replication from Postgres destination

Open-source ETL to Postgres destination

Airbyte enables you to load your Postgres destination data into any data warehouse, lake, or database in minutes using our pre-built, no-code connectors.

Airbyte enables you to load your Postgres destination data into any data warehouse, lake, or database in minutes using our pre-built, no-code connectors.

Replicate your Postgres destination data into any data warehouses, lakes or databases, in minutes, using Change Data Capture. In the format you need with post-load transformation.

Replicate data from any sources into Postgres destination, in minutes. In the format you need with post-load transformation.

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15,000+
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4,000+
daily active companies
1PB+
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Top companies trust Airbyte to centralize their Data

Start analyzing your Postgres destination data in three easy steps

1

Setup a Postgres destination connector in Airbyte

Connect to Postgres destination or one of 300+ Airbyte data sources through simple account authentication

2

Set up a destination for your extracted Postgres destination data

Choose from one of 50+ destinations where you want to import data from your Postgres destination source. This can be a cloud data warehouse, database, data lake, or any other supported Airbyte destination.

3

Configure the Postgres destination connection in Airbyte

This includes selecting the data you want to extract - streams and columns -, the sync frequency, where in the destination you want that data to be loaded.

Start analyzing your Postgres destination data in three easy steps

1

Setup a Postgres destination connector in Airbyte

Connect to Postgres destination or one of 300+ Airbyte data sources through simple account authentication

2

Set up a destination for your extracted Postgres destination data

Choose from one of 50+ destinations where you want to import data from your Postgres destination source. This can be a cloud data warehouse, database, data lake, or any other supported Airbyte destination.

3

Configure the Postgres destination connection in Airbyte

This includes selecting the data you want to extract - streams and columns -, the sync frequency, where in the destination you want that data to be loaded.

Start syncing data from any source to Postgres destination in three easy steps

1

Set up a source connector to extract data from in Airbyte

Choose from one of 300+ sources where you want to import data from. This can be any API tool, cloud data warehouse, database, data lake, files, among other source types. You can even build your own source connector in minutes with our no-code connector builder.

2

Set up Postgres destination as the destination connector

Connect to Postgres destination or one of 50+ Airbyte data sources through simple account authentication

3

Configure the connection in Airbyte

This includes selecting the data you want to extract - streams and columns -, the sync frequency, where in Postgres destination you want that data to be loaded.

LOVED by 10,000 (DATA) ENGINEERS

Ship more quickly with the only solution that fits ALL your needs.

As your tools and edge cases grow, you deserve an extensible and open ELT solution that eliminates the time you spend on building and maintaining data pipelines

Leverage the largest catalog of  connectors

Airbyte’s catalog of 300+ pre-built, no-code connectors is the largest in the industry and is doubling every year, thanks to its open-source community, while closed-source catalogs have plateaued.

Cover your custom needs with our extensibility

Build custom connectors in 10 min with our Connector Development Kit (CDK), and get them maintained by us or our community. Add them to Airbyte to enable your whole team to leverage them.
Customize ANY Airbyte connectors to address Your custom needs. Our connector’s code is open-source, so you can edit it as you see fit.

Reliability at every level

Airbyte ensure your team’s time is no longer time spent on maintenance with our reliability SLAs on our GA connectors.
Airbyte will also give you visibility and control of your data freshness at the stream level for all your connections.
LOVED by 10,000 (DATA) ENGINEERS

Ship more quickly with the only solution that fits ALL your needs.

As your tools and edge cases grow, you deserve an extensible and open ELT solution that eliminates the time you spend on building and maintaining data pipelines

Leverage the largest catalog of  connectors

Airbyte’s catalog of 300+ pre-built, no-code connectors is the largest in the industry and is doubling every year, thanks to its open-source community, while closed-source catalogs have plateaued.

Cover your custom needs with our extensibility

Build custom connectors in 10 min with our Connector Development Kit (CDK), and get them maintained by us or our community. Add them to Airbyte to enable your whole team to leverage them.
Customize ANY Airbyte connectors to address Your custom needs. Our connector’s code is open-source, so you can edit it as you see fit.

Reliability at every level

Airbyte ensure your team’s time is no longer time spent on maintenance with our reliability SLAs on our GA connectors.
Airbyte will also give you visibility and control of your data freshness at the stream level for all your connections.
LOVED by 10,000 (DATA) ENGINEERS

Ship more quickly with the only solution that fits ALL your needs.

As your tools and edge cases grow, you deserve an extensible and open ELT solution that eliminates the time you spend on building and maintaining data pipelines

Leverage the largest catalog of  connectors

Airbyte’s catalog of 300+ pre-built, no-code connectors is the largest in the industry and is doubling every year, thanks to its open-source community, while closed-source catalogs have plateaued.

Cover your custom needs with our extensibility

Build custom connectors in 10 min with our Connector Development Kit (CDK), and get them maintained by us or our community. Add them to Airbyte to enable your whole team to leverage them.
Customize ANY Airbyte connectors to address Your custom needs. Our connector’s code is open-source, so you can edit it as you see fit.

Reliability at every level

Airbyte ensure your team’s time is no longer time spent on maintenance with our reliability SLAs on our GA connectors.
Airbyte will also give you visibility and control of your data freshness at the stream level for all your connections.

Move large volumes, fast.

Quickly get up and running with a 5-minute setup that supports both incremental and full refreshes, for databases of any size.

Change Data Capture.

Airbyte's log-based CDC allows for fast detection of all data changes and efficient replication with minimal resources.

Security from source to destination.

Securely connect to your database using our reliable connection methods (SSL/TLS, SSH tunnels). Bring your own cloud too!

We support the CDC methods your company needs

Log-based CDC

Our binary log reader asynchronously reads the transaction logs to identify any changes made to the database. This scalable method can handle large volumes of data and enables real-time CDC.
Read more about CDC

Timestamp-based CDC

Changes are identified using a cursor, and only the changes made since the last sync are replicated.
Learn more

It’s never been easier to integrate your Postgres destination data into your data warehouse, lake or database

It’s never been easier to integrate your Postgres destination data into your data warehouse, lake or database

It’s never been easier to integrate any data to Postgres destination

Airbyte Open Source

Self-host the leading open-source data movement platform with the largest catalog of ELT connectors.
Deploy Airbyte Open Source

Airbyte Cloud

The easiest way to address all your ELT needs. Largest catalog of connectors, all customizable.
Try Airbyte Cloud free

Airbyte Enterprise

The best way to run Airbyte in self-hosted, with services and features that drive reliability, scalability, and compliance.
Learn more
TRUSTED BY 3,000+ COMPANIES DAILY

Why choose Airbyte as the backbone of your data infrastructure?

Keep your data engineering costs in check

Building and maintaining custom connectors have become 5x easier with Airbyte. Enable your data engineering teams to focus on projects that are more valuable to your business.
Leverage all the alpha and beta connectors for free on Airbyte Cloud with our Free Connector Program.

Get Airbyte hosted where you need it to be

Airbyte helps you deploy your pipelines in production with two deployment options for the data plane:
  • Airbyte Cloud: Have it hosted by us, with all the security you need (SOC2, ISO, GDPR, HIPAA Conduit).
  • Airbyte Enterprise: Have it hosted within your own infrastructure, so your data and secrets never leave it.

White-glove enterprise-level support

With an average response rate of 10 minutes or less and a Customer Satisfaction score of 96/100, our team is ready to support your data integration journey all over the world.

Including for your Airbyte Open Source instance with our premium support.

Get your Postgres destination data in whatever tools you need

Airbyte supports a growing list of destinations, including cloud data warehouses, lakes, and databases.

Get your Postgres destination data in whatever tools you need

Airbyte supports a growing list of destinations, including cloud data warehouses, lakes, and databases.

Sync your data from any sources to Postgres destination

Airbyte supports a growing list of sources, including API tools,  cloud data warehouses, lakes, databases, and files, or even custom sources you can build.

Case study
Consolidating data silos at Fnatic

Fnatic, based out of London, is the world's leading esports organization, with a winning legacy of 16 years and counting in over 28 different titles, generating over 13m USD in prize money. Fnatic has an engaged follower base of 14m across their social media platforms and hundreds of millions of people watch their teams compete in League of Legends, CS:GO, Dota 2, Rainbow Six Siege, and many more titles every year.

FAQs

What is ETL?

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.

What is Postgres destination?

An object-relational database management system, PostgreSQL is able to handle a wide range of workloads, supports multiple standards, and is cross-platform, running on numerous operating systems including Microsoft Windows, Solaris, Linux, and FreeBSD. It is highly extensible, and supports more than 12 procedural languages, Spatial data support, Gin and GIST Indexes, and more. Many web, mobile, and analytics applications use PostgreSQL as the primary data warehouse or data store.

What data can you extract from Postgres destination?

How do I transfer data from Postgres destination?

This can be done by building a data pipeline manually, usually a Python script (you can leverage a tool as Apache Airflow for this). This process can take more than a full week of development. Or it can be done in minutes on Airbyte in three easy steps: 
1. Set up Postgres destination as a source connector (using Auth, or usually an API key)
2. Choose a destination (more than 50 available destination databases, data warehouses or lakes) to sync data too and set it up as a destination connector
3. Define which data you want to transfer from Postgres destination and how frequently
You can choose to self-host the pipeline using Airbyte Open Source or have it managed for you with Airbyte Cloud. 

What are top ETL tools to extract data from Postgres destination

The most prominent ETL tools to extract data from Postgres destination include:
- Airbyte
- Fivetran
- StitchData
- Matillion
- Talend Data Integration
These ETL and ELT tools help in extracting data from Postgres destination and other sources (APIs, databases, and more), transforming it efficiently, and loading it into a database, data warehouse or data lake, enhancing data management capabilities.

What is ELT?

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.

Difference between ETL and ELT?

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.

What is ETL?

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.

What is Postgres destination?

An object-relational database management system, PostgreSQL is able to handle a wide range of workloads, supports multiple standards, and is cross-platform, running on numerous operating systems including Microsoft Windows, Solaris, Linux, and FreeBSD. It is highly extensible, and supports more than 12 procedural languages, Spatial data support, Gin and GIST Indexes, and more. Many web, mobile, and analytics applications use PostgreSQL as the primary data warehouse or data store.

What data can you extract from Postgres destination?

How do I transfer data from Postgres destination?

This can be done by building a data pipeline manually, usually a Python script (you can leverage a tool as Apache Airflow for this). This process can take more than a full week of development. Or it can be done in minutes on Airbyte in three easy steps: 
1. Set up Postgres destination as a source connector (using Auth, or usually an API key)
2. Choose a destination (more than 50 available destination databases, data warehouses or lakes) to sync data too and set it up as a destination connector
3. Define which data you want to transfer from Postgres destination and how frequently
You can choose to self-host the pipeline using Airbyte Open Source or have it managed for you with Airbyte Cloud. 

What are top ETL tools to extract data from Postgres destination

The most prominent ETL tools to extract data from Postgres destination include:
- Airbyte
- Fivetran
- StitchData
- Matillion
- Talend Data Integration
These ETL and ELT tools help in extracting data from Postgres destination and other sources (APIs, databases, and more), transforming it efficiently, and loading it into a database, data warehouse or data lake, enhancing data management capabilities.

What is ELT?

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.

Difference between ETL and ELT?

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.

What is ETL?

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.

What is Postgres destination?

An object-relational database management system, PostgreSQL is able to handle a wide range of workloads, supports multiple standards, and is cross-platform, running on numerous operating systems including Microsoft Windows, Solaris, Linux, and FreeBSD. It is highly extensible, and supports more than 12 procedural languages, Spatial data support, Gin and GIST Indexes, and more. Many web, mobile, and analytics applications use PostgreSQL as the primary data warehouse or data store.

What data can you extract from Postgres destination?

What data can you transfer to Postgres destination?

You can transfer a wide variety of data to Postgres destination. This usually includes structured, semi-structured, and unstructured data like transaction records, log files, JSON data, CSV files, and more, allowing robust, scalable data integration and analysis.

How do I transfer data to Postgres destination?

What are top ETL tools to transfer data from Postgres destination

The most prominent ETL tools to transfer data to Postgres destination 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 [tool] and other databases, data warehouses and data lakes, enhancing data management capabilities.

What is ELT?

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.

Difference between ETL and ELT?

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.