Best PostgreSQL ETL Tools: Pros, Cons, Features, Pricing

For data teams looking for an open-source, on-premises data warehouse platform, PostgreSQL is a popular choice.

Commonly referred to as Postgres, PostgreSQL is a dependable relational database with distinctive features for data engineers.

However, you'll need an ETL tool to migrate data into a PostgreSQL data warehouse.

We'll review the best ETL tools for each use case today, so you can pick the one that works best for your organization.

Using ETL With PostgreSQL

• PostgreSQL is an open-source, online transaction processing (OLTP) database platform.

• Unlike an OLAP database, which is best for frequent reads, PostgreSQL databases are best for frequent writes, such as real-time eCommerce transactions.

• You can use PostgreSQL as a data warehouse, which provides some distinct advantages over other platforms.

• Since Postgres is open-source, it's also free to use. It works with major cloud providers and on-premises with macOS, Microsoft Windows, Linux, BSD, and Solaris.

• To move data between sources (CSV, JSON, XML, etc.) and PostgreSQL, you would use an Extract, Transform, and Load (ETL) tool to move data into and out of the PostgreSQL data warehouse. You can even sync data from Postgres to Snowflake, or other data warehouses.

• Most ETL tools have Postgres integrations; many can work on-premises and in the cloud.

Why PostgreSQL Is a Smart Choice for ETL

Postgres has stayed relevant in the age of big data as a tool for on-premises data warehousing, despite major competition from cloud platforms like Snowflake, Amazon Redshift, and Google BigQuery.

But Postgres sets itself apart from those managed warehouses in several ways. It's open-source and can run in the cloud or on-premises. It also uses an OLTP, a row-oriented database.

Developers prefer PostgreSQL due to its compatibility and support of multiple programming languages (e.g., Python, Javascript, etc.), allowing them to perform database functions without conflicts.

PostgreSQL supports various data types, including JSON and XML, which are helpful for data transformation from multiple sources. It also has built-in high-availability features, essential for loading data into a reliable, fault-tolerant database.

Pricing

Postgres is open-source and completely free to run. The only costs are the architecture you use, which can range in price from servers you own to space on a cloud platform.

Key features

• A mature transactional system to ensure data integrity and consistency

• Open-source licensing lets anyone, even enterprises, use, copy, and modify the software freely.

• Accessible through the command line and third-party GUI tools.

• Robust support for SQL and NoSQL allows developers to store and query structured and unstructured data.

• Extensible custom functions and data types enable developers to create data structures to suit their needs.

• Scalability and performance ensure that PostgreSQL can handle large datasets and high concurrency.

Pros and Cons of PostgreSQL

PostgreSQL Advantages	PostgreSQL Disadvantages
Infrastructure-agnostic and available through all major cloud providers, including Google Cloud, Microsoft Azure, Amazon Web Services, and all major on-premise platforms.	Less ideal for frequent querying of large datasets. These processes are better suited to a column-oriented OLAP database.
Open-source database that's completely free. The only cost is the infrastructure you use to host it.	Scaling Postgres can be a challenge since the user needs to increase the available memory of the database manually, unlike MySQL.
Object-relational database architecture offers superior support for advanced data types, making PostgreSQL better than Redshift or SQL Server for handling pipelines with more complex raw data.	Security depends on your infrastructure, so there's more responsibility and work than through a cloud data warehouse.
Unique schema system for defining metadata like access control and data types within a database.

Who is Postgres best suited for?

PostgreSQL is the best option for teams that want an open-source database, infrastructure-agnostic data warehouse built for frequent transaction processing. Teams that want complete control over their data storage and have the resources and technical know-how to maintain their infrastructure will benefit most from Postgres.

How to Choose a PostgreSQL ETL Tool

You'll need a tool to manage the ETL process to extract data, clean and transform it, and load it into PostgreSQL.

You can then use PostgreSQL data for visualization, business intelligence, and more.

But here's what to consider when looking for the right Postgres ETL tool.

Data integrations

You won't get much use from a data integration tool that won't integrate your most important data sources. Choose a tool that can ingest data from all the apps you need.

Extensibility

Chances are, no single platform supports all the sources you need now and in the future. Choose a tool that lets you create new connectors or will make them for you.

Optimized for Postgres

Nearly every ETL provider supports Postgres, but mainly as a data source. Ensure your ETL solution integrates with Postgres as a data source to extract data and load data.

Customer Support

If something goes wrong, you need hands-on help to fix it. Make sure you choose a PostgreSQL ETL tool with quality support. And remember that many data integrations force you to upgrade for personalized assistance. Remember that most open-source ETL tools only offer self-service documentation or a Github repo for support.

Pricing

Most ETL integration tools use one of two pricing models: by consumption or per data pipeline. Choose one that works for your budget, and remember that consumption-based models can vary wildly in cost from one month to the next.

Top 5 Postgres ETL tools

1. Portable
2. Stitch
3. Fivetran
4. Blendo
5. Airbyte

1. Portable

Portable is the best PostgreSQL ETL tool for teams with long-tail data sources. It has built-in connectors for 500+ data sources and adds more regularly.

Even better, the Portable team develops new data connectors upon request, with turnarounds in a few hours. And they maintain those connectors if APIs change or datasets are no longer supported.

You won't need a tutorial or a lengthy onboarding. It's powerful enough for enterprise data engineers and easy enough for non-developers to manage.

Pricing

• Free: Portable offers a free plan for manual data workflows without limits on volume, connectors, or destinations.

• Automated data flows: $200 per month per data flow

• For enterprise requirements and SLAs, contact sales.

Key features

• 500+ built-in connectors for data sources you won't find with most other ETL tools.

• Development and maintenance of custom connectors at no cost.

• Premium support is included with all plans.

• Examples of its cloud data integrations include Amplitude, Calendly, and Chameleon.

Disadvantages

• Portable focuses on long-tail cloud-based API connectors and doesn't support enterprise applications like Oracle or on-premises flat files.

• Only available to users in the U.S.

Who is Portable best suited for?

Portable is best for data analytics teams that don't want to write PostgreSQL connectors for each data source and want a reliable solution that just works.

2. Stitch

Stitch is an ETL application that's part of the Talend ecosystem. It supports data transformations with Python, Java, SQL, or its drag-and-drop GUI.

Pricing

• Standard: Starts at $100/month for up to 5 million active rows per month, one destination, and 10 sources (limited to "Standard" sources).

• Advanced: Starts at $1,250/month for up to 100 million rows and three destinations.

• Premium: Starts at $2,500/month for up to 1 billion rows and five destinations.

• A 14-day free trial is available.

Key features

• Support for over 130 data sources.

• Built-in integrations with the Talend suite of data tools

• compatible with scripted and GUI-based data transformations.

• Automation for monitoring and notifications

Disadvantages

• Complex data transformations are less well supported than on some other platforms.

• On-premise deployments are not available.

• Limits on the number of data sources and destinations

Who is Stitch best suited for?

Stitch is best for teams using widely used data sources and looking for a tool with basic transformation support.

3. Fivetran

Fivetran is a popular ETL tool with more than 160 supported data sources.

It can load data into PostgreSQL databases hosted locally and on Amazon RDS, Amazon Aurora, Google Cloud, and Microsoft Azure.

Curious how it compares to Portable? Compare them right here.

Pricing

• Standard Select: Est. $60/month (limited to 1 user and 500k monthly active rows)

• Starter: Est. $120/month (limited to 10 users)

• Standard: Est. $180/month

• Enterprise: Est. $240/month

• Business critical: Contact sales

• A 14-day free trial is available.

Key features

• Native warehouse transformations that work well even with complex data

• Support for Change Data Capture (CDC) for data replication jobs

• Real-time or near-real-time data synchronization.

Disadvantages

• Higher-priced tool than many competitors.

• Consumption-based pricing models can be hard to predict month-to-month.

• Only supports ELT workloads, not ETL.

Who is Fivetran best suited for?

Fivetran is best for large businesses looking for a solution that supports the most popular enterprise platforms.

4. Blendo

Blendo is a data integration tool with several automations to speed up the creation of ETL pipelines. It has scripts and predefined data models.

Pricing

• Starter: $150/month for three data pipelines with a data volume of 15M rows

• Grow: $300/mo for up to 10 data pipelines with a data volume of 30M rows

• Scale: $500/mo for up to 150 data pipelines with a data volume of 200M rows, subject to a fair-use policy.

Key features

• Supports 45+ cloud data sources.

• Intended for developers to analyze event streams

• Built-in monitoring and alert features.

Disadvantages

• Not as many data connectors as other PostgreSQL ETL tools.

• Limited data transformation functionality.

• Teams can't create new data connectors on their own.

Who is Blendo best suited for?

Blendo's ETL service is ideal for data teams with a small number of sources with minimal transformation needs are looking for a simpler platform.

5. Airbyte

Airbyte is an ETL platform that supports Postgres as both a data source and a destination.

You can deploy Airbyte's open-source version or use its paid cloud plan.

Curious how Airbyte stacks up against Portable? Compare them right here.

Pricing

• Open source: Free to use since you host the software yourself.

• Cloud: $2.50/credit (one million rows = 6 credits; 1 GB = 4 credits)

• Cloud high volume: custom pricing (for 5,000+ credits)

Key features

• Support for 170+ data connectors (not all connectors are available on the cloud plan).

• Large open-source community.

• Warehouse-native data transformations

Disadvantages

• Consumption-based pricing model, which can be hard to predict from one month to the next.

• The cloud plan is missing some data integrations.

Who is Airbyte best suited for?

Airbyte is best for data engineering teams with the technical ability to develop and maintain additional connectors using the Airbyte CDK.

Runner-up ETL tools for PostgreSQL

Nearly every cloud ETL tool will let you export data from Postgres databases, but not all will help you import it. Here are a few of our runner-up choices for loading data into PostgreSQL.

Pentaho Data Integration

Pentaho is a platform owned by Hitachi Vantara that lets you import data into Postgres. It can perform data integration, transformation, and analysis using a drag-and-drop interface and a set of plugins. It can connect to PostgreSQL and other databases using JDBC or native drivers.

Integrate.io

Integrate is a no-code platform that supports 200+ data sources. It has pre-built templates to speed up the creation of new data flows. It aims to provide bidirectional ETL operations between PostgreSQL and other data endpoints.

Hevo

Hevo is a no-code ETL tool that supports 150+ data sources and ETL, ELT, and reverse ETL workflows. It supports real-time data loading, replication, and transformation.

Apache Spark

Apache Spark is a unified analytics engine for large-scale data processing that can work on batch and real-time analytics. Apache Spark can connect to PostgreSQL using a JDBC connector and perform various operations on the data, such as SQL queries, data transformation, machine learning, and graph analysis.

Streamline ETL Operations With PostgreSQL

As popular as cloud-based data warehouses are, Postgres might be the best solution if you're looking for a reliable database platform that gives you complete control with an on-premise deployment.

But you'll only get the most use from Postgres with a powerful ETL tool.

Most tools focus on major enterprise applications and won't pull in critical data from your long-tail data sources.

Portable streamlines ETL functions for data analytics teams so they can focus on surfacing actionable business intelligence --- not writing custom data transformation scripts.

Sync your business apps to PostgreSQL today with Portable. It's free to sync data manually. Ready to automate? It's just $200/mo for scheduled data syncs.