If you're evaluating the top ETL tools to use with Snowflake, we've got you covered.
Every data-driven business needs the right data orchestration stack, and Snowflake is one of the most popular destinations today.
But you won't be able to get the most out of Snowflake without a proper ETL tool.
Today we'll look at the top ETL choices for Snowflake, as well as their use cases so you can pick what's best for your data needs.
If you've decided on Snowflake data cloud to live at the center of your modern data stack, the next step is choosing an ETL tool---and not all are created equal.
Here are the most important features to look for in a Snowflake ETL tool.
The best ETL tool is one that has connectors for every data source you need. More isn't always better---look for a data integration tool that supports your mission-critical apps and database formats, even if they offer fewer connectors overall.
As your needs grow, you'll probably expand to new data sources. How easy will it be to get connectors for these sources? Can you count on the platform to build them for you, or will you need to develop them yourself?
Make sure you choose a tool that's been optimized for Snowflake specifically. Tools built with Snowflake in mind have better performance, work faster, and can result in lower fees.
Most tools have a tradeoff between power and ease of use. Do you have a technically proficient data engineering team, happy to manually code each data transformation in Python? Or do you prefer a no-code tool with a drag-and-drop interface that works from day one, albeit for less complex workflows?
How much help will you get working with the tool? If something breaks, how fast will the team respond (if at all)? Keep in mind that some tools charge extra for premium support, which you should calculate into your budget.
You'll need a tool that fits your budget now and as you grow. Most tools use one of two pricing models: consumption-based and per data flow. Consumption-based can be hard to predict month-to-month and gets expensive with more complex data. Data flow pricing is predictable. You can also choose an open-source tool that's free if you host it yourself.
Portable is the best Snowflake ETL tool for long-tail data sources. It has connectors for 300+ apps you won't find with the bigger competitors.
Portable also develops custom connectors at no extra cost and has lightning-fast turnaround times---request a connector, and you'll get it in a few days or even hours. Maintenance is included, so your connector will still work even if the API changes.
Plus, Portable handles all monitoring, alerting, and troubleshooting so you can rest easy.
Portable offers a free plan for manual data workflows with no caps on volume, connectors, or destinations.
For automated data flows, Portable charges a flat fee of $200/month.
For enterprise requirements and SLAs, contact sales.
Huge catalog of long-tail data connectors ready to use out-of-the-box.
Custom data source connectors developed upon request at no extra cost, with maintenance included.
Hands-on support available 24/7.
Portable doesn't have connectors for common enterprise data sources you'll find with every other tool, like Oracle and Salesforce.
Data lakes not supported.
Only available to customers based in the U.S.
Portable is best for data teams with long-tail sources who want to spend time gathering data analytics insights, not developing and maintaining ETL pipelines.
Apache Airflow is an open-source ETL tool for Snowflake and other cloud data warehouses. It's a comprehensive tool that gives you complete control over your data with Python.
150+ data source connectors.
Robust Python integrations that can create even highly complex workflows.
Very extensible for users with technical knowledge.
Monitoring, scheduling, and management all built into a single platform.
Very technical with extensive user setup required.
Knowledge of Python is mandatory for creating data pipelines in Airflow.
Teams with a high level of technical expertise that want an advanced open-source platform they can host and manage themselves.
Stitch is a Snowflake ETL tool that's part of the Talend ecosystem.
It handles data extraction, and the basic transformations required to import to your destination.
You can set up integrations with Python, Java, SQL, or using the built-in GUI.
Standard plan starting at $100/month for up to 5 million active rows per month, one destination, and 10 sources (limited to "Standard" sources)
Advanced plan at $1,250/month for up to 100 million rows and three destinations
Premium plan at $2,500/month for up to 1 billion rows and five destinations
14-day free trial available
130+ data sources supported.
Easy-to-use platform with a graphical user interface.
Automation tools including monitoring and alerts.
Integration with Talend suite of business intelligence tools.
Very limited data transformation options.
No on-premise deployment options.
Limited destinations with a maximum of one, three, and five depending on the tiers.
Stitch is best for teams that use the most common data sources and are looking for a no-code tool for basic data ingestion.
Matillion is one of the most popular Snowflake data warehouse tools. It consists of two tools: Matillion Data Loader and Matillion ETL. (Despite the name, Matillion ETL uses an ELT pipeline.)
Credit-based pricing that varies from month-to-month
Free: Up to one million rows/month
110+ data source connectors.
On-premise and cloud-based solutions available.
Robust built-in tools for data transformation and data orchestration.
Easier data governance since the Data Loader and ELT tools are part of the same platform.
No options for users to connect new data sources or adjust Matillion's built-in connectors.
Harder to integrate third-party tools into your data stack.
Matillion is best for organizations looking for an all-in-one data tool, especially a tool that offers on-premise deployments.
Blendo is a data management tool that's now part of Rudderstack. It's designed to make data integration as easy as possible and has a fast setup process and automation scripts to eliminate manual work.
Free plan limited to three sources
Pro plan starts at $750/month and includes transformations
Enterprise plans available with custom pricing
45+ data source connectors.
No-code platform with an intuitive interface.
Monitoring and alert features built-in.
Relatively small number of data connectors compared to other Snowflake ETL tools.
Limited capabilities for data transformations.
Users can't create new data sources on their own.
Data teams with a small number of sources and no transformation needs looking for an easy-to-use platform.
There are dozens of ETL tools compatible with Snowflake data warehouse. Here are a few additional tools that we didn't feature, but might be a good fit for your organization's needs.
Fivetran is one of the industry leaders and supports 160+ data sources. It's best for enterprise-level teams who need a robust, best-in-class platform and have a budget to match.
If you need a Fivetran custom connector that isn't available, Portable will build one for you.
Hevo Data is a no-code platform that supports ETL, ELT, and Reverse ETL workflows. It has 150+ data connectors and offers real-time data migration, replication, and built-in transformations.
Airbyte is an open-source data platform with 170+ data connectors. It supports change data capture and warehouse-native transformations and lets users develop custom connections with its CDK.
Integrate is a no-code platform that comes with templates for faster integrations. It supports 200+ data sources, especially those in eCommerce.
Snowflake is a SaaS data warehouse tool, not an ETL tool.
You can store and manage data within Snowflake, but you'll need a separate tool for the ETL (extract, transform, load) process itself.
ETL is the modern replacement for traditional ELT (extract, load, transform) workflows.
Cloud data warehouses like Snowflake provide data engineering teams with near-infinite capacity.
Instead of transforming data with on-premise systems, today it's easier and cheaper to load data into a warehouse and then transform it using cloud-based tools.
Snowflake is used as cloud-based storage for big data and supports both ETL and ELT data pipelines. But it has plenty of competitors, including Google BigQuery, Microsoft Azure, Amazon Redshift (and other AWS platforms), to name a few.
Snowflake uses a consumption-based pricing model where you'll only pay for what you use.
Rates vary depending on server location, job type, and other variables.
Four plans available: Standard, Enterprise, Business Critical, and Virtual Private Snowflake.
Decoupled architecture, meaning its three parts---storage, compute, and cloud services---are separated, letting you several processes at once on the same set of data without wait times.
Machine learning optimizations to find more efficient ways to handle ETL processes, meaning datasets load faster and more efficiently at a lower cost.
Unique SQL commands like UNDROP (to restore tables quickly) and CLONE (to duplicate without the cost or delay of copying).
Cloud-agnostic and supports Amazon Web Services, Google Cloud Platform, and Microsoft Azure.
Large data marketplace with hundreds of third-party apps.
Support for JSON functions within SQL.
Support for several types of encryption, including end-to-end and client side.
Detailed and thorough documentation.
Bulk data migration can be limited by Snowflake's daily loading limits.
Billing structure allows for unlimited use of services, which can result in unexpected charges at the end of the month.
Snowflake is best for teams that want flexibility between cloud services and don't want to be tied down to a single ecosystem like AWS, Google Cloud, or Microsoft Azure. It's also a good fit for engineering-first teams, with its unique SQL commands and complete documentation.
Whatever your data warehousing plans, you'll benefit from a data integration tool that fits your needs.
Look for a platform that's integrated with Snowflake and offers data sources and features aligned with your data needs---now and in the future.
Your data team should spend its time gathering insights, not dealing with data management housekeeping. Portable helps you leverage your mission-critical data sources by building custom connectors that just work.