Are you using the best Snowflake ETL (extract, transform, and load) tools to automate your data management and pipeline building? That’s a challenging question, because there’s rarely a hands-down best tool for any job. What’s most important is that you find the ones that work best for you and your team.
When it comes to choosing the best Snowflake ETL tools for your enterprise, start by assessing your existing data infrastructure and identifying challenges.
- Are you struggling to create complex workflows in a more graphic way?
- Are your non-engineering teams able to use ETL tools effectively?
- Can you automate data orchestration while employing excellent monitoring solutions for your ETL process?
- Is your Snowflake ETL tool secure and compliant?
At Shipyard we’ve been working with Snowflake ETL for a long time, so we decided to experiment with different tools to determine which ones are the most reliable for various companies’ ETL needs. Some tools have overlapping features, so we’ve identified key differentiators to help you match their capabilities with your requirements.
8 Snowflake ETL tools to consider
1. Shipyard
Shipyard's easy to use, fast to deploy, for data people of all technical backgrounds, and allows for no code, hybrid code, or your code. You're also not locked into Python. Plus, you can test and launch pipelines from your local environment.
This modern cloud-based data orchestration platform easily connects tools and automates workflows. Shipyard’s customizable workflow automation capabilities make it easy to build and optimize workflows for a variety of use cases. For instance, its open source low-code blueprints empower both your engineering and non-engineering teams to quickly customize data workflows and ETL data.
Shipyard’s integration with GitHub offers continuous version control, easy deployments, and up-to-date code. Shipyard also offers reliable monitoring with instant notifications to ensure that you can instantly identify and fix critical data pipeline issues before they impact your business. Its integration with dozens of data sources lets you extract, transform, and load data to your Snowflake warehouse in a matter of minutes.
Top use case:
Shipyard is built for those who are looking for data pipeline flexibility and scalability. It’s a mission-critical Snowflake ETL tool that keeps teams aligned with each other—while ensuring that they can seamlessly scale and customize their data pipelines. Combined with its list of integrations, super-easy data transformations, visual interface, and customer support, Shipyard is the only Snowflake data ETL tool you need for data orchestration.
Pros:
- Shipyard offers a quick setup and a simple and intuitive UI, making it easier for both experienced and new users to adopt the tool.
- It lets you build advanced workflow automations with its low-code templates and visual interface.
- It integrates with a variety of data sources, such as Fivetran, dbt Cloud, Airtable, Amazon S3, spreadsheets, and more.
- It offers robust reporting capabilities so you can track inefficiencies and update processes or make improvements instantly. For instance, it lets you gauge the status, timing, and resource usage of every workflow and job.
- Shipyard not only offers users accurate real-time notifications about critical breakages but also ensures that your data is handled in a secure manner with zero data loss.
- Shipyard lets you modify your data pipelines with new logic immediately, and scales well as your data load grows.
- With extensive documentation and Changelog, Shipyard offers a great knowledge base to help users understand the platform better.
- It also offers chat support and lets users schedule a call directly with the customer support team.
- API access to update/create workflows in bulk.
- You can export or store your logs externally.
- Native Credential Management.
Cons:
- There are no pre-built connectors for ingesting data from SaaS tools.
- Cannot self-host Shipyard on your own infrastructure.
Pricing:
- Shipyard offers a free plan—which is great for users who want to test out the platform’s capabilities before switching to it completely.
- Its basic paid plan is cost-efficient. As your organization grows and usage and use cases increase, the price varies.
2. Matillion
Matillion is a cloud-based ETL platform that moves data from over 70 data sources to data warehouses like Snowflake, Amazon Redshift, Google BigQuery, etc. It’s fairly easy to set up and has a UI for data engineers.
While it offers drag-and-drop capabilities in its visual workspaces, it requires SQL knowledge which limits its usability, especially for non-engineers who’d want to use it for domain-specific use cases.
Overall, Matillion ETL is well integrated with the Snowflake data warehouse, and scheduling orchestration creates workflows when resources are available.
Top use case:
Matilion is a good option for those who want to migrate and transform data from multiple data sources—including CRMs, ERPs, and social networks—into their data warehouse or data lake of choice.
Pros:
- Matilion provides connections for most cloud-based applications, so you don’t need to pay extra for any new connectors (which is the norm for many tools).
- Users accomplish data transformations using custom SQL or by creating transformation components using the GUI.
- It supports 70+ data sources that include databases, CRM platforms, ERPs, and more.
Cons:
- There are no pre-made templates available, so you have to start from scratch and build everything on your own, which is time-intensive.
- Live chat support is not available.
- Users cannot add a new data source or modify an existing one on their own.
Pricing:
- Data loader is free to use, whereas Matillion ETL comes with a 14-day free trial.
- Matillion ETL has three paid plans: Basic, Advanced, and Enterprise.
3. Fivetran
Fivetran is a popular ETL tool that replicates applications, databases, events, and files into high-performance cloud warehouses. Its ease of setup (connecting data sources with destinations) is what makes it one of the most intuitive Snowflake ETL tools.
Fivetran’s pipelines are automatically and continuously updated with fully managed connectors—letting you focus on analytics and leaving out the tedious, repetitive tasks in the ETL process.
Fivetran pulls data from 5,000 cloud applications and allows you to add new data sources quickly. It supports advanced data warehouses like Snowflake, Azure, Amazon Redshift, BigQuery, and Google Cloud, so you can query your data easily.
Features like real-time monitoring, connectors, alerts, and system logs further empower data analysts and data engineers to build ETL pipelines using Fivetran.
Top use case:
Fivetran is a good Snowflake data ETL tool for people who are just getting started with their ETL journey and looking for a tool that’s quick to set up and easy to use.
Pros:
- It has automated pipelines with standardized schemas.
- It offers access to all your data in SQL.
- It allows users to add new data sources by themselves.
Cons:
- There’s no option to use/deploy services on-premise.
- Its product documentation could be better.
- It can be a bit tricky to figure out the final cost of the platform.
Pricing:
- Fivetran offers a 14-day free trial for each of its paid plans.
- It has four paid pricing plans. You can also request for a custom quote if you’re an enterprise that needs access for unlimited users and usage.
- Fivetran also offers a free tier option.
4. Stitch
Stitch is a cloud-based ETL platform that helps ingest data from multiple SaaS applications and databases and move it into data warehouses and data lakes, where it’s analyzed using BI tools. It’s an easy to set up ETL tool with minimal requirements and efforts.
Stitch only does transformations required for compatibility with the destination, such as denesting data and translating data types (when needed). Transformations can be defined in Python, Java, SQL, or via graphical user interface.
Stitch offers connectors for more than 100 databases and SaaS integrations, including data warehouses, data sources, and data lake destinations. Plus, users have the flexibility to build and add new data sources to Stitch.
Top use case:
Stitch is very straightforward, making it a solid option. Users manage their ETL system from their UI easily. With Stitch’s broad range of integrations, it makes for a suitable ETL tool for enterprises that need to ingest data from multiple sources.
Pros:
- Stitch is an easy-to-use tool that sets up quickly by non-technical teams.
- Its scheduling feature helps load the tables on predefined time.
- It allows users to add new data sources by themselves.
Cons:
- It lacks data transformation options.
- Handling large datasets can be tricky and may impact the performance.
- It has no option to use/deploy services on-premise.
Pricing:
- Stitch offers a 14-day free trial and custom paid plans depending on scale.
5. Integrate.io
Integrate.io positions itself as a data warehouse integration platform built for e-commerce enterprises. With a native Snowflake connector, Integrate.io supports over 200+ data sources. It offers no-code solutions and allows data engineers and data analysts to deploy custom transformation jobs (based on multiple data sources).
Integrate.io comes with an intuitive UI, plenty of built-in functions, and a visual editor that makes creating a package faster. While it’s great for SQL transformations, it can be slightly challenging to transform JSON or other nested data.
Top use case:
Integrate.io is the preferred Snowflake ETL choice for e-commerce organizations with many incoming data sources and analytics-heavy decision-making.
Pros:
- Integrate.io offers a native Snowflake connector.
- It comes with a simple drag-and-drop interface, making it easy for non-engineers to use the platform for data transformations.
- It integrates well with dozens of platforms, databases, apps, and data warehouses, including: AWS, Microsoft Azure, Oracle, Salesforce, Amazon Redshift, Tableau, etc.
Cons:
- Debugging can be slightly time-consuming - you need to sift through the error log to identify the root issue.
Pricing:
- You need to schedule a demo by Calendly to get a custom pricing plan based on your needs.
6. Apache Airflow
Apache Airflow is a popular open-source Snowflake ETL tool. It lets you monitor, schedule, and manage your workflows using a web application.
The core concept of Apache airflow is a DAG (Directed Acyclic Graph) where you need to arrange tasks that have upstream and downstream dependencies set between them that define the logical flow of how they should run. DAG visualizations and task trees allow you to see how your DAG is functioning.
Airflow pipelines are defined in Python, which means users need to use standard Python features to create workflows and dynamically generate tasks. As a seasoned data engineer, this is great news since Python allows users to maintain full flexibility when building workflows.
Top use case:
Apache Airflow is a good option for data engineers who frequently work on creating pipelines.
Pros:
- Apache Airflow comes with excellent functionality for building complex pipelines.
- It offers extensive support via Slack.
Cons:
- Apache Airflow doesn’t have the most user-friendly UI and can be clunky at times.
- It requires knowledge of Python.
- Modifying pipelines is difficult once they have been created.
- It contains intensive documentation that needs to be carefully read and reviewed to ensure your configuration works as per your needs.
Pricing:
- Apache Airflow ETL is an open-source platform, licensed under Apache License Version 2.0.
7. StreamSets
SteamSets is a cloud-first, fully managed ETL tool used to build enhanced data ingestion pipelines that deliver continuous data needed for analytics. It provides powerful pre-made connectors for ingesting data.
You can also process real-time data to make it available to downstream applications in a specific format, and even set a monitoring layer. Plus, inbuilt parsers make it easy to parse big and complex payloads with key-value pairs (KVPs), JSON, and XML.
Top use case:
StreamSets is a great Snowflake data ETL product for enterprises and data engineers working with a high volume of file streaming or data input sources.
Pros:
- StreamSets has an intuitive UX that facilitates open-source design for PoC (Proof of Concept) and adaptability. It’s modular to plug into your architecture whenever required.
- It provides a drag-and-drop GUI to perform data transformations such as add, remove, lookup, typecast, etc. before loading the data into warehouses (or any destination).
- It supports 50+ data sources including database and streaming sources like MapR and Kafka.
Cons:
- The new version needs users to purchase addition components (Control Hub) which requires addition 16 databases to manage, patch, and upgrade - this adds more complexity to the platform.
- Logging/error messaging can be hard to sift through to diagnose issues.
- It doesn’t offer live customer chat support.
Pricing:
- StreamSets offers a 30-day free trial.
- It offers three pricing plans: Free, Professional, and Enterprise.
8. Etleap
Etleap is a popular Snowflake ETL tool that builds and manages data pipelines to transform data to Snowflake and Amazon Redshift.
One of the key differentiators of this Snowflake data ETL tool is that it offers the ability to connect to multiple databases/sources of the same type within the licensed connector, which makes it easy for users. It can ingest data from different sources like enterprise databases, log files, sensors, message queries, simple file storage, ERP systems, and more.
Etleap also has an intuitive GUI that adds or modifies new data sources with a single click and applies custom transformations.
Top use case:
Etleap offers simplicity and powerful features to data engineers, allowing them to gather information from multiple data sources and put them into stages. From there, they can use mockups to create final analytical models.
Pros:
- Etleap allows data transformations through GUI as well as custom SQL. Users can easily orchestrate and schedule data pipelines.
- Building connectors is easy with Etleap since you don’t need to familiarize yourself with coding.
- It supports 50+ data sources including SaaS, databases, files, BI tools, and event streams.
Cons:
- Users cannot add or modify data sources on their own.
- Etleap lacks extensive documentation or a resource hub for users to familiarize themselves with the platform.
Pricing:
- Etleap offers a 30-day free trial after a demo with the sales team.
- There are no pricing options available on the company website. You have to get in touch with the team or request a demo to learn more.
Final thoughts
There are many different options for Snowflake ETL tools available in the market. The sheer number of choices makes it challenging and even overwhelming to select the right tool for you. That’s why we recommend you keep things simple.
If you’re looking for an easy-to-use and powerful Snowflake data ETL tool that streamlines your data ETL processes, you can consider using Shipyard.
On the other hand, if you’re just getting started and need a simple ETL tool, Fivetran is a good option. Just keep in mind that it may feel restrictive as the needs of your data pipeline needs grow.
If you have questions about ETL tools or data pipelines, reach out to our team. We’ll help you identify exactly what you need.
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