Moving data from HubSpot to Amazon Redshift sounds scary at first. It feels like moving a closet full of socks, receipts, and mystery cables into a giant warehouse. But with the right ETL tool, it becomes much easier. Your contacts, deals, companies, tickets, emails, and campaign data can flow into Redshift with less drama and fewer broken spreadsheets.
TLDR: The best ETL tool for HubSpot to Redshift depends on your team, budget, and data volume. Fivetran and Hevo are great for simple automation. Airbyte is strong if you want open source control. Matillion and AWS Glue are better for technical teams that need deep customization and scale.
Why Move HubSpot Data to Redshift?
HubSpot is great for marketing, sales, and customer work. It holds a lot of useful data. But it is not built to be your main analytics warehouse.
Amazon Redshift is different. It is built for big queries. It is built for dashboards. It is built for teams that want to slice data like a data ninja with a very sharp spreadsheet sword.
When HubSpot data lands in Redshift, you can join it with other data. Think product usage, billing, ads, support, and website events. Suddenly, you can answer better questions.
- Which campaigns create the best customers?
- Which sales reps close deals fastest?
- Which leads become high-value accounts?
- Which emails help deals move forward?
- Which customers are at risk of churn?
That is the magic. HubSpot gives you the puzzle pieces. Redshift gives you the big table where you can build the full picture.
What Makes a Good HubSpot to Redshift ETL Tool?
A good ETL tool should feel like a helpful robot. Not a robot that needs snacks every ten minutes. A good one just works.
Here are the main things to check:
- HubSpot connector quality: It should support contacts, companies, deals, owners, tickets, engagements, lists, forms, and custom objects.
- Redshift loading method: It should load data efficiently, often using S3 and Redshift COPY.
- Automation: It should sync on a schedule without manual button-clicking.
- Schema handling: It should handle new fields without panic.
- Error recovery: It should retry failed jobs and show clear logs.
- Scalability: It should support growing data volume.
- Pricing: It should not surprise you like a raccoon in a mailbox.
1. Fivetran
Best for: Teams that want a very hands-off, reliable pipeline.
Fivetran is one of the most popular ETL tools for SaaS data. It has a polished HubSpot connector and a strong Redshift destination. Setup is simple. You connect HubSpot. You connect Redshift. Then Fivetran starts syncing.
Its biggest strength is automation. Fivetran handles schema changes, API quirks, retries, and incremental syncs. If HubSpot adds a field, Fivetran can usually detect it and adjust. That is helpful because HubSpot data changes often.
Features:
- Managed HubSpot connector
- Automated schema migration
- Incremental syncs
- Reliable Redshift loading
- Monitoring and alerts
- Strong documentation
Automation: Excellent. Fivetran is built for “set it and breathe normally.”
Scalability: Very strong. It can handle large data volumes well. It is a good fit for growing teams and enterprise analytics.
Watch out: Pricing can rise as data volume grows. Fivetran charges based on monthly active rows. This is simple, but not always cheap.
2. Hevo Data
Best for: Teams that want fast setup, nice usability, and near real-time syncing.
Hevo is another strong no-code ETL tool. It is friendly. It has a clean interface. It supports HubSpot and Redshift well. For many teams, Hevo feels less intimidating than heavier data platforms.
Hevo is good when you want pipelines fast. It also has built-in transformations. That means you can clean or shape data before or after loading it. This is handy if your HubSpot fields look like they were named during a caffeine storm.
Features:
- No-code pipeline builder
- Prebuilt HubSpot connector
- Redshift destination support
- Real-time and scheduled sync options
- Basic transformations
- Error handling and replay
Automation: Very good. Hevo can keep data moving with little manual work.
Scalability: Good to strong. It works well for small and mid-sized teams. Larger teams should check pricing and performance at scale.
Watch out: Some advanced needs may require more setup. Always test custom HubSpot objects before full rollout.
3. Airbyte
Best for: Teams that like open source tools and want more control.
Airbyte is the fun tinkerer in the room. It has open source roots and many connectors. You can run it yourself, or use Airbyte Cloud. This gives teams flexibility.
Airbyte supports HubSpot as a source and Redshift as a destination. It can sync many HubSpot objects. It also lets technical teams customize connectors if needed. This is useful when your CRM setup is special. And let’s be honest. Most CRM setups are special. Like “why is this field called Final Final Lead Score 2” special.
Features:
- Open source option
- Cloud and self-hosted versions
- HubSpot source connector
- Redshift destination connector
- Custom connector framework
- Large connector catalog
Automation: Good. Airbyte supports scheduled syncs and monitoring. But self-hosted setups need operational care.
Scalability: Good, especially with the right infrastructure. Airbyte Cloud reduces maintenance. Self-hosting gives control, but also responsibility.
Watch out: You may need engineering help. Open source does not always mean “free forever.” You still pay with time, servers, and occasional debugging snacks.
4. Stitch
Best for: Smaller teams that want a simple ETL service.
Stitch is a lightweight ETL tool. It connects SaaS sources like HubSpot to warehouses like Redshift. It is easier than building your own pipeline. It is less complex than some enterprise tools.
Stitch is good for basic extraction and loading. It can sync HubSpot data on a schedule. It also tracks changes and handles common warehouse loading tasks.
Features:
- Simple setup
- HubSpot connector
- Redshift destination
- Scheduled syncs
- Basic monitoring
- ELT-style loading
Automation: Good for standard use cases. Less ideal for complex workflows.
Scalability: Fair to good. It can support growing teams, but many larger teams move to more advanced tools over time.
Watch out: It may feel limited if you need deeper transformations, complex orchestration, or strict enterprise controls.
5. Matillion
Best for: Data teams that want strong transformation inside a cloud data stack.
Matillion is more than a simple connector tool. It is a cloud ETL and ELT platform. It works well with warehouses like Redshift. It gives teams a visual way to build data jobs and transformations.
For HubSpot to Redshift, Matillion can help extract, load, and transform data. It is especially useful if your team wants to build data models after loading. For example, you can build sales pipeline tables, marketing attribution models, or customer health scores.
Features:
- Visual job builder
- Good Redshift integration
- Transformation workflows
- Scheduling and orchestration
- Reusable components
- Team-friendly development tools
Automation: Strong. You can schedule workflows and chain jobs together.
Scalability: Strong. Matillion is built for cloud warehouse workloads and larger data teams.
Watch out: It may be more tool than you need for a simple sync. It also needs more data engineering knowledge than plug-and-play tools.
6. AWS Glue
Best for: Technical teams already deep in AWS.
AWS Glue is Amazon’s serverless data integration service. It can move and transform data at scale. Since Redshift is also an AWS service, Glue can fit nicely into an AWS-heavy stack.
However, Glue is not as simple as tools like Fivetran or Hevo. You may need to work with custom scripts, jobs, crawlers, IAM roles, and connectors. That means more power. It also means more ways to say, “Why is this permission failing?”
Features:
- Serverless ETL jobs
- Strong AWS integration
- Custom Python and Spark jobs
- Data catalog support
- Scales for large workloads
- Flexible orchestration with AWS tools
Automation: Strong, but technical. You can schedule jobs and build workflows. Setup takes more skill.
Scalability: Excellent. Glue can handle serious workloads when configured well.
Watch out: HubSpot extraction may require extra connector work or custom development. This is best for engineering teams.
Quick Comparison
| Tool | Best For | Automation | Scalability | Ease |
|---|---|---|---|---|
| Fivetran | Managed pipelines | Excellent | Very strong | Very easy |
| Hevo | Fast no-code setup | Very good | Good to strong | Easy |
| Airbyte | Open source control | Good | Good | Medium |
| Stitch | Simple ETL | Good | Fair to good | Easy |
| Matillion | Transformations | Strong | Strong | Medium |
| AWS Glue | AWS engineering teams | Strong | Excellent | Technical |
What About Automation?
Automation is the whole point. Nobody wants to export CSV files from HubSpot every Monday. That is not a data strategy. That is a cry for help.
The best tools can:
- Run on a schedule
- Sync only new or changed records
- Handle HubSpot API limits
- Retry failed loads
- Send alerts when jobs break
- Update schemas when fields change
For the highest automation, choose Fivetran or Hevo. For automation with more control, choose Airbyte or Matillion. For custom AWS-native automation, choose AWS Glue.
What About Scalability?
Scalability means the tool will not melt when your data grows. Today you may have 50,000 contacts. Next year you may have 5 million activities, 800 custom fields, and a sales team that logs everything.
Image not found in postmetaRedshift can handle big data. But your ETL tool must feed it properly. Large syncs should use efficient batch loading. Incremental updates should be smart. Failed jobs should not require a full reload every time.
Fivetran, Matillion, and AWS Glue are strong choices for larger workloads. Airbyte can also scale well, especially if managed correctly. Hevo is a strong middle ground for fast-moving teams.
How to Choose the Right Tool
Here is the simple version.
- Choose Fivetran if you want the easiest managed option and can pay for convenience.
- Choose Hevo if you want no-code setup with good speed and usability.
- Choose Airbyte if you want open source flexibility and connector control.
- Choose Stitch if your needs are basic and your team is small.
- Choose Matillion if transformation logic is a big part of your workflow.
- Choose AWS Glue if your engineers live in AWS and want maximum control.
Final Thoughts
Moving HubSpot data to Redshift does not need to be painful. It just needs the right tool. The key is to match the tool to your team’s skills and your data goals.
If you want simple and reliable, start with Fivetran or Hevo. If you want flexibility, look at Airbyte. If you need serious transformation power, try Matillion. If you want AWS-native scale and have technical muscle, use AWS Glue.
Think of your ETL tool as the delivery truck for your data. HubSpot is the busy store. Redshift is the giant warehouse. Pick a truck that is fast, safe, and does not lose boxes on the highway. Your future dashboards will thank you.