Top 10 ETL Tools for Klaviyo Integration in 2025

If you use Klaviyo, you already know how much customer data it captures, such as opens, clicks, purchases, email journeys, and more. But what happens when you want to combine that with your Shopify orders, Meta ad spend, or subscription data from Recharge? 

That’s where most teams hit a wall. Klaviyo does a great job at engagement tracking, but it doesn’t connect easily with the rest of your stack. You can see what a customer clicked, but not how much they spent, or whether the order was part of a subscription. And if you’re running campaigns across different channels, your reporting is scattered. 

This is why ETL tools for Klaviyo matter. These tools help you pull your raw Klaviyo data like flows, events, and profile updates into your data warehouse, where it can be combined with everything else. Instead of checking five different tools to get a full picture, you get one clean, reliable dataset. 

By the way, Klaviyo processes over 11 billion messages every month. If you don’t have a proper Klaviyo ETL pipeline in place, it’s easy to lose track of what is actually working. Most brands only scratch the surface with standard Klaviyo reports. That’s a missed opportunity.

What is ETL?

ETL stands for Extract, Transform, and Load. It’s a way to move data from one system to another. Here’s how it works: 

• Extract – You pull data from a source like Klaviyo. 

• Transform – You clean and reshape the data so it’s usable. 

• Load – You move it into your data warehouse. 

For example, let’s say you want to analyze flow performance. You might extract event data from Klaviyo, filter out internal tests, and convert timestamps into readable formats. Then you load that into BigQuery and build your reports on top of it. 

This process is tried and tested, especially in older data setups. But it requires you to do the transformation before anything gets into the warehouse. That’s where it can slow you down.

What is ELT?

ELT flips the order - Extract, Load, and Transform. You send the raw data to the warehouse first, then clean and organize it inside the warehouse. So instead of shaping the data beforehand, you get it into Snowflake or Redshift as it is and then use SQL or tools like dbt to do the rest. 

Why do teams prefer ELT now? 

• It’s easier to change logic later. 

• You don’t need extra infrastructure for transformation. 

• Analysts can work directly with raw data. 

• Historical data stays untouched and reusable. 

Say you load all your Klaviyo events into BigQuery. You can then build views that strip out bot clicks, flag re-engagement flows, or calculate revenue by campaign, without ever going back to re-pulling the data. 

That’s a big deal when your marketing logic changes every quarter.

What is an ETL Tool for Klaviyo?

An ETL tool for Klaviyo helps you move data from Klaviyo into your data warehouse automatically, without code. 

Klaviyo’s export options are limited. And while its API is flexible, building your own integration takes time. Maintaining it takes even more time. A proper ETL tool handles the whole process: 

• It connects to Klaviyo using your API credentials. 

• It pulls the right data, handles paging, and deals with rate limits. 

• It loads that data into your warehouse, either on a schedule or in near real-time. 

Some tools also help clean and structure the data for you. Others let you do that part in SQL. Either way, the end result is the same: you stop guessing what’s working. Instead, you start making decisions based on numbers.

Related Read: Best ETL Tools

Why You Need an ETL Tool for Klaviyo

Before we go into how to choose an ETL tool, let’s walk through a few real reasons brands seek Klaviyo ETL. 

1. Get everything in one place 

Customers don’t live in one tool. Their activity is spread across Klaviyo, Shopify, Google Ads, Meta, and maybe Recharge or Gorgias. If you’re pulling reports from each one, you’re not seeing the full picture. An ETL tool brings it all together. 

Now, instead of comparing numbers manually, you can run one query and see how email campaigns influence orders, or how SMS flows affect subscription retention. 

2. Go deeper with your analysis 

Klaviyo gives you opens, clicks, and attributed revenue. But what if you want to analyze customer lifetime value by campaign? Or look at how many people churned after getting a certain flow? 

Those answers don’t live inside Klaviyo. You need clean, structured data that connects across tools. With that, you can build retention models, cohort reports, and all the deeper metrics that drive growth. 

3. Free up your engineers 

If you’re running your own Klaviyo integration, your engineers are probably spending hours maintaining it. Every time the API changes, something breaks. Every time marketing wants a new field, someone needs to update the logic. 

An ETL tool removes these challenges. The sync just works; and if something fails, support teams are there to fix it. 

4. Make decisions faster 

If your data only updates once a day, you’re always reacting late. But with near real-time syncs, you can see what’s happening within minutes. If a flow is underperforming or a segment is broken, you don’t have to wait until the next day to fix it. 

5. Stay compliant 

In some industries, you’re required to keep communication records for years. Klaviyo doesn’t store everything forever. But with a proper data pipeline, you own the data and can store it however long you need.

Must have features for Klaviyo ETL Tool

If you’re exploring tools that can connect Klaviyo to your warehouse, don’t just pick the first one that claims to “support Klaviyo.” Some tools barely scratch the surface. They might sync a few tables but miss key metrics or fail when volumes increase. 

Before we compare the top ETL tools for Klaviyo, here’s a clear breakdown of features that matter: 

1. Native Klaviyo Connector 

This might seem obvious, but it’s worth checking. A native connector doesn’t just mean “we support Klaviyo”; rather, it means the tool understands the Klaviyo API well enough to pull important tables like Events, Campaigns, Flows, Profiles, Segments, and Lists, and do it in a structured way. It also handles tricky things like pagination and updates automatically. 

2. No-Code or Low-Code Setup 

Not every eCommerce company has engineers available for integration work. A good ETL tool should let your team (whether they’re in marketing, ops, or BI) set up the Klaviyo pipeline without needing to write scripts or mess with config files. At the very least, the setup should be clean and not take more than an hour. 

3. Near Real-Time Sync 

It’s true that daily syncs are often too slow. You don’t want to find out tomorrow that your campaign has been underperforming in the last few days. Hence, you should look for tools that offer syncs every 5–15 minutes or give you the flexibility to set the frequency based on what your team needs. 

4. Warehouse Compatibility 

Next, you need to make sure the tool supports your warehouse. BigQuery, Snowflake, and Redshift are the common ones; but if you use something else (like Databricks or Azure Synapse), verify that before committing. Also, check if the tool supports multiple destinations in case you scale in the future. 

5. Transformation Support 

Some tools are good for just moving data. Others let you clean and prepare it. If you don’t have a data team, built-in transformations can save you a ton of time. You should look for things like column mapping, timestamp formatting, or even simple logic (e.g., filter out unsubscribed contacts or remove bot opens). 

6. Security and Compliance 

This aspect includes things like encryption, SOC 2 certification, access control, and the ability to deploy in your own cloud if needed. As you’re moving customer data, security is of paramount importance. 

7. Pricing Transparency 

Some tools charge based on monthly active rows (MAR), which can get expensive fast, especially with Klaviyo’s high-volume event data. Others offer flat pricing or tiered rates that are easier to understand. Know how pricing scales as your business grows. 

8. Support That’s Actually Helpful 

If your data stops syncing during a big sale, you would want to talk to a person. You would prefer not to wait 48 hours for an email reply. So, you should look for vendors that offer real-time chat, quick ticket responses, and dedicated success teams if possible.

Top 10 ETL Tools for Klaviyo Integration (2025) 

Here’s a side-by-side look at the tools worth considering. This table gives you a quick view of how they stack up across key criteria:

10 Best ETL Tools for Klaviyo Integration (Detailed Breakdown) 

1. Saras Daton 

Saras Daton is a no-code ETL platform purpose-built for eCommerce and DTC brands. Unlike generic ETL tools that require workarounds to make Klaviyo integrations usable, Daton offers a native Klaviyo connector designed around real campaign use cases, like revenue attribution by flow, cohort tracking, and join-ready models with Shopify, Meta Ads, and Recharge. It’s focused on fast setup, efficient syncs, and built-in ecommerce logic that most other platforms overlook. 

Saras Daton is for: Brands that want to unify their marketing and order data across Shopify, Klaviyo, Google Ads, Meta, Recharge, and other key tools, without engineering bottlenecks. It is ideal for teams that want to go live in a day, and not for months. 

Key Features of Saras Daton: 

• True native connector for Klaviyo (supports all core tables, including events, flows, segments, and list memberships) 

• Pre-modeled transformations for ecommerce use cases (e.g., remove recurring orders from attributed revenue, normalize currency across orders) 

• Near real-time syncs (as fast as 5 minutes) 

• Support for BigQuery, Snowflake, Redshift, and more 

• Templates that join Klaviyo events to Shopify orders out of the box 

• SOC 2 compliant, with optional VPC deployment 

• Simple, row-based pricing (no MAR) 

• Setup takes less than 30 minutes with no engineering required 

Pros: 

• Designed specifically for eCommerce, not just compatible with it 

• Ensures 100 percent accuracy in transferring the data from Klaviyo to your warehouse 

• Built-in logic to remove test events, calculate true send timestamps, and group campaign metrics by customer 

• Friendly to both analysts and marketers 

• Fast support with dedicated success team 

• Pricing scales based on rows, not data size or API volume 

Cons: 

• Not suitable for legacy on-prem SQL systems like Oracle 

• BigQuery users will need to configure service accounts for full automation 

Pricing: 

Transparent pricing. No surprise charges tied to MAR or number of connectors.

2. Fivetran

Fivetran is one of the most recognized ETL tools in the market, known for its large connector library and automation-first approach. Its Klaviyo connector is reliable and well-documented, but the tool wasn’t built for ecommerce analytics specifically, which creates challenges when blending Klaviyo data with other systems like Shopify or Recharge.

Fivetran is for: Data engineering or analytics teams at mid to large enterprises who already use Fivetran for other integrations and are looking to add Klaviyo to their existing data pipeline.

Key Features:

• Fully managed connector with automatic schema updates

• Good documentation for setup and testing

• Supports major warehouses like BigQuery, Redshift, and Snowflake

• Works well with dbt for transformation workflows

• Usage-based billing tied to Monthly Active Rows (MAR)

Limitations:

• Does not offer any ecommerce-specific transformations

• Klaviyo’s high event volume can lead to expensive MAR bills

• Some complexity in monitoring sync behavior for non-engineering teams

Pros:

• Extremely stable connector

• Great for teams already familiar with Fivetran

• Handles schema drift automatically

Cons:

• High cost for event-heavy platforms like Klaviyo

• Transformation layer (dbt) adds another tool to manage

• Less flexible if ecommerce logic is required

Pricing:

Pricing is per connection, based on Monthly Active Rows (MAR).

Related Read:

1. Best Fivetran Alternatives & Competitors (Features + Comparison)
2. Saras Daton vs Fivetran

3. Stitch Data

Stitch (a Talend company) is a lightweight ETL platform built for startups and small teams. Its Klaviyo support is technically available but remains in beta or limited feature mode. Stitch works best for companies who want a simple pipeline with scheduled syncs and can tolerate reduced flexibility.

Stitch Data is for: Teams without complex reporting needs who want a simple, low-cost ETL solution to get basic Klaviyo data into a warehouse.

Key Features:

• Easy UI and fast onboarding

• Scheduled syncs (15-min minimum lag)

• Basic transformation support

• Good integration with Redshift and Snowflake

Limitations:

• No real-time syncing

• Minimal support for ecommerce-specific use cases

• Limited control over field mapping or transformation

Pros:

• Very easy to use

• Predictable pricing

• Suitable for proof-of-concept work

Cons:

• Lacks speed and customization

• Limited transformation abilities

• Support is slower than others on this list

Pricing:

Tiered pricing based on volume and sync frequency. Transparent but limited flexibility.

4. Skyvia

Skyvia is a cloud data integration platform that offers a mix of ETL, ELT, and reverse ETL. While it includes Klaviyo among its supported sources, the integration is relatively shallow, pulling only high-level objects and without built-in ecommerce logic.

Skyvia is for: Businesses that need a low-cost, visual integration tool for lightweight reporting or small data syncs.

Key Features:

• Web-based UI for drag-and-drop workflows

• Built-in data viewer for sync verification

• Support for multiple data destinations

• Basic transformation layer

Limitations:

• Doesn’t sync all Klaviyo event types

• Slower syncs (scheduled only, not real-time)

• No ecommerce modeling or templates

Pros:

• Simple interface

• Low cost

• Good for straightforward use cases

Cons:

• Lacks depth in Klaviyo schema support

• No built-in ecommerce-specific modeling

• Not suitable for large datasets or detailed segmentation

Pricing:

The plans vary by record count and features.

5. Hevo Data

Hevo Data is a modern ELT platform built for real-time analytics. It offers a strong native Klaviyo connector and a transformation engine that supports advanced logic. Hevo is positioned as a mid-market tool, and it works well for ecommerce brands that need fast syncs but don’t want to build pipelines from scratch.

Hevo Data is for: Growth teams and data analysts who want a real-time pipeline from Klaviyo to their warehouse with a balance of speed, reliability, and transformation flexibility.

Key Features:

• Native Klaviyo connector with full event and profile sync

• Built-in transformations with filtering, enrichment, and custom logic

• Support for popular warehouses like BigQuery, Redshift, and Snowflake

• Real-time syncing for event-based use cases

• Strong UI for data mapping and job monitoring

Limitations:

• Less tailored to ecommerce-specific reporting needs (e.g., no prebuilt joins with Shopify or Recharge)

• Event volume spikes can affect sync performance without tuning

• Requires learning curve for non-technical users to manage transforms

Pros:

• Great real-time performance

• Customizable data filtering and mapping

• Responsive 24/7 customer support

Cons:

• No ecommerce-native schema templates

• Slightly more technical than tools like Daton or Skyvia

• Pricing can increase if sync frequency is high

Pricing:

Transparent and usage-based.

Related Read: Saras Daton vs Hevo Data

6. Talend

Talend is a comprehensive enterprise-grade data integration platform. It includes data pipeline tools, data quality, data cataloging, and governance features. Its Klaviyo integration is not plug-and-play and usually requires manual setup using API connectors and Talend Studio.

Talend is for: Enterprise businesses with in-house data engineering teams, complex data governance requirements, or existing Talend investments.

Key Features:

• Full control over API pipelines and job orchestration

• Supports large-scale data movement and transformation

• Offers data quality, lineage, and auditing tools

• Deployable on-premise or in cloud environments

• Highly customizable, but not beginner-friendly

Limitations:

• No native Klaviyo connector (requires manual API integration)

• Complex UI with steep learning curve

• Setup and maintenance require technical expertise

• Pricing tailored to enterprise budgets

Pros:

• Best-in-class for data governance and compliance

• Flexible integration framework

• Excellent for teams with hybrid data environments

Cons:

• Expensive and time-consuming to implement

• Overkill for smaller ecommerce teams

• Requires Java and Talend Studio knowledge

Pricing:

Enterprise-only pricing.

7. Pentaho

Pentaho (by Hitachi) is an open-source BI and ETL suite used in traditional enterprise setups. It’s best known for its visual workflow design (Pentaho Data Integration or PDI) and flexibility across legacy systems. However, it doesn’t include a native Klaviyo connector.

Pentaho is for: Enterprise teams running on older infrastructure or with heavy on-prem workloads that require ETL flexibility and manual configuration.

Key Features:

• Visual data pipeline designer

• Deep customization for transformations

• Suitable for batch processing

• Can connect to REST APIs (including Klaviyo) through scripting

• Strong Java SDK and plugin support

Limitations:

• No plug-and-play support for Klaviyo

• Requires manual API handling and data mapping

• Onboarding takes significant time

• Lacks modern cloud-native performance and monitoring tools

Pros:

• Fully customizable for advanced ETL use cases

• Open-source (community edition)

• Suited for large, legacy environments

Cons:

• Not cloud-native

• Difficult to maintain without in-house engineers

• UI and capabilities feel dated compared to modern platforms

Pricing:

Open-source available. Enterprise version requires custom licensing from Hitachi.

8. Rivery

Rivery is a SaaS data pipeline platform with a focus on automation. Its Klaviyo connector is fully native and supports both ingestion and transformation workflows. With Rivery, you can create “Rivers,” which are modular data jobs that can sync, transform, or export data on a schedule or trigger.

Rivery is for: Data and analytics teams looking for a flexible cloud-native platform that supports orchestration, multi-source pipelines, and advanced scheduling.

Key Features:

• Modular data workflows (Rivers)

• Native Klaviyo support

• Real-time and scheduled syncs

• SQL and Python-based transformations

• Strong support for business logic orchestration

• API-based triggering and alerts

Limitations:

• Requires more setup than tools like Daton or Hevo

• Pricing is opaque and generally higher

• UI takes time to get used to for first-time users

Pros:

• Very flexible and programmable

• Supports multi-step data workflows

• Helpful customer success teams

Cons:

• More configuration required up front

• Pricing not ideal for smaller teams

• No ecommerce-specific templates

Pricing:

Custom pricing based on API volume, compute usage, and user seats. Requires a demo for quotes.

9. Airbyte

Airbyte is an open-source ELT tool that has grown quickly thanks to its community-driven approach. It offers over 300 connectors, including a Klaviyo connector maintained by the community. It also allows teams to build and host their own integrations.

Airbyte is for: Teams with engineering resources that want full control over their pipelines and are comfortable self-hosting or customizing integrations.

Key Features:

• Open-source and self-hostable

• Klaviyo connector can be customized

• dbt-based transformations supported

• Offers both CLI and cloud version

• Large GitHub and community support base

Limitations:

• Klaviyo connector isn’t officially maintained by Airbyte

• Requires more effort to monitor and debug

• Cloud version still maturing in UX

Pros:

• Fully open-source and flexible

• Great for experimentation or highly specific needs

• Free if self-hosted

Cons:

• Requires engineering resources

• Not ideal for non-technical teams

• Community support can be hit-or-miss

Pricing:

Free for self-hosted. Cloud pricing is based on credits and data usage.

10. Microsoft SSIS (SQL Server Integration Services)

SSIS is Microsoft’s traditional ETL platform bundled with SQL Server. It supports connecting to REST APIs using script components, but there’s no native support for Klaviyo. SSIS is best suited for companies that already run SQL Server on-prem and want to centralize data there.

Microsoft SSIS is for: Enterprise teams that are heavily invested in Microsoft SQL Server and have in-house IT teams to manage custom API integrations.

Key Features:

• Integration with SQL Server and Azure

• Full control over data pipeline scripting

• Stable for internal database ETL

Limitations:

• No direct support for Klaviyo

• APIs must be manually handled through script tasks

• Lacks real-time or cloud-native functionality

• Maintenance-heavy

Pros:

• Familiar to SQL Server admins

• No additional cost if SQL Server is already licensed

• Integrated with Microsoft stack

Cons:

• Outdated compared to cloud-native tools

• Setup time is high

• Not scalable for modern analytics use cases

Pricing:

Included with SQL Server. No standalone cost, but development time can be expensive.

How to Start Pulling Data from Klaviyo with Saras Daton in seconds

Follow these steps to set up and automate Klaviyo data extraction into your data warehouse using Saras Daton:

1. Prerequisites

• Daton Account: Sign up or log in to your Saras Daton account. Set up your warehouse (with Big Query, Snowflake, Amazon S3, Redshift, etc.)

• Klaviyo API Key: Generate a Private read-only API Key from your Klaviyo account:

• Go to Klaviyo > Settings > API Keys > Create Private read-only API Key

2. Set Up the Integration

1. Log in to Saras Daton:
   a. Access your Daton dashboard.

2. Go to the “Sources” tab > Click on “Add new source”

3. Add Klaviyo as a Source:

         a. Search for “Klaviyo” in the list of connectors.

         b. Click Configure

4. Enter Integration Details:

          a. Provide an Integration Name (used for table naming).

          b. Set the Replication Frequency (e.g., every hour).

          c. Choose the Replication Start Date (how far back to pull data).

5. Authenticate with Klaviyo:

          a. Enter your Klaviyo Private read-only API Key.

          b. Click Authenticate

6. Select Data Tables:

          a. Choose which Klaviyo tables to sync (e.g., Events, Campaigns, Flows, Profiles, Segments, Lists).

          b. For each table, select the specific fields you want to extract.

7. Choose Your Data Destination:

          a. Select your data warehouse (BigQuery, Snowflake, Redshift, etc.).

          b. Confirm the connection details.

8. Submit and Activate:

         a. Review your selections and click Submit.

3. Monitor and Manage the Integration

• Job Status: Check the integration details page for job status, logs, and last sync time.

• Edit or Pause: You can re-authenticate, edit, clone, pause, or delete the integration at any time.

• Adjust Frequency: Change how often data is pulled as your needs evolve.

4. Supported Data & Customization

• Tables Supported: Metrics, Events, Campaigns, Flows, Profiles, Segments, Lists, and more.

• Column Selection: Choose only the fields you need for efficient data warehousing.

• Incremental Sync: Daton supports incremental replication to avoid redundant data loads

Wrap-Up: Saras Daton or Something Else?

If you’re integrating Klaviyo data into a warehouse to support serious reporting and campaign analysis, it’s not just about whether a tool "works." It’s about whether it works fast, works at scale, and understands ecommerce data nuances. That’s why Saras Daton leads this list because of reasons like fast setup, eCommerce-specific features, and transparent pricing.

That said, other tools on this list also serve clear purposes. Fivetran is excellent for enterprise stacks. Hevo is fast and reliable for those wanting real-time. Airbyte offers flexibility if you can code.

The best choice depends on your team’s technical depth, your warehouse environment, and how clean you want the data to be on Day 1.

Ready to see what’s possible?  

Let’s have a quick conversation and map out a smarter, faster way to turn your data into a business ROI channel. Talk to our data consultants now!