ELT comparison: Extract vs Fivetran vs Stitch vs Airbyte

Need to pick the right ELT tool? Here’s an ELT comparison between Fivetran, Airbyte, Stitch, and a new player, Extract to help …

To help you find the best data movement platform for you, and decide which features are essential for your needs, we’ve done a massive ELT comparison of key players. We’re going to compare Fivetran vs Stitch vs Airbyte … plus a brand-new entrant into the modern data pipeline space, Extract.

(Yeah, that’s us!)

Our insanely bold promise is that compared to current market leaders, Extract is …

• Up to 17X more efficient
• Up to 75% cheaper

Plus much more customizable for what data you want to move and how you want to schedule. And incredibly more transparent about what’s happening in real-time with your data. 

These are big promises, agreed. Check and see if you agree in the ELT comparison below. But we do know what we’re talking about since we’ve used all the ELT and ETL tools on the market. And because our parent company, Singular, is one of the biggest data collection, transformation, and loading companies on the planet. 

Our engineers have literally built solutions that some of the biggest data-moving companies on the planet use every day. Think Microsoft. Rovio. Uber. Shopify. Nike. Electronic Arts. Doordash. Warby Parker, and hundreds of other massive brands. And they’ve used all the big ELT tools out there. So we kinda know what we’re doing here, even if we look brand-new to the ELT game.

That’s how we’ve seen that Extract is both super scalable, super efficient, and super inexpensive..

So how do they all compare? Specifically, how does Extract compare to:

• Fivetran
• Stitch
• Airbyte

Check out our ELT comparison …

ELT comparison: Extract vs Fivetran vs Stitch vs Airbyte

	Extract	Fivetran	Airbyte	Stitch
Type	Fully managed ELT	Fully managed ELT	Fully managed ELT + DIY open source	Fully managed ELT
Open source	No	No	Partial	No
Deployment	Cloud only	Cloud only	Cloud Self-hosted	Cloud only
License	Proprietary	Proprietary	MIT (Core) Commercial add-ons	Proprietary
Features	Extract	Fivetran	Airbyte	Stitch
Built in	Rust	Java/Python	Python/Java/etc depending on connector	Java
Connector reliability	High, 100% of the code is owned and maintained by the company	High, 100% of the code is owned and maintained by the company	Mix, most of the connectors are open source projects	Mix, some of the connectors are community-provided
Efficiency	Heavily optimized with Rust; up to 17x more efficient	Standard Java/Python performance	Inefficient architecture (multiple processes/ containers for a single connection)	Standard Java performance, old code-base
Scheduling	Manual Predefined Schedule, Custom Cron Expressions API Invocation	Manual Predefined Schedule	Manual Predefined Schedule, Custom Cron Expressions API Invocation	Fixed intervals Cron expressions available at additional cost
Schema evolution	Automatic Configurable Full Audit Log	Automatic Configurable	Automatic Configurable	Limited Schema Events Log
Transparency	Full visibility into API calls, queries, and processing	Black box	Black blox	Some visibility
Scalability	Enterprise grade	Struggles at high volume	Requires heavy tuning	Limited
Customization	Advanced controls	Limited	Medium	Medium
Transformation	SQL Column mapping Value mapping dbt (coming)	dbt integration Post-load	dbt Custom scripts (pre/post-load)	dbt integration
Logs availability	Yes, super robust in-product logging interface + API access	Not in the product, can be synced to a database	Yes, limited UI	Limited
Quality of logs	Detailed and useful customer facing logs. Code review process guarantees that in present and future connectors.	Lots of internal API calls, unclear logs.	Depends on the developer; many connectors are open source written by non-AirByte employees, and may have no logging	Logs are separated between extraction and loading which makes analysis extremely difficult
Logs API	Yes	No, can be synced in the DB	Partial	No
Realtime logs	Yes	No	No (unless self-hosted)	Yes
Alert customization	System event log + custom rule engine to define any alert you want.	Fixed list of events	Fixed list of events	Fixed list of events
Alert types	Any system event: failures, success, retries, user login, connector edit, etc.	Failures	Failures	Failures Post-load webhooks at additional cost
Alert channels	Email Slack Webhooks	Email	Email Webhooks	Email
SSO	Yes	Yes	Yes	Yes
RBAC	Yes	Yes	Yes (if using SaaS and not self-hosting)	Minimal
Pricing	Extract	Fivetran	Airbyte	Stitch
Basis	Monthly rows	Monthly active rows	Monthly rows	Monthly rows
Free tier	Yes	Yes	Yes	No
Cost	Low (up to 75% cheaper)	High	High	Medium
Security	Extract	Fivetran	Airbyte	Stitch
SOC 2	Yes	Yes	Yes (cloud) Optional (self-hosted)	Yes
GDPR	Yes	Yes	Yes (cloud) Optional (self-hosted)	Yes
HIPPA	Yes	Yes	Yes (cloud) Optional (self-hosted)	Yes

Checking this ELT comparison is one thing.

But we also want to highlight a few areas where we think Extract has a significant advantage.

4 things you can’t do without in a modern ELT

Legacy ELT systems are often slow. They are typically built on aging platforms using inefficient frameworks and code. That matters for both data engineers and the CEOs they ultimately report to, because it makes them expensive: using more CPU time for tasks than they should.

As you can see in the ELT comparison above, Extract is built to do what you need quickly on a super-modern and super-efficient codebase. That makes it both more efficient and more reliable, requiring fewer resources to accomplish the same job. And that makes it cheaper, too, while not sacrificing quality.

Obviously, individual features matter, as we’ve shown in the ELT comparison. But at a higher level than features, you want an ELT system to do 4 things:

1. Move data reliably
2. Move data quickly
3. Move data easily
4. Most data cheaply

Move data reliably

Obviously, reliability is non-negotiable for a modern data stack. Your dashboards, reports, ML models, and ops workflows all depend on fresh, accurate data. If your ELT pipeline fails silently or loses data, trust erodes and downstream systems break.

Ultimately, what that means is that your business breaks.

That why Extract:

• Automatically retries on failure
• Manages drift handling when source tables change seamlessly
• Offers robust logging and alerting
• Supports monitoring & lineage tracking

The idea is no babysitting, no unreliability, no stale insights, no bad decisions, and — especially — no unhappy stakeholders.

Move data quickly

Just as clearly, speed matters, especially for near real-time or real-time analytics, or operational use cases.

That’s why Extract supports:

• incremental syncs that don’t require a full reload every time something small changes
• low-latency replication at a schedule you pick
• super-efficient connectors to minimize lag
• parallelized loading into your data warehouse

Faster syncs equal more responsive analytics and tighter feedback loops, boosting your ability to provide business-critical data when and where you need it.

Move data easily

Set-up matters. Usability is critical. And just as critical is the ability to see exactly what is happening when you add a data connector and when you’re running data pulls. No data engineer wants to hand-hold pipelines every day. 

And non-engineers might need to create pipelines too.

So Extract abstracts away data movement, offering:

• Super easy connector setup
• Totally managed infrastructure (no servers to run)
• Support for the most-common sources and destinations (and growing every day)
• Schema auto-detection and syncing

Simple is fast. Simple is less prone to error. Simple is less engineering effort, more agility, and ultimately faster time-to-value.

Move data cheaply

You don’t want to have to constantly worry about how much your data engineering is costing you. Cost is always a constraint, especially at scale, and legacy ELT tools can get expensive fast, particularly when syncing lots of rows or using complex connectors.

That’s why Extract has:

• Fully transparent pricing
• Highly efficient syncs so you’re not paying for redundant data
• Super-optimized code so we use fewer CPU cycles and you pay less

The best data pipeline is one that does what you need done at a low cost, giving you more scale and less friction with finance. That’s just better ROI.

Extract: the ELT for you

Extract has been customer-engineered by a massive data consuming/moving/transforming company for needs just like yours, and it has all the features you need for your biggest ingestion jobs.

That means Extract is:

• Robust
• Scalable
• Reliable
• Fast
• Low maintenance

But Extract adds unbeatable efficiency to those enterprise requirements so that you get what you need, but get it much more affordably. 

That means Extract is:

• Simple
• Affordable
• Flexible
• Customizable

Try Extract today for free

Interested? Want to take this new tool for a spin? You can do it now, for free, no credit card required.

Simply click here to start making your data movement better.