The Extract blog:insights & innovations in data movement

Explore the latest trends, industry news, and expert perspectives on the innovation of data pipelines, automation, and the future of ELT—designed for data-driven teams looking to stay ahead.

Powering data teams globally

The first AI-native ad channel just got measurement: ChatGPT Ads reporting and Conversion APIs in Extract
Measure ChatGPT Ads performance alongside every other channel and send clean conversion signals back to ChatGPT Ads with Extract.
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Build vs. buy: AI can write your ELT pipeline. It can't maintain it.
- ELT
AI made the first connector nearly free. It did nothing to the cost of the fortieth, six months later, at 2 a.m. A framework for when to keep building and when to buy.
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Reverse ETL, explained: no-code mapping, PII hashing, and audit logs
- ELT
Reverse ETL moves data back out of your warehouse into the tools your team works in. How it works, why PII hashing and audit logs matter, and how it fits with ELT.
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Extract and the modern mobile marketing stack: how ELT fits between your MMP and your BI tools
Attribution in one silo, spend in another? See how an ELT layer connects your MMP, warehouse, and BI tools without custom scripts or Monday fire drills.
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Introducing the Extract Plugin for ChatGPT and Codex: Bring Your Data Pipeline into AI
The Extract Plugin for ChatGPT and Codex brings data pipeline operations directly into AI. Set up connections, monitor syncs, troubleshoot…
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Troubleshooting common ELT issues (and how Extract solves them)
- ELT
- How-to
Learn how to troubleshoot common ELT issues like schema changes, pipeline failures, and rising costs, and see how Extract’s Rust-based…
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ELT for mobile games analytics: How SciPlay is using Extract to win
- Data
- ELT
Can ELT provide better mobile games analytics so modern technical growth teams can make smarter marketing and advertising decisions?
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Extract vs Fivetran: an ELT platform comparison
- Data
- ELT
Can a brand-new ELT tool offer something better than an established player? Take a look at this Extract vs Fivetran…
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Best data integration platforms for 2025: top 7 solutions compared
- Data
- ETL
Data integration platforms are critical tools for enterprises to unify physical or logical access to data. Here are some of…
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Extract vs Stitch: an ELT platform comparison
- ELT
Extract vs Stitch: how do they compare? Here’s a quick overview of Stitch compared to the newest ELT competitor in…
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Extract vs Airbyte: an ELT platform comparison
- ELT
Extract vs Airbyte: how do they compare? Here’s a quick 5-minute overview …
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Real-time analytics and ELT: accelerating business velocity in every vertical
- Data
- ELT
Real-time analytics help you run a business, sure. More importantly, they help you accelerate decisions and actions …
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Top modern data stack tools for 2025
- Data
- ELT
A modern data stack is mission critical in 2025. It’s a toolkit for making fast, reliable data-driven decisions. Here are…
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Why your data pipeline keeps breaking (and how Extract can fix it)
Data pipelines are often fragile, delicate things. But they don’t have to be. Extract offers the best of ELT to make everything better
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The top 10 ELT use cases in 2025: AI, supply chain, compliance, CRM, and more
- Data
- ELT
ELT is driving change in multiple industries. Here are the top 10 ELT use cases for 2025
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How ELT fits into the modern data stack
- ELT
How does ELT drive business results? By connecting your modern data stack to make everything smarter. Here’s how …
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ELT tools comparison: Extract vs Fivetran vs Stitch vs Airbyte
- Data
- ELT
Need to pick the right ELT tool? Here’s an ELT comparison between Fivetran, Airbyte, Stitch, and a new player, Extract to help …
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Introducing Extract: The new status quo in data movement
- Data
- ELT
- ETL
Introducing Extract, the high-performance ELT platform built in Rust for lightning-fast, resource-efficient data movement. With powerful customization, real-time observability, and radically affordable pricing, Extract redefines how modern data teams move data. Try it free today.
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ETL vs ELT: which is right for you?
- Data
- ELT
- ETL
What are the key differences between ELT and ETL data pipelines? Which is best for your business needs, data scale, and team skills?
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