Data Warehouse vs. Database
Data warehouses are a particular kind of database. Learn how they are uniquely suited to analytics.
The Importance of ETL Security
ETL security is essential for safeguarding your customer's data and complying with regulations. Learn about the Fivetran approach.
dbt Explained
Learn how dbt adds data modeling and transformation to the modern data stack.
Introducing the Fivetran Protocol
Here's how SaaS providers can build bulletproof data replication APIs.
Data Transformation Fundamentals, Uses and Tools
Data can transform a struggling business into a successful one, but first, you need to transform the data. Here’s how.
Key Considerations for Pipeline Performance
Data pipeline performance hinges on several important techniques, including algorithmic optimization and parallelization.
What Is a Data Lakehouse?
The data lakehouse is a promising new technology that combines aspects of data warehouses and data lakes.
When to Use NoSQL and MongoDB
What is MongoDB used for? Learn how MongoDB and its Fivetran connector can help you.
SQL vs. NoSQL: Database Differences Explained
What is NoSQL, and what does it bring to the table?
ETL Platform Alternatives: Fivetran vs. Informatica and More
Compare popular data integration tools on cost, security, reliability and number of supported sources.
Which Connectors Does Your ETL Tool Need?
Make sure your data integration solution can connect to critical data sources.
How to Compare ETL Tools
Use these criteria to choose the best ETL tool for your data integration needs.
What Is ETL?
How do data integration architectures work, and how are they continuing to evolve?
Network Performance and Data Integration
Data integration can easily become non-performant. Learn about some common bottlenecks.
What Is Fully Managed ELT?
Fully managed ELT allows data integration to be outsourced and automated, saving precious engineering time.
Five Things I’ve Learned From Building Analytics Stacks at J.P. Morgan and Fivetran
These data management best practices apply to both large enterprises and fast-growing startups.
What Is the Modern Data Stack?
A radically new approach to data integration saves engineering time, allowing engineers and analysts to pursue higher-value activities.
Why ELT Will Disrupt ETL
ETL, long a mainstay of data integration, is labor-intensive, brittle, complex — and ripe to be supplanted by ELT.
The Ultimate Guide to Data Integration
This guide is a one-stop introduction to data integration. Learn how to make data-driven decisions a reality for your organization!
The Dangers of DIY Database Replication
Database replication for database analytics involves many serious difficulties.
Process Isolation in Data Pipelines
Process isolation is an important pillar of software engineering that can keep your data pipelines (and you) out of trouble.
The Importance of Database Analytics
Use database connectors to uncover insights about your operations.
What Is a Database Schema?
Use schemas to make life easier for your analysts and engineers.
Building Efficient Data Pipelines With Incremental Updates
Sync data incrementally, or watch your pipeline grind to a halt.
Don’t Try This at Home: Building an Idempotent Data Pipeline
Learn about the technical challenges involved in building an idempotent data pipeline.
Idempotence and How It Failure-Proofs Your Data Pipeline
Learn how idempotence protects you from the worst consequences of data integration failures.
ETL vs. ELT: Choose the Right Approach for Data Integration
Learn about ETL and ELT so you can decide which method works for you.
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