Finding The Right ETL/ELT Solution - What Is Estuary And Should You Use It?

Finding The Right ETL/ELT Solution – What Is Estuary And Should You Use It?

Data warehousing would be easy if all data were structured and formatted in the data source. Maybe we wouldn’t even need to build a data warehouse.

But as anyone who has worked with data from more than one source knows, that’s rarely the case. Businesses today need to pull data from a plethora of sources, like SQL Server, MySQL, Postgres, and more. Not to mention all the data needs a lot of love to get it to a point you can perform data analytics. When combining information from multiple sources, you’ll find that data integration quickly becomes important.

If you hope to ever consolidate and analyze data in a consistent and unified fashion, you’ll need a robust, modern data integration solution. Fortunately, there are a lot of good solutions to this problem. Here’s a look at one of the best data ingestion and data integration solutions, Estuary.Dev. Whether you’re new to data warehousing or you’re looking for a Fivetran replacement that can meet your growing data integration needs, Estuary is a compelling option for today’s businesses and their IT departments.

What Estuary Does

So, what is Estuary?

Estuary is a real-time ETL/ELT and data integration platform. ETL—extract, transform, and load—is a critical component of data management and warehousing.

Estuary’s comprehensive feature set simplifies integration by way of “data pipelines.” This eliminates the hassle of consolidating data from multiple locations in various formats, providing a foundation for data accuracy. From there, the consolidated information is available for whatever your team needs it for, from building data-driven apps to enhanced analytics.

As you look around the Estuary website, you’ll find they refer to their product as a DataOps platform geared toward software engineering teams. While it is indeed well-suited for development teams delivering SaaS and streaming applications, Estuary’s flexibility and functions make it a compelling option for any organization dealing with lots of data that comes from disparate sources.

VentureBeat praised Estuary for providing a real-time data integration platform that offers both “batch” and “stream” data processing pipelines. Batch data processing, as its name implies, performs data integration in batches at specified intervals. Meanwhile, stream data processing integrates bits of information from various sources in real time. It’s this flexibility, in tandem with Estuary’s easy-to-manage data pipelines, that makes it a compelling integration solution for any business that needs to harness lots of data.

Change Data Capture (CDC) And Estuary

While the multiple pipelines set Estuary apart from its competitors, its real secret weapon is a process known as change data capture (CDC).

CDC improves upon traditional ETL methods by keeping a historical record of all the data Estuary processes. When changes are made to any of that information, Estuary captures and tracks the changes in real time. There are several advantages to this approach, but the top three benefits are efficiency, accuracy, and analysis:

Efficiency: Rather than re-extracting, transforming, and loading the same information that has been updated or modified, Estuary’s CDC process identifies the existing data and records the changes. When you’re dealing with multiple databases and other sources that are updated frequently, the CDC approach is much more efficient than constantly re-loading and re-writing data.
Accuracy: With CDC, you can always be sure your data warehouse has the latest information, with a historical record of changes and updates.
Analysis: Recording changes allows for a rich historical analysis of your data. Estuary thus helps organizations detect emerging trends and react quickly.

Estuary’s own explanation presents a common scenario that shows the value of the CDC method:

Say you’re a company that manages customer records in a relational database, like PostgreSQL, and powers data analysis from a data warehouse, like Snowflake. When a customer record is updated in Postgres, your CDC mechanism takes note and updates the corresponding record(s) in Snowflake.

In real-world applications that depend on accurate data warehousing, CDC offers a host of benefits, from ensuring an online store’s inventory is accurate to catching fraudulent activity faster. And like Estuary’s other features, CDC is flexible enough to suit just about any organization that works with fast-changing data.

Database Replication Done Right

Database replication is a core feature of most ETL and data integration solutions. It ensures that the apps and business processes that depend on consolidated data can keep running in case of disaster while providing load balancing and high availability at the same time. The problem is that each database or data source can have its own replication requirements. Estuary.Dev offers an impressive range of data replication options, making it well-suited for all your systems.

The eight different types of replication offered are:

Full table replication
Key-based incremental replication
Merge replication
Snapshot replication
Transactional replication
Bidirectional replication
Peer-to-peer replication
Log-based replication

This comprehensive replication feature set brings integrity and resiliency to data availability, again making Estuary a very flexible data integration product.

Who is Estuary For?

Given the above list, it seems clear that Estuary is built for data engineers and DataOps teams. But it’s also well-suited for all types of organizations that have real-time data integration needs. And today, that could apply to almost any company that relies on more than one database or SaaS app.

Estuary offers a full range of open-source connectors and a managed service that streamlines data ingestion and data integration in a wide range of applications and scenarios. Compared to traditional data warehousing tools, if you’re finding roadblocks in your data unification processes, Estuary is worth a look.