Google BigQuery has become a dominant leader in the world of big data.

But that data only works if you can collect and analyze metrics from every data set that matters to your business. And to do that, your data science team needs the right ETL tool.

Google BigQuery ETL Overview

• BigQuery is a serverless, scalable, and fully managed cloud data warehouse part of the Google Cloud Platform (GCP).
• Users create data pipelines with SQL using Google's integrated tools or third-party ETL tools.
• You can access BigQuery through the cloud console, command-line tool, or REST API.
• BigQuery connects with most major business intelligence tools to deliver data insights in a visual dashboard.
• BigQuery offers superior performance, scalability, and speed compared to platforms like SQL Server. That's because of its fully managed data warehouse.
• Google offers several BigQuery ETL tools, including Dataflow and Data Fusion, but third-party tools offer more flexibility.
• Whether you want ETL (extract, transform, load) or ELT (extract, load, transform) processes, you can find a tool that works with BigQuery.

Why BigQuery is a Smart Choice for ETL

BigQuery is one of the most popular data warehouses, but it's not the only one. It's in a crowded field with competition from other players like Snowflake, Amazon Redshift, and Microsoft Azure Synapse Analytics.

Pricing

• Flexible on-demand and flat-rate pricing. Check out our deep-dive analysis of BigQuery's pricing plans.
• On-demand data analytics: free for 1TB/month; $5.00/TB thereafter
• Flat rate: Based on pre-committed amounts, with steep discounts for longer commitments.

Key features

• BigQuery divides its storage and compute resources, which means handling computations where the data is instead of replicating it elsewhere.
• Serverless architecture means you don't need to worry about allocating clusters or resources to individual processes.
• Machine learning is built-in with SQL queries, letting you access much more advanced features without learning a new skill set.
• BigQuery is an OLAP (online analytical processing) solution that works best with relatively infrequent database writes and can handle much more frequent reads.

Who is BigQuery best suited for?

• Data science teams seeking a powerful cloud data warehouse with fewer management requirements will be satisfied with BigQuery.
• BigQuery's managed platform, serverless architecture, and low overhead mean less time overseeing infrastructure and more time using the platform.
• And, of course, BigQuery is an obvious option for data engineers familiar with the Google Cloud Platform ecosystem.

How to Choose the Best BigQuery ETL Tool

If you're choosing a BigQuery ETL tool, there are a few features to pay careful attention to. Each solution has its advantages and disadvantages.

Data sources

Your BigQuery data should function as the foundation of the best data-driven insights. Tools that lack data integration features for mission-critical apps aren't going to deliver the 360-degree view your team needs.

Extensibility

Look for a tool that supports the data pipelines you need now and can grow with you in the future.

Choose a BigQuery ETL solution that supports various use cases and workflows and supports the different sources and SaaS apps you'll use down the road.

Customer support

Your data engineering team should spend most of its time leveraging the data, not moving it from one place to the next. The best ETL tools will offer hands-on support to help guide you through this process.

Pricing

Budgets matter, of course, but a pricing model that's easy to understand and predict is even more important for many teams.

Consumption-based pricing can change every month, making it hard to estimate costs from one billing cycle to the next.
 
Top 4 BigQuery ETL Tools

1) Google Cloud Dataflow

Dataflow is an ETL tool that's part of the Google Cloud Platform. It accepts data pipelines built in Java or Python and integrates seamlessly with BigQuery. Dataflow uses Apache Beam as its engine.

Key features

• Integrates with Google BigQuery and other GCP products.
• Wide range of templates to speed up development.
• Works for batch and streaming data.

Who is Google Cloud Dataflow best suited for?

Dataflow is best suited for teams fully integrated into the GCP ecosystem looking for a code-friendly BigQuery ETL tool.

2. ) Google Cloud Data Fusion

Google Cloud Data Fusion is another GCP product focused more on simple integrations than complex data transformation workflows.

Data Fusion is a no-code platform that uses a GUI to import data into BigQuery. It's built with the open-source Cask Data Application Platform (CDAP) under the hood.

Key features

• User-friendly interface that lets you create ETL workflows without code.
• Pre-built transformations to get data pipelines up and running faster.
• Ability to import from on-premises sources in real-time.
• The serverless platform handles infrastructure provisioning, cluster management, and more automatically.
• Plugins for loading data, performing common dataset transformations, and populating business intelligence dashboards (Looker)

Who is Google Cloud Data Fusion best suited for?

Google Cloud Data Fusion is best suited for teams that work exclusively with GCP but need a no-code tool for data integration.

3) Stitch

Stitch is an ETL tool part of the Talend suite of tools. It includes features to load data into BigQuery and handle replication tasks using change data capture.

Stitch also supports simple data transformation using its GUI or Python, Java, or SQL scripts.

Key features

• 137 data sources are supported.
• Part of the Talend ecosystem and integrates with other tools on the platform.
• Intuitive platform with GUI-based transformations.
• Monitoring and alerts are handled automatically.

Who is Stitch best suited for?

Stitch is ideal for teams with popular data sources that only need simple transformations. You'll need to upgrade your plan if you need more support than self-service tutorials and chat.

4) Hevo

Hevo is a no-code platform that has 150+ data connectors. It supports ETL, ELT, and reverse ETL workflows and includes features like real-time data loading, replication, and data transformations.

Key features

• 150+ data connectors (limited to 50+ on the free plan)
• Data migration in real-time.
• Robust data transformation support through Python scripting
• 24/7 live support

Who is Hevo best suited for?

Hevo is best for data science teams with common data sources that prefer a no-code platform but want the flexibility to write code.

What is Google BigQuery?
Google's BigQuery is part of the Google Cloud Platform, a database-as-a-service (DBaaS) supporting the querying and rapid analysis of enterprise data.

COMPARISONS

Google BigQuery

Google's BigQuery is part of the Google Cloud Platform, a database-as-a-service (DBaaS) supporting the querying and rapid analysis of enterprise data.

Snowflakes

The Snowflake Cloud Data Platform is the eponymous data warehouse with, from the company in San Mateo, a cloud and SQL based DW that aims to allow users to unify, integrate, analyze, and share previously siloed data in secure, governed, and compliant ways. With it, users can securely access the Data Cloud to share live data with customers and business partners, and connect with other organizations doing business as data consumers, data providers, and data service providers.

Amazon redshift

Amazon Redshift is a hosted data warehouse solution, from Amazon Web Services.

Amazon athena

Amazon Athena is an interactive query service that makes it easy to analyze data directly in Amazon S3 using standard SQL. With a few clicks in the AWS Management Console, customers can point Athena at their data stored in S3 and begin using standard SQL to run ad-hoc queries and get results in seconds. Athena is serverless, so there is no infrastructure to setup or manage, and customers pay only for the queries they run. You can use Athena to process logs, perform ad-hoc analysis, and run…

mysql

MySQL is a popular open-source relational and embedded database, now owned by Oracle.

Microsoft Power bi

Microsoft Power BI is a visualization and data discovery tool from Microsoft. It allows users to convert data into visuals and graphics, visually explore and analyze data, collaborate on interactive dashboards and reports, and scale across their organization with built-in governance and security.

looker

Looker is a BI application with an analytics-oriented application server that sits on top of relational data stores. It includes an end-user interface for exploring data, a reusable development paradigm for data discovery, and an API for supporting data in other systems