Google’s BigQuery is a cloud data warehouse leveraged by data analysts and data scientists. If your data already lives on Google Cloud Platform, BigQuery is a natural choice.
But before you can benefit from BigQuery’s user-friendly platform, accelerated insights, and ability to handle different types of data, you have to first extract, transform, and load vast amounts of data into the data warehouse. The goal here is to move your data from disparate sources to the destination data warehouse with zero loss.
So what’s the best BigQuery ETL tool for your next project?
The short answer is that the best BigQuery ETL tool to use is relative to your business, resources, and technical expertise. As ETL is a critical part of the process, you have to be careful when choosing an ETL tool to avoid potential hiccups and even data loss.
At Panoply, we’re on a mission to become data analytics gurus that have the correct answers to any question related to big data. We dove right in, explored a bunch of data platforms, and came up with the top 8 BigQuery ETL tools.
Panoply is equipped with built-in ETL integrations with dozens of data sources out of the box. These include popular advertising platforms, cloud APIs, CRMs, databases, file storage systems, and much more. As Panoply makes syncing, storing, and accessing data a breeze, it might be worth further exploration if you have both data savvy folks and business users on your team.
TL;DR: Panoply is an excellent ETL tool for small to mid-sized businesses with a mix of technical and non-technical users. General ETL tools don’t include storage and are often more difficult to use than Panoply, making it a powerful and affordable solution.
Panoply pricing: see all pricing options; a free trial is available.
Xplenty makes it relatively easy for non-techy users to clean, process, normalize, and transform data while adhering to governance protocols. If you’re a small business operating in a regulated environment, this might be the right tool for you. However, more technical users will be left wanting more.
TL;DR: Xplenty is best for small to mid-sized companies with non-technical users who want to derive value from business data. If you have data scientists and data analysts on your team, it’s best to look elsewhere.
Xplenty pricing: Xplenty offers flat-rate, connector-based pricing that’s available upon request. A 14-day free trial is also available.
Fivetran is armed with a sophisticated caching layer that enables the transfer of data over a secure connection. This approach also helps data scientists move data from the source to the destination without storing a copy on an application server. However, you can only work with the data within BigQuery and create reports because (unlike Panoply) Fivetran doesn’t let you query data within its platform.
TL;DR: Fivetran is perfect for data gurus who want to do much more with enterprise data. However, users report that the UI is a bit clunky and Fivetran lacks a SQL workbench so you can’t interact directly with your data.
Fivetran pricing: Fivetran follows a Monthly Active Rows pricing model that starts at $1/credit. A 14-day free trial is also available.
On the plus side, Stitch comes with dozens of pre-built integrations, including BigQuery (and Panoply). So, connecting Stitch to a BigQuery data warehouse is pretty straightforward.
TL;DR: Stitch is best suited for small businesses with techy-users. This is because you need to know JSON to work with it, and it comes with a steep learning curve.
Stitch pricing: Stitch follows a volume-based pricing model that starts at $100 per month. A 14-day free trial is also available.
Alooma users can write custom code to cleanse and enrich data by leveraging Alooma’s Python-based Code Engine. What’s great about Alooma is that it offers protection against data loss or corruption in potentially error-prone ETL processes. However, as it doesn’t provide a code-free data transformation option, business users won’t be able to participate in the process.
TL;DR: Alooma is perfect for data scientists running enterprise-scale data operations. However, users complain that Alooma isn’t scalable and often breaks when the number of data pipelines increases.
Alooma pricing: available upon request.
Talend also provides several data governance and stewardship features to ensure strict adherence across your organization. You can also quickly transform business data into multiple formats to share across departments. There are also many functions and features to improve data quality and ensure data integrity.
TL;DR: Talend is best suited for Fortune 100 companies with a team of data scientists and data analysts. However, users report that it becomes slower when you scale and that customization can be challenging.
Talend pricing: starts at $1,170 per user per month or $12,000 annually. A free, open-source option and 14-day free trial are also available.
The web-based UI makes it easy to edit and manage Directed Acyclic Graphs (DAGs). So, you can spread tasks across an array of workers without defining precise parent-child relationships between data flows.
TL;DR: Airflow is a powerful tool that’s ideal for businesses engaged in advanced data analytics. Although it’s highly extensible and scalable, it’s useless if you don’t have Python coders onboard.
Airflow pricing: is free and open-source, but Astronomer provides commercial support, which comes at a cost.
With over 100 built-in integrations for popular databases, streaming services, and SaaS applications, you can set up your pipelines and get started within hours. Hevo Data also comes with the option of engaging in data manipulation with Python.
TL;DR: Hevo Data is perfect for large corporations leveraging data to improve processes at every level. However, users complain about its clunky UI, alerts that aren’t precise or intelligent, and the limited number of data sources included in each package.
Hevo Data pricing: starts at $249 per month, and a free trial is available.
It can be difficult to choose the right ETL tool for your business with all of the different options available in the marketplace. But at its most basic, it comes down to your available resources, technical know-how, and your business goals.
At Panoply, we are firm believers in providing robust ETL pipelines and data warehousing with unparalleled support. Although Panoply was designed with data analysts and data scientists in mind, even non-technical users can set up and manage their data without depending on expert support.
Curious? Why not try a Get started for free or get a real-time personalized demo?