8 min read
Elevate Data Visualization with Apache Superset™ Integration
Elevate Data Visualization with Apache Superset™ Integration
Bruce McFadden
Bruce McFadden Peaka / Seasoned Taskmaster

Elevate Data Visualization with Apache Superset™ Integration

At Peaka, we decided at the beginning of this summer to launch a series of integrations with top-notch business intelligence tools. Having unified your data via innovative techniques like data virtualization and zero-ETL, it was time to provide you with the best data visualization capabilities so you could make the most of your data.

Our Metabase integration went live a few weeks ago so we could democratize data visualization for non-technical users. This time around, we are unveiling an integration with Apache Superset™, a more technical tool that performs at a high level in the most demanding corporate settings.

What is Apache Superset™?

Apache Superset™ is an open-source, Python-based platform for data visualization, exploration, and analytics.

Superset started as an in-house project to develop a data visualization tool at AirBnB in 2015. In 2017, it became a part of the Apache Incubator program, which ensures the smooth development of software projects according to the principles set forth by the Apache Software Foundation. Superset graduated from the program in 2021, officially becoming a “top-level project.” Today, Apache Superset is available as an open-source platform under the Apache License 2.0, and it offers a way out of the “Build vs. Buy” dilemma for organizations in need of a capable data visualization platform.

Build or buy? Why not use open source?

Most tech companies face the “build vs. buy” dilemma at some point. When you need a particular kind of software, do you buy it off-the-shelf or develop it in-house?

The first option provides a well-designed product with some highly sought-after features. However, it might fall short for domain-specific tasks, and because they are a bit of a black box, customizing them to accommodate those needs may be impossible. Then there’s the price issue: Enterprise-grade products can be prohibitively expensive for some use cases.

Building in-house, on the other hand, can be a viable alternative for organizations with ample engineering resources. These organizations can specify the features they want and build software that is tailor-made to their specific needs. However, not many companies can undertake such projects due to resource constraints and the challenges of maintaining and managing such software.

Open-source software, when supported by a lively community, can offer a third option. For tools that are not part of the core business functions and where there are established standards, using the open-source alternative makes sense, especially when you don’t want to incur high costs to buy off-the-shelf and commit engineering resources to build in-house.

Data visualization is not a core business function for most companies and does not offer a competitive advantage when implemented one way or the other. Moreover, metrics and KPIs vary from one company to another, leading to an increased need to customize data visualization tools as required by the workflows. Open-source platforms tick all the boxes here and are perfect fits for data visualization.

Superset: Customizable and enterprise-ready

Superset offers the Goldilocks solution for the common data visualization problem many startups and SMBs suffer from. A few pros make it stand out among the alternatives in the market:

  • User-friendly interface,

  • More than forty pre-built visualizations,

  • Granular access control with table- and metric-level restrictions,

  • Reduced query time for frequently used and elaborate dashboards thanks to cache warmup.

However, Superset’s true strength lies in customizability. Members of the Apache community can influence the roadmap, propose new features, or develop features for common use. Developers have access to the source code, which allows them to modify existing features for their use cases. As a result, Superset users end up with made-to-order data visualization capabilities for their organizations instead of trying to fit squares in round holes.

Another point that distinguishes Superset is its enterprise-readiness. Most open-source projects disappoint when it comes to user experience and polish. That’s because they are developed and maintained by rather small teams of volunteers who have other responsibilities and find it difficult to continuously improve the user experience and fix glitches. That’s not the case for Apache Superset™.

The standards observed by the Apache Software Foundation and the continuous support from the community solve this problem, ensuring that the platform is always up-to-date and scalable. As a result, companies from different industries, such as tech, gaming, media & entertainment, e-commerce, healthcare, finance, and energy, rely on Superset for data visualization. AirBnB, Lyft, Wise, Rakuten Viki, Nielsen, Udemy, and Dropbox have been using Apache Superset and contributing news features to this platform for years. If something is good enough for AirBnB, it will probably be good for your SaaS company as well.

What is Peaka?

Peaka is a cutting-edge data platform that simplifies the process of consolidating and sharing data from various sources across different systems and applications. Peaka is capable of serving as a zero-etl data integration platform and a serverless connector infrastructure.

Zero-ETL data integration platform

Developed as a zero-ETL data integration platform for startups and SMBs, Peaka replaces the modern data stack for these companies. The modern data stack has proved to be overkill for startups and SMBs, whose data integration needs do not justify expensive and complicated systems that are also maintenance nightmares.

Peaka is a good fit for startups and SMBs because it eliminates complex and time-consuming ETL processes from data unification thanks to data virtualization. Turning your data into virtual tables, Peaka establishes a semantic layer over your data sources—relational and NoSQL databases, SaaS tools, and APIs. This semantic layer allows you to query disparate data sources, providing a single view of truth.

Serverless connector infrastructure

In addition to its zero-ETL data integration capability, Peaka also functions as a serverless connector infrastructure for its customers.

Building connectors at scale poses two serious challenges for organizations. The first involves building the connector, which may take weeks or even months for a single connector. Doing this at scale even stretches the engineering resources of enterprises. The second challenge arises from the maintenance hassle, which continues for years to come and gets more complicated with version changes in third-party APIs.

Thanks to Peaka’s serverless connector infrastructure, startups can quickly launch “white-label” SaaS connectors that are always up-to-date, scalable, and highly capable. This reduces development costs for startups, enables them to close deals faster, gain traction, and save on maintenance costs.

What does Peaka’s Apache Superset™ integration do?

Peaka’s Apache Superset™ integration expands this platform’s already impressive skill set.

Further extends Superset

Apache Superset™ currently integrates with more than twenty SQL-based databases and data warehouses, including PostgreSQL, MySQL, Snowflake, Google Big Query, and Amazon Redshift. Peaka maximizes the potential of Superset by connecting it to the most popular SaaS tools. Users can leverage Peaka to pull in their SaaS data from tools such as HubSpot, Salesforce, and Stripe and use that data to enrich the data they keep in SQL databases.

Allows for deeper analysis of data

Every time you run join queries on Peaka and filter your data, you create new datasets. Peaka’s Apache Superset™ integration allows you to visualize these newly-formed datasets as charts and dashboards, helping capture the story they tell. By enabling you to slice & dice your data every which way, this integration makes it possible for you to make the most of your data and draw insights from it, which would not be possible otherwise.

Improves decision-making

Data visualization tools are critical to data-driven decision-making. They help you uncover the trends and patterns hidden in gigabytes of data, which would not be possible in tabular form. However, these tools are limited by the data sources they can connect to. Peaka turns Apache Superset™ into a core part of your decision-making process by letting it retrieve data from all kinds of data sources and establishing a semantic layer over them.

Conclusion

Data visualization is a powerful instrument for extracting information from your consolidated data and making sense of it. That’s why at Peaka, we put a special emphasis on building integrations with the most popular BI tools. These integrations will enable you to form a single view of truth for your business and unlock insights that you would not be able to draw from tabular data.

Click here to access the how-to guide on on Peaka's Apache Superset™ integration.

Check out Peaka’s growing library of custom connectors and book a free demo to see Peaka in action!

faq-icon

Frequently Asked Questions

<p>Apache Superset™ is an open-source business intelligence (BI) tool used for data exploration, data visualization, and analytics. It has a user-friendly interface, more than forty built-in visualizations, detailed access controls for users, and cache warmup, which reduces query execution time for frequently used and elaborate dashboards.</p>
<p>Peaka’s Apache Superset™ integration helps extend this platform, allowing it to retrieve data from to new data sources. Thanks to this integration, users can</p> <p>- Connect Superset to a wide array of SaaS tools that are currently not supported by the platform,</p> <p>- Run join queries on Peaka and visualize their results with Superset,</p> <p>- Consolidate their data from disparate sources and form a single source of truth,</p> <p>- Make data-driven decisions thanks to a better understanding of customer data.</p>
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