Open Source
Apache Superset is fully open source, allowing users to modify and extend it as needed without any licensing fees.
Rich Visualization Options
Superset offers a wide range of pre-built visualization types, including pie charts, line charts, and maps, allowing for versatile data representation.
SQL Lab
The SQL Lab feature makes it easy to explore and query data in a natural SQL interface, which is highly valuable for analysts and data scientists.
Lightweight
Superset is designed to be a lightweight platform, making it relatively easy to set up and manage compared to more cumbersome BI tools.
Extensibility
With its plugin architecture, Superset can be extended to support additional visualizations and data sources, which makes it highly customizable.
Community and Ecosystem
As part of the Apache Software Foundation, Superset benefits from a robust community and a broad ecosystem of tools and integrations.
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Apache Superset is a good choice for teams and organizations looking for a flexible, scalable, and user-friendly data visualization tool. It offers a balance between simplicity for non-technical users and depth for advanced users who want to perform complex data analyses. However, it might require some initial setup and configuration, especially for those not familiar with managing web applications or working with databases.
We have collected here some useful links to help you find out if Apache Superset is good.
Check the traffic stats of Apache Superset on SimilarWeb. The key metrics to look for are: monthly visits, average visit duration, pages per visit, and traffic by country. Moreoever, check the traffic sources. For example "Direct" traffic is a good sign.
Check the "Domain Rating" of Apache Superset on Ahrefs. The domain rating is a measure of the strength of a website's backlink profile on a scale from 0 to 100. It shows the strength of Apache Superset's backlink profile compared to the other websites. In most cases a domain rating of 60+ is considered good and 70+ is considered very good.
Check the "Domain Authority" of Apache Superset on MOZ. A website's domain authority (DA) is a search engine ranking score that predicts how well a website will rank on search engine result pages (SERPs). It is based on a 100-point logarithmic scale, with higher scores corresponding to a greater likelihood of ranking. This is another useful metric to check if a website is good.
The latest comments about Apache Superset on Reddit. This can help you find out how popualr the product is and what people think about it.
Power Live Dashboards and Proactive Alerts: Feed continuously updated KPIs from RisingWave into your BI tools like Grafana or Superset. Create alerts for critical business events, such as a high-value deal becoming at-risk or a sudden drop in MQLs from a key channel. - Source: dev.to / 3 months ago
By making RisingWave compatible with PostgreSQL, we ensured that any developer familiar with SQL could immediately start writing streaming queries. This wasn't just about syntax; it meant RisingWave could plug seamlessly into existing data workflows and connect easily with a vast ecosystem of familiar tools like DBeaver, Grafana, Apache Superset, dbt, and countless others. - Source: dev.to / 6 months ago
Superset[1] BI tool is a good example of how useful ECharts are [1] https://superset.apache.org/. - Source: Hacker News / 6 months ago
Is this really true? Something that can be supported by clear evidence? I’ve seen this trotted out many times, but it seems like there are interesting Apache projects: https://airflow.apache.org/ https://iceberg.apache.org/ https://kafka.apache.org/ https://superset.apache.org/. - Source: Hacker News / 7 months ago
Open source tools like Apache Superset, Airbyte, and DuckDB are providing cost-effective and customizable solutions for data professionals. Becoming adept at these tools not only reduces dependency on proprietary software but also fosters community engagement. - Source: dev.to / 10 months ago
ClickHouse is highly compatible with a wide range of data tools, including ETL/ELT processes and BI tools like Apache Superset. It supports virtually all common data formats, making integration seamless across diverse ecosystems. - Source: dev.to / 10 months ago
With the transition from ETL to ELT, data warehouses have ascended to the role of data custodians, centralizing customer data collected from fragmented systems. This pivotal shift has been enabled by a suite of powerful tools: Fivetran and Airbyte streamline the extraction and loading, DBT handles the transformation, and robust warehousing solutions like Snowflake and Redshift store the data. While traditionally... - Source: dev.to / about 1 year ago
Also, instead of the custom Dashboard app, a proper BI tool like Power BI, Tableau, Apache Superset, ..., etc. Will be more powerful and flexible. - Source: dev.to / over 1 year ago
We are looking at moving our Power BI stuff to Apache Superset [1]. How does this compare to Superset? [1] https://superset.apache.org/. - Source: Hacker News / over 1 year ago
Do you have any thoughts on Superset? Did you consider it as a candidate? For anyone who doesn't know: https://superset.apache.org/ (There's at least one service that offers managed Superset hosting if that's what you're looking for; it's easy to find so I won't link it here.). - Source: Hacker News / almost 2 years ago
Recently I discovered BigQuery public datasets - just over 200 datasets available for directly querying via SQL. I think this is a great thing! I can connect these direct to an analytics platform (we use Apache Superset which uses Python SQLAlchemy under the hood) for example and just start dashboarding. Source: about 2 years ago
If they don't want to pay for powerbi, can try something like https://superset.apache.org/. Source: over 2 years ago
In today's fast-paced data-driven world, organizations must analyze data in real-time to make timely and informed decisions. Real-time data analytics enables businesses to gain valuable insights, respond to real-time events, and stay ahead of the competition. Also, the analytics engine must be capable of running analytical queries and returning results in real-time. In this article, we will explore how you can... - Source: dev.to / over 2 years ago
For charting, I use superset. It is a good solution if you have a server, but a bit difficult to install. You can use hledger2psql to convert the journal to a database and you can use the docker-compose file included to install with one command. Source: over 2 years ago
There are other viz tools out there, such as Tableau, Quicksight, Looker, Qlikview, and many others in the commercial space. On the open source side, there are some options; Apache Superset is one. Source: over 2 years ago
Perhaps try a BI tool like Tableau, power BI or https://superset.apache.org/. Source: over 2 years ago
You can use superset[0]. Its a Flask app that can connect to databases, read csv, json and create good plots [0] https://superset.apache.org/. - Source: Hacker News / over 2 years ago
Very cool! Anyone know how this compares to Apache Superset? https://superset.apache.org/. - Source: Hacker News / over 2 years ago
Just don't let the folks at Apache hear you, or they'd be very upset. Source: over 2 years ago
The chosen app for visualizing data at our data warehouse is Apache Superset it is an incredible tool considering it is free, and from my experience it has most of the features we can find the famous and paid Power BI. In addition, Superset is also ready for streaming needs and is cluster scalable. - Source: dev.to / over 2 years ago
Check out Apache Superset: https://superset.apache.org/ Originally from Airbnb. Very powerful and flexible OS frontend BI tool. - Source: Hacker News / almost 3 years ago
Apache Superset, a prominent open-source project in the data analysis and visualization domain, has garnered significant attention for its robust capabilities and flexibility. Positioned among competitors such as Metabase, Microsoft Power BI, Tableau, and others, Superset stands out for its open-source nature, allowing businesses to use and modify the software without incurring licensing costs. This aspect is particularly appealing for start-ups and small businesses seeking powerful data analytics tools without the financial commitment of premium products like Tableau or Power BI.
Public sentiment around Apache Superset highlights several strengths and some areas for improvement. One of the key advantages frequently mentioned is its cost-effectiveness. As an open-source software licensed under the Apache License 2.0, Superset provides a viable alternative for businesses aiming to reduce reliance on proprietary software, facilitating a customizable business intelligence solution. This has made it a preferred choice for organizations that prioritize community engagement and adaptability in their data processes.
The flexibility and robustness of Apache Superset are underscored by its seamless integration capabilities. It can connect effortlessly with a variety of data sources and supports diverse data workflows, making it suitable for real-time data analytics applications. Tools such as ClickHouse and RisingWave are compatible with Superset, demonstrating its adaptability within a modern data stack for both startups and established companies. Additionally, Superset's compatibility with SQL-based queries suits data environments that rely heavily on SQL, adding to its appeal for SQL-competent users.
However, there are identified limitations that reflect the challenges associated with using Superset. Notably, it does not support NoSQL databases, which restricts its applicability for businesses that operate primarily on such databases. The installation can also be somewhat cumbersome for users lacking technical expertise, though solutions like using Docker can facilitate the setup process. Despite these hurdles, versatility in deployment options—ranging from self-hosted environments to managed Superset services—provides flexibility for different organizational needs.
Superset’s status as an alternative to popular BI tools like Tableau is well recognized. As highlighted in several articles and discussions, its provision for handling large data volumes effectively and offering a user-friendly interface enhances its role as a competitive open-source BI solution. Comparatively, while tools like Power BI and Tableau are known for their advanced features and ease of use, they come at a cost, making Superset an attractive option for cost-conscious enterprises.
In summary, Apache Superset has carved out a niche in the data visualization and business intelligence landscape, offering a compelling blend of flexibility, cost-effectiveness, and integration capabilities. While there are areas it can enhance, particularly in supporting a broader range of databases and simplifying installation, its open-source nature and compatibility within modern data ecosystems ensure its continued popularity and potential for growth.
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Is Apache Superset good? This is an informative page that will help you find out. Moreover, you can review and discuss Apache Superset here. The primary details have not been verified within the last quarter, and they might be outdated. If you think we are missing something, please use the means on this page to comment or suggest changes. All reviews and comments are highly encouranged and appreciated as they help everyone in the community to make an informed choice. Please always be kind and objective when evaluating a product and sharing your opinion.
