Some common use cases include building a CRM, an application for office inventory management, or an employee directory — all of which Teable has templates for getting started quickly from. 

“Databases and spreadsheets are like brothers, one is serious and high-performing, offering excellent performance and providing powerful data support for applications, but requiring developers to drive through code. The other is flexible and easy to use, a fundamental infrastructure for data processing in the modern office system, almost a basic skill for everyone. We created an organic combination of the two, not only converting ordinary editing operations into a what-you-see-is-what-you-get experience but also organically inheriting the mechanism of column data types, making it the foundation for creating powerful and stable applications,” the project’s creators wrote in a blog post.

According to the creators, while Teable looks similar to the popular tool Airtable, under the hood it is quite different, resulting in better performance and advanced capabilities. Airtable has a limit of 100,000 database rows, but because of Teable’s architecture, it has no upper limit because every table is a real database table and has the query and storage capabilities of one. They have tested a table of 1 million rows of data and were able to do complex filtering and statistical queries in around 200 milliseconds. 

Visually, users can interact with data in a number of different types of views, including a grid view where data is displayed like a normal spreadsheet, a form view where data can be collected via a form, or a Kanban board. The maintainers are also working on multiple other view types, including calendar view for tracking dates and events, gallery for displaying media, Gantt view for tracking project schedules, and a timeline view for tracking events over time. 

It also provides collaboration features where multiple team members can collaborate on the data and have the database be updated in real-time. 

Teable is built on PostgreSQL, which allows it to easily interface with other BI, low-code, and ETL tools, and supports SQL querying. 

Some upcoming features that are being worked on include extensions, the ability to bring your own database, and an AI copilot. 

“Whether you are a seasoned developer or a beginner who wants to complete your own application but does not understand databases, you can easily manage data and implement complex database applications in Teable,” the creators wrote.

Read about other recent Open-Source Projects of the Week:

Penpot | Dioptra | Semantic Kernel’s Agent Framework | Hoppscotch

The post Teable – SD Times Open-Source Project of the Week appeared first on SD Times.

The first update is the ability to extract insights from large amounts of data. It provides an easy-to-understand summary of the insights, which can then be shared with other users or teams. For instance, it can analyze unstructured data such as customer feedback and summarize the most relevant points. 

Next, the company added the ability to automatically apply categories or tags to data, helping teams keep their data better organized. Categories can be based on things like theme, sentiment, product features, and more. 

“If you aggregate thousands of transcripts of customer calls, you can ask Airtable AI to categorize each call according to sentiment (positive, negative, or neutral) and group the data accordingly,” Airtable wrote in a blog post. 

Users can also now create content based off of their data, such as generating emails for sales teams or drafts of campaign assets for marketing teams. It does this by using information about messaging, product, and audience that has been stored in Airtable.

Airtable AI also now offers the ability to automatically translate content across multiple languages. In addition to just translating language, it can also translate tone based on a specific region. 

“Rather than just translating from English to Spanish, Airtable AI can translate copy from English to Mexican Spanish specifically, with a friendly, consumer-oriented voice and tone. This hyper-local approach makes your content immediately relevant to your target audience, and produces a much more accurate and compelling translation compared to other solutions,” the company wrote. 

And finally, there are new capabilities to improve data routing so that data gets in the hands of the right team. This frees up managers from having to spend their time identifying what teams data requests should go to. 

“Organizations have enormous potential to transform the way they work with AI,” said Howie Liu, co-founder and CEO of Airtable. “From the beginning, Airtable has been the most powerful way for teams to work with structured data. Now, Airtable AI offers the fastest way to bring AI to the data and the workflows that matter the most, uniquely unlocking AI capabilities for customers small and large.”

The post Airtable launches several new AI-based features to improve productivity appeared first on SD Times.