Semi Structured Analytics

Unleash Semi-Structured data with fast and seamless analytics

Query semi-structured data with standard SQL and let go of complicated ETL processes that flatten and blow up data set sizes and costs

Your data no longer arrives only in predictable and structured formats, it arrives in different types and from different sources. Semi-structured has become the default in running your apps with dynamic document store and key-value databases, so why does it feel like you’ve gone 10 years back when working with it?

The key to extremely fast and efficient queries on semi-structured data

From raw semi-structured data to fast insights 

If you’re trying to query semi-structured data, you’re probably spending a lot of time on flattening/unnesting/exploding. Whatever you call it, it’s wasting your time and budget. Flattening a table multiplies the number of rows with the number of cells in the arrays and as a result you end up with a much bigger table, more unnecessary costs and painfully slower performance.

Firebolt enables you to run SQL queries directly on semi-structured data with native array manipulation functions, and without compromising speed and efficiency.

Load semi-structured data without transformation

JSON manipulation functions are used to seamlessly cleanse, fix and organize semi-structured data as it’s ingested through Firebolt’s pipeline.

Automatically convert semi-structured data to make it ready for querying

Semi-structured data is automatically converted and stored as arrays of primitive types. Users query the data extremely fast with native array manipulation functions while using standard SQL.

Leverage the same performance optimizations of structured data to reach Firebolt speed

Firebolt provides extreme performance across structured and semi-structured data, regardless of the amount of attributes and arrays it contains

Curious to learn more?

Unleash structured and semi-structured data for fast and seamless analytics