Introducing IAQ

Infobright Approximate Query (IAQ) is purpose-built to provide rapid insight for organizations with multi-terabytes to petabytes of data with minimal infrastructure.

Gain rapid insight using high fidelity


Here at Infobright, we believe that data problems can be solved with intelligent software, and NOT more hardware.  Using methodology based on proven statistical models, Infobright Approximate Query (IAQ) was created to provide rapid insight on Big Data while working with traditional scale-out architectures.  Unlike sampling, IAQ examines all data, but performs at impeccable speeds due to relaxing the requirements of accuracy.

Watch this 12-minute overview of IAQ to learn how this powerful engine can interrogate, transform, and materialize your data using a fraction of the resources while producing analogous results to exact queries.

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The Advent of Superscale

Bloor Research describes IAQ as unique and statistically sound.

It’s no secret that big data queries take a long time to complete.  The database industry has spent decades refining database products and inventing new ones in an effort to make such queries run faster.

“What Infobright has done here is truly ground breaking. Query optimization still has a lot of room for improvement and IAQ is certainly the most sophisticated new approach I’ve seen to date.”
– Robin Bloor, Chief Analyst, The Bloor Group.

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Get Insight at Scale

Download this brief datasheet to learn how IAQ accelerates query time.

See how IAQ works without brute-force methods and complements NoSQL options.

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Innovating with Metadata
and Statistical Models

NeuronsWith data volumes climbing at a pace faster and larger than ever before, organizations are left with mountains of data, A LOT of infrastructure, and limited access.  IAQ intelligently reads data upon ingest and alleviates massive scale-out architectures from deriving exact answers to queries.

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Join Beta

If you are interested in participating in our beta phase, please contact us to tell us about your use case.

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