AtScale recently took several key steps to turn its analytics software into a universal semantic layer for big data queries.

Specifically, the privately-held company based in San Mateo, California announced version 6.0 of its Intelligence Platform, integration with Google BigQuery, Microsoft Azure, and Amazon Redshift, and a new round of funding.

Version 6.0. AtScale 6.0 includes the third iteration of the Adaptive Cache, the central feature of the Intelligence Platform. Now, customers can set up a local cache that processes and stores queries with variable filter lists for fast dashboard and visualization rendering times. AtScale has also decreased aggregate processing time by using a graph engine to optimize processing. And AtScale improved its administrative interface to make it easier for administrators to manage and monitor the Adaptive Cache.

New Database Support. Originally, AtScale’s semantic layer only worked with on-premises Hadoop deployments. The announcement extends AtScale’s support for large-scale databases beyond Hadoop. Now, customers can run Google BigQuery, Microsoft Azure HDInsight, and Amazon Redshift with AtScale’s Intelligence Platform . The combination will increase query performance, lower costs, and turn these big data platforms into scale-out OLAP servers.

Typically, organizations extract and load big data into a dedicated OLAP server to achieve speed-of-thought, dimensional analysis. This limits the amount of data users can analyze and prevents them from using real-time information. However, AtScale changes this equation by enabling users to query big data sets without having to extract and move the data into a separate OLAP server. AtScale’s mantra is: bring compute to data, not data to compute.

Funding. AtScale recently closed its series C round for $25 million. Combined with its prior rounds, which totaled $20 million in the past three years, AtScale has raised $45 million. The funds came primarily from one investor, Atlantic Bridge. AtScale officials say they will use the influx of cash to hire developers so it can continue to integrate with big data cloud platforms and invest in customer success teams that support customers after a sale.

Future. AtScale officials say the company intends to build automated intelligence features in the near future.  AtScale wants to use machine learning technology to make its product easier to use and generate insights automatically. For instance, machine learning algorithms might model customer data and past queries to determine which data sets customers want before they even ask.