Rockset Allows Users To Ingest, Analyse Real-Time Data From Microsoft Azure

Rockset-Now-Allows-Users-to-Ingest,-Transform,-and-Analyze-Real-Time-Data-from-Microsoft-Azure

Rockset, the real-time analytics company, now supports real-time data ingestion from Azure Blob Storage, Azure Event Hubs, and Azure Service Bus — enabling customers to ingest, transform and analyse real-time data from their Azure data lake or event stream.

With an extensive library of built-in data connectors for schemaless ingestion from existing event streams, databases, and lakes, Rockset stays in sync with the data source, enabling fast analytics within 1-2 seconds of new data being generated, according to the vendor. As the data arrives, Rockset supports continuous SQL transformations and roll ups without the need for batch ETL jobs.

With this new release, Azure customers can sync their data using fully managed connectors to popular Azure and Microsoft services, including Azure Blob Storage, Azure Event Hubs, and Azure Service Bus.

“Companies are recognizing that they cannot build a data-driven culture relying on batch-based analytics and BI alone. There is too much latency at every step—finding the data, ingesting it, querying it and representing it. In an age of lightning-fast consumer apps such as Instagram, users won’t tolerate excruciatingly slow analytics experiences. Not your customers, nor even your internal employees,” said Venkat Venkataramani, co-founder and CEO at Rockset. “Azure has a strong public cloud presence, and with this release we are making real-time analytics more accessible and affordable for all Azure customers.”

Rockset already integrates with multiple data lakes, event streams and transactional databases within Amazon Web Services (AWS) and Google Cloud Platform (GCP).

Rockset offers built-in connectors that are fully managed as part of its cloud platform, obviating the need for users to build and manage complicated data pipelines or use a separate ETL tool, and enabling real-time search, aggregations, and joins across disparate data from multiple sources.