Big Data 50 - Companies Driving Innovation in 2018

Big Data Trailblazer by Craig Stewart, VP of Product Management

As companies hit the wall with on-premise systems, they are looking to the cloud to take advantage of promised cost savings, nearly limitless data processing power, and instant scaling options. But connecting cloudbased big data environments with diverse data sources, while also creating Apache Spark pipelines to transform that data, has typically required highly technical knowledge and continuous coding resources, resulting in soaring operational costs and long time-to-value.

To help enterprises overcome these barriers and harness data as a strategic asset, SnapLogic introduced SnapLogic eXtreme earlier this year enabling big data engineers and technical business users to process large volumes of data, without complex code. Just as SnapLogic democratized app and data integration for IT and citizen integrators, Snap- Logic is extending its capabilities to bring the same time and cost benefits to data engineers integrating big data services.

Via SnapLogic’s graphical user interface, data engineers can land data in storage services like Amazon S3 or Azure Data Lake Store using 450+ pre-built connectors. The engineers can then quickly create transformative Apache Spark pipelines with SnapLogic’s ephemeral plex capabilities to easily process large volumes of data from various endpoints using managed big data services like Amazon EMR and Microsoft Azure HDInsights. This results in a substantially lowered barrier to creating cloud-based big data architectures for data engineers while empowering companies with massive cloud compute power and cost efficiencies.

SnapLogic eXtreme benefits include:

• Managed data architecture in the cloud: Automated, fully managed cloud-based big data runtime environment includes integration (iPaaS), processing (BDaaS), and data storage.
• Self-service: A drag-and-drop interface empowers technical business users, or citizen integrators, to save time and eliminate the IT bottleneck.
• Scale: The SnapLogic platform populates the cloud data lake by leveraging 450+ pre-built Snaps for Hadoop, Kafka, Cassandra, MongoDB, AWS Redshift, and other applications and data stores.
• Accelerated time-to-value: Move big data to the cloud quickly to generate business value faster.
• Compatibility: Easily connect managed Hadoop services like Amazon EMR, Microsoft Azure HDInsight, and more

SnapLogic
www.snaplogic.com

Big Data Trailblazer by David Leichner, CMO

Due to exponentially growing data, organizations today are facing slowdowns, with analytics taking hours or even days. Time-consuming preparation is needed for each change in perspective, and some complex analytics simply cannot be done.

SQream has redefined big data analytics with SQream DB, a complementary SQL data warehouse harnessing the power of GPU to enable fast, flexible, and cost-efficient analysis of massive datasets of terabytes to petabytes. SQream’s powerful technology breezes through trillions of rows of data, getting you results up to 100x faster.

SQream DB integrates seamlessly into enterprises’ MPP ecosystems—whether on-premise or on the cloud—drastically reducing query times and enabling previously unobtainable business intelligence. With standard SQL syntax as well as ODBC, JDBC, .NET, Node.js and Python connectivity, SQream DB is already supported.

With SQream DB, raw data is analyzed directly, enabling data scientists and BI analysts to ask more questions about more data from a variety of perspectives without the need for arduous preparation.

Leading organizations in telecom, retail, healthcare, finance and additional industries around the world use SQream DB to accelerate business intelligence and gain access to a world of never-before-seen insights.

SQream
https://sqream.com/