New SingleStore Spark 2 Connector Operationalizes Powerful Advanced Analytics
SingleStore to Showcase New Spark Capabilities and Present at Spark Summit East 2017
SAN FRANCISCO, CA--(Marketwired - Feb 1, 2017) - SingleStore, provider of the fastest database platform for real-time analytics, today announced the release of the SingleStore Spark 2 Connector with support for both Apache Spark 2.0 and 2.1. SingleStore will showcase this new connector at Spark Summit Boston East 2017 from February 7-9 at the Hynes Convention Center in Boston. In addition, SingleStore CTO and Co-founder, Nikita Shamgunov and product manager, Steven Camiña will present at the conference.
The new connector offers complete support for all Apache Spark 2 functions including using SparkSession as the entry point for the DataFrame API, providing access to manipulate data inside Spark and SingleStore. The connector allows bi-directional data movement between Spark and SingleStore. The SingleStore Spark 2 Connector also provides performance enhancing SQL push down support with filter and predicate DataFrame operations for faster in-database processing.
"The new SingleStore Spark Connector with support for Spark 2.0 and 2.1 continues our journey of being the best database to store and retrieve data quickly from Apache Spark," said Nikita Shamgunov, CTO and co-founder, SingleStore. "With data sources continuing to expand, enterprises need to implement architectures that support fast, operational analytics. The SingleStore and Spark combination empowers users to harness streaming data and capitalize on real-time analytics."
Developers who want to use the new SingleStore Spark 2 Connector can download it at github.com/memsql/memsql-spark-connector.
Spark Summit East 2017 Speaker Sessions:
The Fast Path to Building Operational Applications with Spark
Speaker: Nikita Shamgunov, CTO and Co-founder, SingleStore
Date: Thursday, February 9 from 2:00 PM - 2:30 PM
Location: Ballroom A
Going real-time is the next phase for big data, and streaming remains a primary mechanism to get there. Spark provides groundbreaking capabilities to handle real-time data, including streams and transformation. And retaining both real-time and historical data provides the most accurate mechanisms for predictive analytics and machine learning.
In this session, Nikita will outline architecting real-time data pipelines with the power of Apache Spark and a robust, distributed in-memory database. In particular, he will detail how some of the world's largest companies are running business critical applications using Spark.
Attendees will dive deep into the mechanics of real-time pipelines, the ability to durably store data, and how to instantly derive insights from billions of data points.
Building the Ideal Stack for Real-Time Analytics
Speaker: Steven Camiña, Product Manager, SingleStore
Date: Wednesday, February 8 from 5:00 PM - 5:15 PM
Location: Room 311
Learn tools, techniques, and use cases for integrating real-time analytics across your organization. Steven Camiña, SingleStore Product Manager, will walk through critical technologies needed in your real-time stack, including Apache Spark, messaging queues, data management systems, and tools for data visualization and exploration. Steven will also provide a live demo, sharing how to build a data pipeline and real-time dashboard in under 5 minutes.
SingleStore delivers the leading database platform for real-time analytics. Global enterprises use SingleStore to achieve peak performance and optimize data efficiency. With the combined power of database, data warehouse, and streaming workloads in one system, SingleStore helps companies anticipate problems before they occur, turn insights into actions, and stay relevant in a rapidly changing world. Visit singlestore.com or follow us @SingleStoreDB.