MemSQL Introduces Seamless Spark Connectivity For Enterprise Deployments
MemSQL Spark Connector Enables Real-Time Data Exchange Allowing Enterprises to Operationalize and Streamline Apache Spark Deploymen
SAN FRANCISCO, CA--(Marketwired) - MemSQL, the leader in real-time databases for transactions and analytics, today announced performance connectivity to Apache Spark with its MemSQL Spark Connector, allowing enterprises to operationalize and streamline Spark deployments. The powerful combination of an in-memory database from MemSQL and Spark's memory optimized processing framework gives enterprises immediate access to transactions, ETL, and analytics -- opening up new opportunities for revenue and improved customer experiences. The MemSQL Spark Connector is also available as open source, providing developers the ability to adapt it to their needs.
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Traditionally, data has been siloed in multiple data stores, requiring lengthy transfer time for data to be made available to other systems. With the MemSQL Spark Connector, operational data is immediately available for analysis in Spark, giving enterprises and data analytics teams access to real-time data. Further, results from Spark operations can be quickly placed into production by transferring back to the MemSQL persistent and transactional database.
"Spark is an impressive execution engine for data exploration, and enterprises can now operationalize Spark results with persistent databases," said Eric Frenkiel, CEO and co-founder, MemSQL. "The integration between MemSQL and Spark represents the best of both worlds -- giving enterprises an ability to automate data-driven decision making, perform real-time operational analytics and detect and respond to anomalies in real-time."
The MemSQL Spark Connector utilizes the in-memory and distributed architectures of both MemSQL and Spark for high performance parallel throughput. Regardless of the number of nodes in each cluster, the MemSQL Spark connector allows rapid transfer between the database and Spark RDDs (resilient distributed datasets).
"Users continue to cite data integration as an ongoing challenge, and the luxury of conducting time-intensive and rigid extract/transform/load (ETL) operations is diminishing," said Nik Rouda, Senior Analyst, Enterprise Strategy Group. "Customers expect data solutions to be capable of achieving high performance analysis, with more complicated integration, and the MemSQL Spark Connector helps fill these needs."
Enterprises now have access to real-time analytics on changing datasets, and an elegant and fluid way to interact and consume results from Spark. By simplifying an organization's infrastructure, companies can reduce latency, increase reliability and ensure the productivity and efficiency of its data scientists and developers.
"We are excited to see developments such as the MemSQL Spark Connector enhance the breadth of use cases with Apache Spark," said Matei Zaharia, CTO at Databricks and Vice President of Apache Spark. "This is a great example of seeing the extensibility, performance, and library capabilities of Spark expand with MemSQL to meet the rapid adoption and interest in large-scale data processing anywhere, both on-premises and in the cloud."
To download MemSQL Spark Connector, visit the MemSQL Github site: https://github.com/memsql/memsql-spark-connector
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MemSQL is the leader in real-time databases for transactions and analytics.
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Based in San Francisco, MemSQL is a Y Combinator company funded by prominent investors including Accel Partners, Data Collective, First Round Capital, IA Ventures, In-Q-Tel, and Khosla Ventures. Follow us @MemSQL or visit at www.memsql.com.