Esgyn Launches Enterprise-Class Converged Big Data Platform for Transactions, Operational Data Stores, and BI/Analytics with EsgynDB 2.1

//Esgyn Launches Enterprise-Class Converged Big Data Platform for Transactions, Operational Data Stores, and BI/Analytics with EsgynDB 2.1

Introducing EsgynDB 2.1

Esgyn Adds Support for Columnar Storage, Expands Enterprise Features and Launches Technical Preview of Apache Spark integration to Empower Enterprises with Operational Big Data

Milpitas CA – September 7, 2016 – Esgyn Corporation, the provider of the industry’s most mature, Enterprise-class, MPP SQL Engine for Big Data, has announced the general availability of EsgynDB Release 2.1.  Esgyn is a pioneer in enabling enterprises to step into the emerging world of Operational Big Data. Operational Big Data is a new category of Big Data applications that encompass operational and transactional workloads beyond analytics.


EsgynDB is the commercially supported software with enterprise add-ons, built on Apache Trafodion (incubating).  EsgynDB 2.1 propels Esgyn’s march towards a converged Big Data vision to support any structure of data, of any size, for any workload, from instantaneous transactional and operational to complex reporting, via deep integration with appropriate storage engines, both persistent and in-memory.


EsgynDB 2.1 provides the scale out capabilities of a NoSQL database with the advantages and flexibility of a relational Database, so that enterprises can have the best of both worlds to support ever increasing, complex workloads and multi-structured datasets.

“The latest release of EsgynDB provides critical features for any enterprise which is betting on realizing the value from Big Data, by leveraging the investments for BI, analytics and operational reporting. We are excited to take advantage of the release right away to accelerate the value of Big Data to our business and our customers.”

Wang Zheng, General Manager of Enterprise Business at LeTV.

“We are extremely pleased with our latest release of EsgynDB, which now offers support for columnar storage and enhanced text search capabilities. By deeply integrating with row, columnar and Big Table open source storage engines, we are ushering in a new era for enterprises to deliver transactions through analytics in a single Database for Big Data. We are able to draw from our rich experience with Enterprise Data Warehouse workloads, to enable a holistic approach and an adaptive architecture.”

Dr. Hong Ding, Co-Founder & Executive Vice President of Esgyn Corporation

Key highlights of EsgynDB 2.1 include:

  • Optimized Row Columnar (ORC) format – Seamless support for columnar storage to run analytical workloads efficiently. By fully taking advantage of columnar storage, Esgyn customers can speed up BI and analytical queries by at least 3X.  ORC support brings together relational data in Trafodion tables on low latency HBase, with semi-structured data stored in the HBase Big Table format, with columnar storage in ORC for reporting, via a single powerful world-class query engine.
  • Extensible Data Pipeline Architecture – Integrate external data sources and processing engines in the same query to enable ingestion, text search, and machine learning. Esgyn offers out-of-the-box support for Apache Kafka, Apache Spark, Apache Lucene and Anaconda, and customers can add custom integrations.
  • Elastic Scaling – EsgynDB scales up and down in the Cloud or on-premises, completely online, not losing a single heartbeat, as customer workloads scale to demand. With elastic scaling, EsgynDB customers can add or remove more servers without disrupting services and impacting SLAs.
  • Point-in-Time Restore – EsgynDB’s Point-in-Time Restore protects the data from unintended table updates or drops.

Technical Preview of Apache Trafodion to Spark Connector to Open Source Community

Along with EsgynDB 2.1 release, Esgyn is releasing a technical preview of its integration with Spark through the Extensible Data Pipeline Architecture. Trafodion users can take advantage of this extensible integration to run Spark queries and run machine learning algorithms on the data stored in EsgynDB.  The connector allows the users to create in-memory materialized views from Trafodion data as Spark DataFrames that Trafodion can query for lightning fast reporting.


Visit for more information on EsgynDB 2.1.


About LeTV

LeTV offers online streaming media to 350 million users per month from its library of more than 100,000 television show episodes and 5,000 movies.  LeTV is a subsidiary of Chinese technology company LeEco, whose businesses span Internet TV, video production and distribution, consumer electronics, smart phones and electric cars.


About Esgyn

Esgyn is the leader in Converged Big Data solutions that empower global enterprises to realize the potential of Big Data. With the industry’s most mature, scalable and adaptive SQL Database for Big Data, Esgyn is leading the way enterprises cope with ever increasing data management needs in the cloud or on-premises. Esgyn is a key contributor to Apache Trafodion (Incubating) project and has roots in Tandem NonStop SQL and HP Enterprise Data Warehouse Products.


Please visit for more information on Esgyn and visit for more information on Apache Trafodion.


About the Author:

Ken is an experienced software development leader with deep knowledge of building and delivering enterprise-class database products and supporting platforms from the ground up. Prior to Esgyn, Ken held a variety of positions at HP ranging from Director roles in Product Management, QA, and Development to Chief of Staff. Most recently Ken played a key role in launching Apache Trafodion as an open source project in collaboration with HP Labs, and has the dubious honor of giving the project its name.Ken earned his Bachelor’s degree in Physics from University of Wales with a specialty in Computing Physics and has been a lifelong student of technology ever since.