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With Strato, Esgyn Sends Hybrid Data Workloads to the Cloud

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With Strato, Esgyn Sends Hybrid Data Workloads to the Cloud 451 RESEARCH REPRINT REPORT REPRINT With Strato, Esgyn sends hybrid data workloads to the cloud JAMES CURTIS 01 NOV 2018 Esgyn is an emerging player in the hybrid processing space that sells a SQL-based query engine based on the Apache Trafodion project. Now the company is introducing a managed cloud service to handle hybrid workloads as it looks to spur US adoption. THIS REPORT, LICENSED TO ESGYN, DEVELOPED AND AS PROVIDED BY 451 RESEARCH, LLC, WAS PUBLISHED AS PART OF OUR SYNDICATED MARKET INSIGHT SUBSCRIPTION SERVICE. IT SHALL BE OWNED IN ITS ENTIRETY BY 451 RESEARCH, LLC. THIS REPORT IS SOLELY INTENDED FOR USE BY THE RECIPIENT AND MAY NOT BE REPRODUCED OR RE-POSTED, IN WHOLE OR IN PART, BY THE RE- CIPIENT WITHOUT EXPRESS PERMISSION FROM 451 RESEARCH. ©2018 451 Research, LLC | WWW.451RESEARCH.COM 451 RESEARCH REPRINT Establishing itself as an up-and-coming player in the hybrid processing space, Esgyn has rolled out an updated version of its EsgynDB database, which is based on Apache Trafodion. The company is also making an active push into the cloud with a managed cloud service called Esgyn Strato, which is ex- pected to be generally available in November on AWS and Azure. THE 451 TAKE With hybrid workloads on the rise, Esgyn is in a good position to ride the current wave. The startup’s core technology of Apache Trafodion hearkens back nearly 30 years to technology developed at Tan- dem and later refined at Hewlett-Packard. As such, the company’s core technology rests on a solid foundation with a proven history. Primarily targeting hybrid workloads consisting of transactions and analytics, Esgyn is still ramping up, looking to raise its US profile and increase adoption. The company’s Strato cloud service ought to aid in that strategy, which brings the company in-line with some of its peers in the space, increasing competition. CONTEXT Esgyn is a spinoff from HP that was founded in July 2015. The company is based in Milpitas, California, and has a strong presence in China. While Esgyn has been in existence for just a handful of years, the technology behind the company’s EsgynDB product goes back nearly 30 years. The EsgynDB product is built on the Apache Trafodion project, which was initially open-sourced by HP in 2014. Trafodion was later submitted to the Apache Foundation in 2015, and became a top-level project in early 2018. The core technology behind Trafodion hearkens back to Tandem Computer’s NonStop SQL database offering, where the database was initially developed. Tandem was later acquired by Compaq, which was then acquired by Hewlett-Packard in 2002. At a high level, Esgyn provides an ANSI-SQL query engine that enables hybrid workloads to be carried out, cover- ing transactions and analytics simultaneously on its processing platform, and processing a variety of data types while integrating with a number of storage and in-memory processing engines. While Esgyn can technically work with other storage engines (e.g., Apache Geode), the company’s primary focus has been to run atop Hadoop- based systems, where the firm notes that it is certified to run on Cloudera and Hortonworks deployments. Management reports approximately 30 paying customers and 120 employees, with one-third of those residing in the US and the remaining two-thirds residing in China. Esgyn has taken in $35.4m in funding to date. PRODUCTS In June, Esgyn released version 2.4 of EsgynDB, which included a number of updates. The company’s EsgynDB Manager has been improved, providing a cleaner UI and enhancing the capabilities for backup, restore and overall high-availability functionality. Since data likely resides in multiple locations, Esgyn now supports data in AWS S3, as well as Azure Data Lake Storage, to go along with previously supported HBase and HDFS repositories. Data can be combined or read directly from all of these sources. Furthermore, the company has added functional- ity to enable transitioning from Oracle to Esgyn. Specifically, the company has embedded tooling, a translation function that is able to convert PL/SQL statements to SQL, thereby eliminating the need to manually convert the query logic. Along with a new EsgynDB version, the company has rolled out a managed cloud service called Strato, which was soft-launched in September and is expected to be generally available in November. As a managed service, the company takes care of all the provisioning, tuning, monitoring and so forth. Strato is currently available on AWS and Azure, with Google Cloud Platform forthcoming. While Strato will be initially released as a managed service, a self-service option is also in development, although no specific timetable was provided. 451 RESEARCH REPRINT Like the company’s on-premises version, Esgyn Strato caters to operational and analytical workloads, including the driving of both workloads simultaneously. For operational workloads, Esgyn has customers streaming in IoT data and then carrying out reporting on those transactions, leveraging HBase as the storage engine. But Esgyn can also be set up as a type of operational data store, where the company notes some customers are using it for change-data-capture scenarios paired with a relational database, the idea being that data can be offloaded to two systems. On the analytics side, management reports EsgynDB being deployed as a type of data warehouse capable of short, high-concurrency queries, a mainstay of enterprise data warehouses. But Esgyn can also handle more com- plex analytics, such as for data science and machine learning. In a mixed or hybrid scenario, the use case is geared for real-time analytics. Data is streamed into EsgynDB, where it can carry out materialized views on the data for analysis, such as for fraud detection. With this approach, EsgynDB leverages a number of different storage engines. COMPETITION With its specific focus on hybrid workloads leveraging open source technologies, including integration with Ha- doop-based environments, there are a few direct competitors to Esgyn. Perhaps the startup’s closest competitor is Splice Machine, which is also available as open source and is available on public cloud platforms. While Esgyn leverages the Apache Trafodion project and has ties to Tandem Computer’s NonStop database offering, Splice Machine leverages Apache Derby, which it then fuses with HBase. Another close competitor is LeanXcale. Other competitors might include MemSQL, Actian with its Actian X offering, SAP HANA and InterSystems with its IRIS Data Platform. Some of the in-memory data grid/cache providers (such as Pivotal, GridGain and GigaSpaces) can also be noted as potential competitors, and are increasingly being positioned for a combination of operational and analytical workloads. The traditional relational database vendors have certainly ventured into this space. Some of these vendors – Or- acle, IBM and Microsoft – have added in-memory functionality that serves as a means to store data for analytics, while transactional data can be kept on disk. A number of NoSQL vendors likewise offer mixed workload capabilities and are worth identifying. These vendors include DataStax, MongoDB, MarkLogic, Aerospike, Redis Labs and FairCom. On the cloud front, we would expect competition to come from enterprises blending cloud services to address mixed workloads, such as Amazon Red- shift or Snowflake being paired with Amazon Aurora, for instance. SWOT ANALYSIS STRENGTHS WEAKNESSES Esgyn has been able to leverage existing Tan- The company has a strong presence in China, dem/HP technology – now available as Apache but is not as well known in the US, thus its pro- Trafodion – and has added enterprise capabili- file is a bit smaller than some of its peers in ties on top of it, which it has been able to par- the space. lay into a system targeting hybrid workloads. OPPORTUNITIES THREATS Esgyn’s approach is such that customers can Hybrid workloads are gaining market trac- deploy EsgynDB to run purely as a transac- tion, with many vendors getting into the game tional or analytical system, or in an environ- with offerings based on relational databases, ment where both are combined, giving pro- NoSQL and Hadoop-based systems, thus form- spective clients a good deal of flexibility on ing a highly competitive market. the workloads they might want or need to run..
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