Big Data Education Webcast: Introducing DMX and DMX-h Release 8
Download as PPTX, PDF0 likes1,742 views
This document introduces Syncsort DMX-h Release 8, which provides a complete solution for offloading legacy workloads to Hadoop. Key features include: - An intelligent execution layer that isolates users from Hadoop's underlying complexities. - The ability to design ETL jobs once and deploy them on-premises, in the cloud, with or without Hadoop. - End-to-end data ingestion capabilities for Hadoop, including from mainframes, databases, JSON, Avro, Parquet, and NoSQL sources.
Big Data Education Webcast: Introducing DMX and DMX-h Release 8
- 1. Greg Grubbs, Product Manager | Big Data Jorge A. Lopez, Director Marketing | Big Data DMX-h Release 8
- 2. Syncsort Confidential and Proprietary - do not copy or distribute 2 Introducing Syncsort DMX-h Release 8 Intelligent Execution Layer isolates users from underlying complexities of Hadoop Design once. Deploy anywhere - with or without Hadoop; on-premises or in the Cloud Provides the most complete, end-to-end solution for offloading heavy legacy workloads to Hadoop Delivers best-in-class, one-step data ingestion capabilities for Hadoop: mainframes, RDBMS, MPP, JSON, Avro/Parquet, NoSQL, and more Facilitates metadata management and data lineage by automatically updating HCatalog when loading to Hive, Avro and Parquet
- 3. Syncsort Confidential and Proprietary - do not copy or distribute 3 A Complete Solution to Harness the Power of Hadoop
- 4. Syncsort Confidential and Proprietary - do not copy or distribute 4 Collect Build Your Enterprise Data Hub Hadoop + DMX-h Avro Parquet Cassandra MongoDB Mainframe Vertica Oracle Teradata Netezza JSON HBaseFiles Cloud • Collect virtually any data from mainframe to Big Data and NoSQL sources • Access, re-format and load data directly into Avro & Parquet. No staging required • Access & translate mainframe data using Sqoop and Spark • Load more data into Hadoop in less time. Let DMX-h dynamically split the data and load it to HDFS in parallel
- 5. Syncsort Confidential and Proprietary - do not copy or distribute 5 Hive and HCatalog Read & write to Hive Support for multiple file formats including text, Avro, Parquet Metadata using HCatalog (Hive Meta Store) Dynamically parallelize load to Hive 0.00 2.00 4.00 6.00 8.00 10.00 12.00 1.01 2.03 4.50 Hour Hive Write Throughput (TB/hour) DMX ODBC Parallel Hive Command
- 6. Syncsort Confidential and Proprietary - do not copy or distribute 6 Prepare Get Your Data Ready for Analytics • Sort • Cleanse • Partition • Translate • Reformat • Compress • Validate • Prepare your data on-the-fly at lightning speeds before loading into Hadoop • Increase data compression ratios by up to 10x • Achieve significant storage savings Hadoop + DMX-h
- 7. Syncsort Confidential and Proprietary - do not copy or distribute 7 Blend Find Bigger Insights by Combining New and Legacy Data • Fastest, most efficient data joins • Best-in-class mainframe data access & translation • Common user experience with or without Hadoop! • No need to worry about mappers, reducers, big side, small side and so on • No code to generate, compile, maintain or tune! Mainframe JSON RDBMS
- 8. Syncsort Confidential and Proprietary - do not copy or distribute 8 Transform Design Once, Deploy Anywhere! • Free your users from the underlying complexities of Hadoop • Visually design data transformations once, and run anywhere • No changes or tuning required • Intelligent Execution Layer dynamically optimizes the job for each platform: Hadoop, Windows, Unix, Linux or Cloud • Future-proof your applications! Intelligent ExecutionLayer Windows, Linux, Unix Hadoop Cloud
- 9. Syncsort Confidential and Proprietary - do not copy or distribute 9 DEMO DEMO
- 10. Syncsort Confidential and Proprietary - do not copy or distribute 10 Distribute Achieve the Fastest Path from Raw Data to Insight • Create Tableau & Qlikview files with one click • Achieve the fastest data loads without tuning hassles: • Fastest parallel loads to Greenplum, Netezza, Teradata & Vertica • High-performance connectivity to Big Data & NoSQL databases such as Cassandra, Hbase & MongoDB Hadoop + DMX-h NoSQL
- 11. Syncsort Confidential and Proprietary - do not copy or distribute 11 Not Using Hadoop? Single Design Experience = ETL Anywhere! Best-in-class Data Visualizations, Just a Click Away Complete Access to All Your Data, Big or Small Web Based Monitoring & Administration Secure Mainframe Data Access Intelligent Execution Layer Windows, Linux, Unix, Cloud, and more… when you’re ready
- 12. Syncsort Confidential and Proprietary - do not copy or distribute 12 DEMO DEMO
- 13. Syncsort Confidential and Proprietary - do not copy or distribute 13 Plus… The Only Tool Specifically Designed for EDW Offload Now with automatic DTL generation! • Web-based utility • Takes SQL as an input • Provides visual analysis of SQL ELT jobs • Generates metadata and data migration with DMX jobs • Supports ANSI-SQL 2011, BTEQ, Netezza, Oracle PL/SQL
- 14. Syncsort Confidential and Proprietary - do not copy or distribute 14 Save users from underlying Hadoop complexities Future-proof your applications. Design once, deploy anywhere! Offload heavy ELT workloads to Hadoop Secure, monitor, manage and scale with minimum effort Sign up for a Free Trial! Break Free from ETL Complexity Experience DMX & DMX-h Release 8 Syncsort.com/dmxh8 Watch this webcast on demand – including the product demos! http://bit.ly/1wI1SRN
Editor's Notes
- #4: So when you take a look at what we do as company, you will notice we no longer use the term ETL. Big Data requires a new approach. ETL tools that failed in the past are even less suitable for Hadoop. For most legacy ETL tools, Hadoop is not the cornerstone, it is an after-thought: They have heavy stacks with software that you don’t need and dependencies on lots of 3rd party components They are a result of patchwork that now generates highly inefficient code On the other hand, newer tools do not provide a complete solution, require lots of hand coding and most of them lack enterprise-grade capabilities Syncsort DMX-h was designed specifically for Hadoop – combining a long history of innovation with significant contributions Syncsort has made to improve Apache Hadoop. DMX-h is deployed as part of the Hadoop Cluster Delivers everything you need to collect, prepare, blend, transform and distribute data with Hadoop – nothing more, nothing less Facilitates adoption and development of Hadoop jobs with a design once, deploy anywhere approach Packages industrial-grade capabilities to deploy, manage, monitor and secure your Hadoop environment in fact, we are much more than just ETL – we are a complete solution to help organizations collect, prepare, blend, transform and distribute your data. Now that’s a mouthful, so let me explain what this mean…
- #9: Removes the complexity of Hadoop Makes it more accessible to more people within your organization Future-proofs your applications, that means, when the new execution framework comes, you can deploy there with minimum or no changes to your applications So if you look at it from the perspective of the business it removes a tremendous amount of risk, because you ensure your investments will continue to pay back even as the Hadoop ecosystem continues to evolve