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New Features Plus New
Onboarding User Experience
Paige Roberts, Integrate Product Marketing Manager
Ashwin Ramachandran, Integrate Product Manager
June 2018
1
New Features Plus New Onboarding User Experience
• Data Integration Product News
• DataFunnel UI Demo
• New Onboarding User Experience – DMX DataFunnel GUI
• Where to Find Out More
1 Hive Improvements
2 Impala Support
3 Lineage
4 DMX Change Data Capture
Disclaimer
Any information about our roadmap outlines our general
product direction and is subject to change at any time
without notice. It is for informational purposes only and
shall not, be incorporated into any contract or other
commitment.
Syncsort undertakes no obligation either to develop the
features or functionality described or to include any such
feature or functionality in a future release.
3
DMX/DMX-h Product News
4
5
Hive Support Enhancements
• JDBC connectivity
• Support for partitioned tables: ORC, Parquet, AVRO, HDFS
• Support for Truncate and Insert
• Automatic creation of Hive and other Hcat supported tables
• Direct distributed processing of Hive
• Update of Hive statistics
• Use Hive tables for lookups
• Change data capture target
• Hive ACID Merge support – Updates, inserts, deletes, and upserts in Hive
• Full support for complex types – arrays, structs, etc.
• Improved usability and support in mapping entire arrays, array elements and
composite fields.
6
Cloudera Impala Support
• JDBC connectivity
• Both read and write support
• Support for Impala tables backed by: Parquet, Kudu
• Automatic creation of Impala tables
• Direct distributed processing of Impala – on edge node, framework-
designated node, or distributed on cluster with MapReduce or Spark
• Update of Impala statistics
• Use Impala tables for lookups
• Full support for update and insert
• Change data capture support
7
Db2 on IBM i
DMX/DMX-h Product News
Lineage
8
9
Govern and Track Everything for Compliance
• Metadata and data lineage for Hive, Avro and Parquet
through HCatalog
• Metadata lineage export and REST API from DMX/DMX-h
o Simplify audits, analytics dashboards, metrics
o Integrate with enterprise metadata repositories
• Cloudera Navigator certified integration
o Audit and track data from source to cluster
o HDFS, YARN, Spark and other metadata
o Lineage, tagging
o Business and structural metadata
• Apache Atlas ingestion lineage integration
o Audit and track data from source to cluster
o Lineage, tagging
10
Onboard ALL Enterprise Data – Mainframe to Streaming
Data Sources
Onboard data, modify
on-the-fly to match
Hadoop storage model,
or store unchanged for
archive and compliance.
Access data from
streaming and batch
sources outside
cluster.
Data Lake
Data
Transform, join,
cleanse, enhance
data in cluster
with MapReduce
or Spark.
Analytics,
Visualization,
Machine
Learning
Complete
Data
Analytics,
visualizations, and
machine learning
algorithms get ALL
necessary data.
11
Get Source to Consumption, End-to-End Data Lineage
Data Sources
Auditors
get end-to-end
data lineage.
Analytics,
visualizations, and
machine learning
algorithms get ALL
necessary data.
Navigator or Atlas
gathers any other
changes made to
data on cluster.
Pass source-to-
cluster data
lineage info to
Navigator or Atlas.
Data Lake
Data changes made
by MapReduce,
Spark, HiveQL.
Data
Data Lineage
REST
API
Onboard data, modify
on-the-fly to match
Hadoop storage model,
or store unchanged for
archive and compliance.
Access data from
streaming and batch
sources outside
cluster.
Transform, join,
cleanse, enhance
data in cluster
with MapReduce
or Spark.
Complete
Data
Analytics,
Visualization,
Machine
Learning
12
Syncsort Published Lineage in Cloudera Navigator
13
Syncsort Published Lineage in Apache Atlas
Customer Single View
DMX Change Data Capture
Product News
14
Keep Your Data Fresh with Real-Time Change Data Capture
Keep data in sync in real-time
• Without overloading networks.
• Without affecting source database
performance.
• Without coding or tuning.
Reliable transfer of data you can trust even if connectivity fails on either side.
• Auto restart.
• No data loss.
Real-Time Replication
with Transformation
Conflict Resolution,
Collision Monitoring,
Tracking and Auditing
Files
RDBMS
Streams
Streams
RDBMS
Data
Lake
Mainframe
Cloud
OLAP
Real-Time Change Data Capture – New Sources and Targets
Sources
• IBM Db2 for z, i, LUW
• Apache Kafka
• VSAM
• IBM Informix
• MS SQL Server
• Oracle
• Oracle RAC
• Sybase
Targets
• Hive
• HDFS
• Apache Kafka
• Impala
• IBM Db2
• MS Azure SQL
• SQL Server
• PostgreSQL
• MySQL
• Oracle
• Oracle RAC
• Sybase
• Teradata
• Apache Kafka - Streaming
• Amazon Kinesis
17
Onboard Relational Data Quickly
• Extract, map and move whole DB schemas in one invocation
• Extract from Oracle, Db2, MS SQL Server, Teradata, Netezza and Redshift
• To SQL Server, Postgres, Hive, HDFS, Redshift and Amazon S3
• Automatically create target Hive and HCat tables
• Onboard hundreds of tables into your cluster
• Onboard whole database schemas at once
• Create target tables automatically in Hive
• Transform data in flight
• Filter unwanted:
o Tables
o Rows
o data types
o columns
DMX DataFunnel™
New Onboarding User Experience
DMX DataFunnel GUI Demo
18
19
THANK YOU!
Check out the DMX DataFunnel New User Experience Demo!
http://www.syncsort.com/en/Resource-Center/BigData/Videos/DMX-DataFunnel-New-User-Interface-Makes-Database

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What’s New in Syncsort Integrate? New User Experience for Fast Data Onboarding

  • 1. New Features Plus New Onboarding User Experience Paige Roberts, Integrate Product Marketing Manager Ashwin Ramachandran, Integrate Product Manager June 2018 1
  • 2. New Features Plus New Onboarding User Experience • Data Integration Product News • DataFunnel UI Demo • New Onboarding User Experience – DMX DataFunnel GUI • Where to Find Out More 1 Hive Improvements 2 Impala Support 3 Lineage 4 DMX Change Data Capture
  • 3. Disclaimer Any information about our roadmap outlines our general product direction and is subject to change at any time without notice. It is for informational purposes only and shall not, be incorporated into any contract or other commitment. Syncsort undertakes no obligation either to develop the features or functionality described or to include any such feature or functionality in a future release. 3
  • 5. 5 Hive Support Enhancements • JDBC connectivity • Support for partitioned tables: ORC, Parquet, AVRO, HDFS • Support for Truncate and Insert • Automatic creation of Hive and other Hcat supported tables • Direct distributed processing of Hive • Update of Hive statistics • Use Hive tables for lookups • Change data capture target • Hive ACID Merge support – Updates, inserts, deletes, and upserts in Hive • Full support for complex types – arrays, structs, etc. • Improved usability and support in mapping entire arrays, array elements and composite fields.
  • 6. 6 Cloudera Impala Support • JDBC connectivity • Both read and write support • Support for Impala tables backed by: Parquet, Kudu • Automatic creation of Impala tables • Direct distributed processing of Impala – on edge node, framework- designated node, or distributed on cluster with MapReduce or Spark • Update of Impala statistics • Use Impala tables for lookups • Full support for update and insert • Change data capture support
  • 9. 9 Govern and Track Everything for Compliance • Metadata and data lineage for Hive, Avro and Parquet through HCatalog • Metadata lineage export and REST API from DMX/DMX-h o Simplify audits, analytics dashboards, metrics o Integrate with enterprise metadata repositories • Cloudera Navigator certified integration o Audit and track data from source to cluster o HDFS, YARN, Spark and other metadata o Lineage, tagging o Business and structural metadata • Apache Atlas ingestion lineage integration o Audit and track data from source to cluster o Lineage, tagging
  • 10. 10 Onboard ALL Enterprise Data – Mainframe to Streaming Data Sources Onboard data, modify on-the-fly to match Hadoop storage model, or store unchanged for archive and compliance. Access data from streaming and batch sources outside cluster. Data Lake Data Transform, join, cleanse, enhance data in cluster with MapReduce or Spark. Analytics, Visualization, Machine Learning Complete Data Analytics, visualizations, and machine learning algorithms get ALL necessary data.
  • 11. 11 Get Source to Consumption, End-to-End Data Lineage Data Sources Auditors get end-to-end data lineage. Analytics, visualizations, and machine learning algorithms get ALL necessary data. Navigator or Atlas gathers any other changes made to data on cluster. Pass source-to- cluster data lineage info to Navigator or Atlas. Data Lake Data changes made by MapReduce, Spark, HiveQL. Data Data Lineage REST API Onboard data, modify on-the-fly to match Hadoop storage model, or store unchanged for archive and compliance. Access data from streaming and batch sources outside cluster. Transform, join, cleanse, enhance data in cluster with MapReduce or Spark. Complete Data Analytics, Visualization, Machine Learning
  • 12. 12 Syncsort Published Lineage in Cloudera Navigator
  • 13. 13 Syncsort Published Lineage in Apache Atlas Customer Single View
  • 14. DMX Change Data Capture Product News 14
  • 15. Keep Your Data Fresh with Real-Time Change Data Capture Keep data in sync in real-time • Without overloading networks. • Without affecting source database performance. • Without coding or tuning. Reliable transfer of data you can trust even if connectivity fails on either side. • Auto restart. • No data loss. Real-Time Replication with Transformation Conflict Resolution, Collision Monitoring, Tracking and Auditing Files RDBMS Streams Streams RDBMS Data Lake Mainframe Cloud OLAP
  • 16. Real-Time Change Data Capture – New Sources and Targets Sources • IBM Db2 for z, i, LUW • Apache Kafka • VSAM • IBM Informix • MS SQL Server • Oracle • Oracle RAC • Sybase Targets • Hive • HDFS • Apache Kafka • Impala • IBM Db2 • MS Azure SQL • SQL Server • PostgreSQL • MySQL • Oracle • Oracle RAC • Sybase • Teradata • Apache Kafka - Streaming • Amazon Kinesis
  • 17. 17 Onboard Relational Data Quickly • Extract, map and move whole DB schemas in one invocation • Extract from Oracle, Db2, MS SQL Server, Teradata, Netezza and Redshift • To SQL Server, Postgres, Hive, HDFS, Redshift and Amazon S3 • Automatically create target Hive and HCat tables • Onboard hundreds of tables into your cluster • Onboard whole database schemas at once • Create target tables automatically in Hive • Transform data in flight • Filter unwanted: o Tables o Rows o data types o columns DMX DataFunnel™
  • 18. New Onboarding User Experience DMX DataFunnel GUI Demo 18
  • 19. 19 THANK YOU! Check out the DMX DataFunnel New User Experience Demo! http://www.syncsort.com/en/Resource-Center/BigData/Videos/DMX-DataFunnel-New-User-Interface-Makes-Database