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© 2016, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Vidhya Srinivasan, General Manager, AWS
November 30th, 2016
What’s New with Amazon Redshift
“It’s our biggest driver of growth in our biggest markets, and is a feature of the
company” …on Data Mining in Redshift
– Chris Lambert, Lyft CTO
“The doors were blown wide open to create custom dashboards for anyone to
instantly go in and see and assess what is going in our ad delivery landscape,
something we have never been able to do until now.”
– Bryan Blair, Vevo’s VP of Ad Operations
“Analytical queries are 10 times faster in Amazon Redshift than they
were with our previous data warehouse.”
– Yuki Moritani, NTT Docomo Innovation Manager
“We have several petabytes of data and use a massive Redshift
cluster. Our data science team can get to the data faster and then
analyze that data to find new ways to reduce costs, market
products, and enable new business.”
– Yuki Moritani, NTT Docomo Innovation Manager
“We saw a 2x performance improvement on a wide variety of
workloads. The more complex the queries, the higher the
performance improvement..”
- Naeem Ali, Director of Software Development, Data
Science at Cablevision (Optimum)
“Over the last few years, we’ve tried all kinds of databases in search of more
speed, including $15k of custom hardware. Of everything we’ve tried,
Amazon Redshift won out each time.”
– Periscope Data, Analyst’s Guide to Redshift
“We took Amazon Redshift for a test run the moment it was
released. It’s fast. It’s easy. Did I mention it’s ridiculously fast?
We’re using it to provide our analysts an alternative to Hadoop.”
– Justin Yan, Data Scientist at Yelp
“The move to Redshift also significantly improved dashboard query
performance… Redshift performed ~200% faster than the
traditional SQL Server we had been using in the past.”
- Dean Donovan, Product Development at DiamondStream
“…[Redshift] performance has blown away everyone here (we
generally see 50-100x speedup over Hive)”
- Jie Li Data Infrastructure at Pinterest
“450,000 online queries 98 percent faster than previous traditional data
center, while reducing infrastructure costs by 80 percent.”
- John O’Donovan, CTO, Financial Times
“We needed to load six months' worth of data, about 10 TB of data, for a
campaign. That type of load would have taken about 20 days with our previous
solution. By using Amazon Redshift, it only took six hours to load the data.”
- Zhong Hong, VP of Infrastructure, Vivaki (Publicis Groupe)
“We regularly process multibillion row datasets and we do that in a
matter of hours. We are heading to up to 10 times more data volumes in
the next couple of years, easily.”
- Bob Harris, CTO, Channel 4
“On our previous big data warehouse system, it took around 45
minutes to run a query against a year of data, but that number went
down to just 25 seconds using Amazon Redshift”
- Kishore Raja Director of Strategic Programs and R&D, Boingo Wireless
“Most competing data warehousing solutions would have cost us up
to $1 million a year. By contrast, Amazon Redshift costs us just
$100,000 all-in, representing a total cost savings of around 90%”
- Joel Cumming, Head of Data, Kik Interactive
“Annual costs of Redshift are equivalent to just the annual
maintenance of some of the cheaper on-premises options for
data warehouses..”
- Kevin Diamond, CTO, HauteLook (Nordstrom)
“Our data volume keeps growing, and we can support that
growth because Amazon Redshift scales so well.. We wouldn’t
have that capability using the supporting on-premises hardware in
our previous solution.”
- Ajit Zadgaonkar, Director of Ops. and Infrastructure, Edmunds
“With Amazon Redshift and Tableau, anyone in the company can set up
any queries they like - from how users are reacting to a feature, to growth by
demographic or geography, to the impact sales efforts had in different areas”
- Jon Hoffman, Head of Engineering, Foursquare
BDA304
AWS Big Data Portfolio
Collect Store Analyze
Amazon Kinesis
Firehose
AWS Direct
Connect
Amazon
Snowball
Amazon
Kinesis Analytics
Amazon Kinesis
Streams
Amazon S3 Amazon Glacier
Amazon
CloudSearch
Amazon RDS,
Amazon Aurora
Amazon
Dynamo DB
Amazon Elasticsearch
Service
Amazon EMR Amazon EC2
Amazon
Redshift
Amazon Machine
Learning
Amazon
QuickSight
AWS Data PipelineAWS Database Migration Service
Legacy architectural models lead to dark data
0
200
400
600
800
1000
1200
Enterprise Data Data in Warehouse
Very Expensive
complicated
Slow at scale
Amazon Redshift
shift
Fast, simple, petabyte-scale data warehousing for $1,000/TB/Year
Amazon Redshift is fast
“Did I mention that it’s ridiculously fast? We’re using
it to provide our analysts with an alternative to Hadoop”
“After investigating Redshift, Snowflake, and
BigQuery, we found that Redshift offers top-of-the-
line performance at best-in-market price points”
“…[Redshift] performance has blown away everyone
here. We generally see 50-100X speedup over Hive”
“We regularly process multibillion row datasets
and we do that in a matter of hours. We are heading
to up to 10 times more data volumes in the next couple
of years, easily”
“We saw a 2X performance improvement on a wide
variety of workloads. The more complex the queries,
the higher the performance improvement”
“On our previous big data warehouse system, it took
around 45 minutes to run a query against a year of
data, but that number went down to just 25 seconds
using Amazon Redshift”
Amazon Redshift is easy to use
“With Amazon Redshift and Tableau, anyone in the
company can set up any queries they like - from how
users are reacting to a feature, to growth by demographic or
geography, to the impact sales efforts had in different areas”
“The doors were blown wide open to create custom
dashboards for anyone to instantly go in and see and
assess what is going in our ad delivery landscape,
something we have never been able to do until now.”
Provides an easy-to-use mechanism for querying data with
quick and uniform response times that analysts can use to
run research projects and perform in-depth analysis…We don’t
have to pre-allocate resources and can easily scale up to meet
demand and then scale down for efficiency”
Amazon Redshift is inexpensive
“450,000 online queries 98 percent faster than previous
traditional data center, while reducing infrastructure costs by
80 percent.”
“Annual costs of Redshift are equivalent to just the annual
maintenance of some of the cheaper on-premises options
for data warehouses..”
“Most competing data warehousing solutions would have cost
us up to $1 million a year. By contrast, Amazon Redshift costs
us just $100,000 all-in, representing a total cost savings of
around 90%”
Selected Amazon Redshift customers
Traditional Data Warehousing
Business
Reporting
Complex pipelines and
queries
Secure and
Compliant
Simple Migration – Point & Click using AWS Database Migration Service
Secure & Compliant – End-to-End Encryption. SOC 1/2/3, PCI-DSS, HIPAA and FedRAMP compliant
Large Ecosystem – Variety of cloud and on-premises BI and ETL tools
Japanese Mobile Phone
Provider
World’s Largest Children’s
Book Publisher
Powering 100 marketplaces in
50 countries
Bulk Loads and
Updates
Log Analysis
Log & Machine
IOT Data
Clickstream
Events Data
Time-Series
Data
Inexpensive – Analyze large volumes of data cost-effectively
Fast – Massively Parallel Processing (MPP) and columnar architecture for fast queries and parallel loads
Near real-time – Micro-batch loading and Amazon Kinesis Firehose for near-real time analytics
Interactive data analysis and
recommendation engine
Ride analytics for pricing and
product development
Ad prediction and on-demand
analytics
Business Applications
Multi-Tenant BI
Applications
Back-end
services
Analytics as a
Service
Fully Managed – Provisioning, backups, upgrades, security, compression all come built-in so you can focus on
your business applications
Simple Chargeback – Pay as you go, add clusters as needed. A few big common clusters, several data marts
Service Oriented Architecture – Integrated with other AWS services. Easy to plug into your pipeline
Infosys Information
Platform (IIP)
Analytics-as-a-
Service
Product and
Consumer Analytics
Thousands of companies run mission-critical
workloads on Amazon Redshift
Redshift is used for mission-critical workloads
Financial and
management reporting
Payments to suppliers
and billing workflows
Web/Mobile clickstream
and event analysis
Recommendation and
predictive analytics
Amazon Redshift is available everywhere AWS is
Dublin
Frankfurt
London
Seoul
Sydney
Tokyo
Singapore
Beijing
Mumbai
Sao Paulo
US East - Virginia
US West - Oregon
US West – Northern California
GovCloud
Columbus Ohio
Montreal
Currently Available
Coming soon
Redshift is fast and has gotten faster...
5X Query throughput improvement this year
 Memory allocation (launched)
 Improved commit and I/O logic (launched)
 Queue hopping (launched)
 Query monitoring rules (coming soon)
 Power start (coming soon)
 Short query bias (coming soon)
10X Vacuuming performance improvement
 Ensures data is sorted for efficient and fast I/O
 Reclaims space from deleted rows
 Enhanced vacuum performance leads to better system throughput
Fast
Efficient
Amazon Redshift Cluster
The life of a query
BI tools
SQL clients
Analytics tools
Client
Leader node
Compute node
Compute node
Compute node
Queue 1
Queue 2
1
4
32
Amazon Redshift Workload Management
Waiting
Coming soon: Short query bias
BI tools
SQL clients
Analytics tools
Client
Running
Queue 1
Queue 2
4 Slots
2 Slots
Short queries go to
the head of the
queue
1
1
Amazon Redshift Cluster
Coming soon: Power start
BI tools
SQL clients
Analytics tools
Client
Leader node
Compute node
Compute node
Compute node
All queries receive a
power start. Shorter
queries benefit the
most
2
2
2
2
Amazon Redshift Workload Management
Waiting
Queue hopping
BI tools
SQL clients
Analytics tools
Client
Running
Queue 1
Queue 2
4 Slots
2 Slots
Release slot if a query
exceeds timeout
3
3
Coming soon: Query monitoring rules
• Allows automatic handling of runaway (poorly written) queries
• Metrics with operators and values (e.g. query_cpu_time > 1000) create a predicate.
• Multiple predicates can be AND-ed together to create a rule.
• Multiple rules can be defined for a queue in WLM. These rules are OR-ed together.
If { rule } then [action]
{ rule : metric operator value } eg: rows_scanned > 100000
• Metric : cpu_time, query_blocks_read, rows scanned, query
execution time, cpu & io skew per slice, join_row_count, etc.
• Operator : <, >, ==
• Value : integer
[action] : hop, log, abort
Coming soon: Query monitoring rules
Monitor and control
cluster resources
consumed by a query
Get notified, abort and
reprioritize long-
running / bad queries
Pre-defined templates
for common use
cases
Amazon Redshift is easy to use
Provisioning in
minutes
Automatic Patching SQL - Data loading
Backups built-in Security is built-in Compression is built-in
And is getting easier…
Automatic and incremental background VACUUM (coming soon)
 Reclaims space and sorts when Redshift clusters are idle
 VACUUM is initiated when performance can be enhanced
 Improves ETL and query performance
Automatic data compression for CTAS
 CREATE TABLE AS (CTAS) command creates a new table
 The new table leverages compression automatically
Automatic compression for new tables (coming soon)
 All newly created tables will leverage default encoding
 Provides higher compression rates
010101010101
And is getting easier…
Enhanced localization
 Support for Timestamp with Time zone : New TIMESTAMPTZ data type to input complete timestamp values that
include the date, the time of day, and a time zone. Eg: 30 Nov 07:37:16 2016 PST
 Support for Multi-byte (UTF-8) characters for tables, columns, and other database object names
Resource management
 Connection limits: You can now set a limit on the number of database connections a user is permitted to have open
concurrently
 Query Monitoring rules (coming soon)
Table level restore
 Restore tables that you might have dropped accidentally
 Reconcile data from an older table that you might have updated or deleted unintentionally
Coming soon: Ingestion improvements
Faster migrations
 Schema Conversion Tool
 Already supports schema conversion from Oracle, Teradata, Netezza and Greenplum
 Coming soon: Support for Vertica and SQL Server
 AWS Database Migration Service
 Supports data migration with CDC from Oracle, SQL Server, PostgreSQL, MySQL and Aurora
 Will add more DW engines as sources
Data Loading
 Enhanced JSON & AVRO ingestion performance
Durability and availability
Automated Backups Cross-region backups Cluster-level mirroring
Streaming restore Monitoring Ticketing
Compute node
Durability
1. Multiple copies of a block within the cluster
2. Continuous and incremental backups to Amazon
S3 (automatic)
3. Continuous and incremental backups across
regions (checkbox enable)
4. Streaming restore – database is available for
query once metadata restored. Data streams
down in background or when queried. Enables
cross-AZ restores.
Amazon S3
Region 1
Region 2
Compute node Compute node
Amazon S3
1. Disk failures
2. Availability Zone failures
3. Region level failures
4. Node failures
Fault tolerance
Compute node
Amazon S3
Region 1
Region 2
Compute node Compute node
Amazon S3
Node fault tolerance
Leader nodeClient
Data-path monitoring agents
Compute node
Compute node
Compute node
Node level monitoring
can detect SW/HW
issues and take action
Node fault tolerance
Leader nodeClient
Data-path monitoring agents
Compute node
Compute node
Compute node
Failure is detected at one
of the compute nodes
Node fault tolerance
Leader nodeClient
Data-path monitoring agents
Compute node
Compute node
Compute node
Redshift parks the
connections
Next, the node is
replaced
Node fault tolerance
Leader nodeClient
Data-path monitoring agents
Compute node
Compute node
Compute node
Queries are re-submitted
(coming soon)
Node fault tolerance
Leader nodeClient
Data-path monitoring agents
Compute node
Compute node
Compute node
Cluster-level monitoring agents
Additional monitoring
layer for the leader
node and network
Amazon Redshift is secure
End-to-End
data encryption
Alerts and notifications Amazon VPC
AWS KMS and HSM Audit logging Certifications & Compliance
Leader node
Compute node
10 GigE
(HPC)
Ingestion
Backup
Restore
Customer VPC
Internal VPC
BI tools SQL clientsAnalytics tools
Compute node Compute node
JDBC/ODBC
 Load encrypted from S3
 SSL to secure data in transit
 ECDHE perfect forward secrecy
 Amazon VPC for network isolation
 Encryption to secure data at rest
 All blocks on disks and in S3 encrypted
 Block key, cluster key, master key (AES-256)
 On-premises HSM & AWS CloudHSM support
 Audit logging and AWS CloudTrail integration
 SOC 1/2/3, PCI-DSS, FedRAMP, BAA
Amazon Redshift is secure
Amazon S3 Amazon EMR Amazon Dynamo DB SSH
We have added even more security features...
IAM support for data LOAD/UNLOAD
 Use IAM roles to perform LOAD/UNLOAD operations
 Cluster is given IAM credentials
 Cluster can be granted access to specific S3 buckets
 Simplify credentials management
 More secure
Enhanced VPC Routing
 All query traffic only flows through customer VPC
 Strict data traffic management between Amazon Redshift and other data sources
Secure
Simple
BI tools SQL clientsAnalytics tools
Client AWS
Redshift
ADFS
Corporate
Directory IAM
User groups Individual user
Coming soon: IAM Authentication for DB users
Identity providers
IdP registers with
IAM
1
1
BI tools SQL clientsAnalytics tools
Client AWS
Redshift
ADFS
Corporate
Directory IAM
User groups Individual user
Single Sign-On
Coming soon: IAM Authentication for DB users
Identity providers
End-users can
leverage SSO
2
2
BI tools SQL clientsAnalytics tools
Client AWS
Redshift
ADFS
Corporate
Active Directory IAM
Amazon Redshift
ODBC/JDBC
User groups Individual user
Single Sign-On
Coming soon: IAM Authentication for DB users
Identity providers
New Redshift
ODBC/JDBC drivers.
Grab the ticket
(userid) and get a
SAML assertion
3
3
BI tools SQL clientsAnalytics tools
Client AWS
Redshift
ADFS
Corporate
Active Directory IAM
Amazon Redshift
ODBC/JDBC
User groups Individual user
Coming soon: IAM Authentication for DB users
Identity providers
Send SAML
assertion to IAM.
Obtain IAM role
credentials
4
4
BI tools SQL clientsAnalytics tools
Client AWS
Redshift
ADFS
Corporate
Active Directory IAM
Amazon Redshift
ODBC/JDBC
User groups Individual user
Coming soon: IAM Authentication for DB users
Identity providers
Use IAM role to
obtain temporary
cluster credentials.
Use temporary
credentials to log
into the database
5
5
Amazon Redshift
shift
Contact us at redshift-pm@amazon.com
Available now
 Queue hopping
 10X VACUUM performance improvement
 Node fault tolerance
 Enhanced VPC routing
 IAM support for Copy/Unload
 Auto compression for CTAS
 TimestampTZ datatype
Coming soon
 Query Monitoring rules
 Automatic and incremental background VACUUM
 Short query bias
 Power start
 IAM Authentication for DB users
 Auto compression for new tables
 Enhanced JSON & AVRO ingestion performance
Thank you!
Remember to complete
your evaluations!

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AWS re:Invent 2016: What’s New with Amazon Redshift (BDA304)

  • 1. © 2016, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Vidhya Srinivasan, General Manager, AWS November 30th, 2016 What’s New with Amazon Redshift “It’s our biggest driver of growth in our biggest markets, and is a feature of the company” …on Data Mining in Redshift – Chris Lambert, Lyft CTO “The doors were blown wide open to create custom dashboards for anyone to instantly go in and see and assess what is going in our ad delivery landscape, something we have never been able to do until now.” – Bryan Blair, Vevo’s VP of Ad Operations “Analytical queries are 10 times faster in Amazon Redshift than they were with our previous data warehouse.” – Yuki Moritani, NTT Docomo Innovation Manager “We have several petabytes of data and use a massive Redshift cluster. Our data science team can get to the data faster and then analyze that data to find new ways to reduce costs, market products, and enable new business.” – Yuki Moritani, NTT Docomo Innovation Manager “We saw a 2x performance improvement on a wide variety of workloads. The more complex the queries, the higher the performance improvement..” - Naeem Ali, Director of Software Development, Data Science at Cablevision (Optimum) “Over the last few years, we’ve tried all kinds of databases in search of more speed, including $15k of custom hardware. Of everything we’ve tried, Amazon Redshift won out each time.” – Periscope Data, Analyst’s Guide to Redshift “We took Amazon Redshift for a test run the moment it was released. It’s fast. It’s easy. Did I mention it’s ridiculously fast? We’re using it to provide our analysts an alternative to Hadoop.” – Justin Yan, Data Scientist at Yelp “The move to Redshift also significantly improved dashboard query performance… Redshift performed ~200% faster than the traditional SQL Server we had been using in the past.” - Dean Donovan, Product Development at DiamondStream “…[Redshift] performance has blown away everyone here (we generally see 50-100x speedup over Hive)” - Jie Li Data Infrastructure at Pinterest “450,000 online queries 98 percent faster than previous traditional data center, while reducing infrastructure costs by 80 percent.” - John O’Donovan, CTO, Financial Times “We needed to load six months' worth of data, about 10 TB of data, for a campaign. That type of load would have taken about 20 days with our previous solution. By using Amazon Redshift, it only took six hours to load the data.” - Zhong Hong, VP of Infrastructure, Vivaki (Publicis Groupe) “We regularly process multibillion row datasets and we do that in a matter of hours. We are heading to up to 10 times more data volumes in the next couple of years, easily.” - Bob Harris, CTO, Channel 4 “On our previous big data warehouse system, it took around 45 minutes to run a query against a year of data, but that number went down to just 25 seconds using Amazon Redshift” - Kishore Raja Director of Strategic Programs and R&D, Boingo Wireless “Most competing data warehousing solutions would have cost us up to $1 million a year. By contrast, Amazon Redshift costs us just $100,000 all-in, representing a total cost savings of around 90%” - Joel Cumming, Head of Data, Kik Interactive “Annual costs of Redshift are equivalent to just the annual maintenance of some of the cheaper on-premises options for data warehouses..” - Kevin Diamond, CTO, HauteLook (Nordstrom) “Our data volume keeps growing, and we can support that growth because Amazon Redshift scales so well.. We wouldn’t have that capability using the supporting on-premises hardware in our previous solution.” - Ajit Zadgaonkar, Director of Ops. and Infrastructure, Edmunds “With Amazon Redshift and Tableau, anyone in the company can set up any queries they like - from how users are reacting to a feature, to growth by demographic or geography, to the impact sales efforts had in different areas” - Jon Hoffman, Head of Engineering, Foursquare BDA304
  • 2. AWS Big Data Portfolio Collect Store Analyze Amazon Kinesis Firehose AWS Direct Connect Amazon Snowball Amazon Kinesis Analytics Amazon Kinesis Streams Amazon S3 Amazon Glacier Amazon CloudSearch Amazon RDS, Amazon Aurora Amazon Dynamo DB Amazon Elasticsearch Service Amazon EMR Amazon EC2 Amazon Redshift Amazon Machine Learning Amazon QuickSight AWS Data PipelineAWS Database Migration Service
  • 3. Legacy architectural models lead to dark data 0 200 400 600 800 1000 1200 Enterprise Data Data in Warehouse Very Expensive complicated Slow at scale
  • 4. Amazon Redshift shift Fast, simple, petabyte-scale data warehousing for $1,000/TB/Year
  • 5. Amazon Redshift is fast “Did I mention that it’s ridiculously fast? We’re using it to provide our analysts with an alternative to Hadoop” “After investigating Redshift, Snowflake, and BigQuery, we found that Redshift offers top-of-the- line performance at best-in-market price points” “…[Redshift] performance has blown away everyone here. We generally see 50-100X speedup over Hive” “We regularly process multibillion row datasets and we do that in a matter of hours. We are heading to up to 10 times more data volumes in the next couple of years, easily” “We saw a 2X performance improvement on a wide variety of workloads. The more complex the queries, the higher the performance improvement” “On our previous big data warehouse system, it took around 45 minutes to run a query against a year of data, but that number went down to just 25 seconds using Amazon Redshift”
  • 6. Amazon Redshift is easy to use “With Amazon Redshift and Tableau, anyone in the company can set up any queries they like - from how users are reacting to a feature, to growth by demographic or geography, to the impact sales efforts had in different areas” “The doors were blown wide open to create custom dashboards for anyone to instantly go in and see and assess what is going in our ad delivery landscape, something we have never been able to do until now.” Provides an easy-to-use mechanism for querying data with quick and uniform response times that analysts can use to run research projects and perform in-depth analysis…We don’t have to pre-allocate resources and can easily scale up to meet demand and then scale down for efficiency”
  • 7. Amazon Redshift is inexpensive “450,000 online queries 98 percent faster than previous traditional data center, while reducing infrastructure costs by 80 percent.” “Annual costs of Redshift are equivalent to just the annual maintenance of some of the cheaper on-premises options for data warehouses..” “Most competing data warehousing solutions would have cost us up to $1 million a year. By contrast, Amazon Redshift costs us just $100,000 all-in, representing a total cost savings of around 90%”
  • 9. Traditional Data Warehousing Business Reporting Complex pipelines and queries Secure and Compliant Simple Migration – Point & Click using AWS Database Migration Service Secure & Compliant – End-to-End Encryption. SOC 1/2/3, PCI-DSS, HIPAA and FedRAMP compliant Large Ecosystem – Variety of cloud and on-premises BI and ETL tools Japanese Mobile Phone Provider World’s Largest Children’s Book Publisher Powering 100 marketplaces in 50 countries Bulk Loads and Updates
  • 10. Log Analysis Log & Machine IOT Data Clickstream Events Data Time-Series Data Inexpensive – Analyze large volumes of data cost-effectively Fast – Massively Parallel Processing (MPP) and columnar architecture for fast queries and parallel loads Near real-time – Micro-batch loading and Amazon Kinesis Firehose for near-real time analytics Interactive data analysis and recommendation engine Ride analytics for pricing and product development Ad prediction and on-demand analytics
  • 11. Business Applications Multi-Tenant BI Applications Back-end services Analytics as a Service Fully Managed – Provisioning, backups, upgrades, security, compression all come built-in so you can focus on your business applications Simple Chargeback – Pay as you go, add clusters as needed. A few big common clusters, several data marts Service Oriented Architecture – Integrated with other AWS services. Easy to plug into your pipeline Infosys Information Platform (IIP) Analytics-as-a- Service Product and Consumer Analytics
  • 12. Thousands of companies run mission-critical workloads on Amazon Redshift
  • 13. Redshift is used for mission-critical workloads Financial and management reporting Payments to suppliers and billing workflows Web/Mobile clickstream and event analysis Recommendation and predictive analytics
  • 14. Amazon Redshift is available everywhere AWS is Dublin Frankfurt London Seoul Sydney Tokyo Singapore Beijing Mumbai Sao Paulo US East - Virginia US West - Oregon US West – Northern California GovCloud Columbus Ohio Montreal Currently Available Coming soon
  • 15. Redshift is fast and has gotten faster... 5X Query throughput improvement this year  Memory allocation (launched)  Improved commit and I/O logic (launched)  Queue hopping (launched)  Query monitoring rules (coming soon)  Power start (coming soon)  Short query bias (coming soon) 10X Vacuuming performance improvement  Ensures data is sorted for efficient and fast I/O  Reclaims space from deleted rows  Enhanced vacuum performance leads to better system throughput Fast Efficient
  • 16. Amazon Redshift Cluster The life of a query BI tools SQL clients Analytics tools Client Leader node Compute node Compute node Compute node Queue 1 Queue 2 1 4 32
  • 17. Amazon Redshift Workload Management Waiting Coming soon: Short query bias BI tools SQL clients Analytics tools Client Running Queue 1 Queue 2 4 Slots 2 Slots Short queries go to the head of the queue 1 1
  • 18. Amazon Redshift Cluster Coming soon: Power start BI tools SQL clients Analytics tools Client Leader node Compute node Compute node Compute node All queries receive a power start. Shorter queries benefit the most 2 2 2 2
  • 19. Amazon Redshift Workload Management Waiting Queue hopping BI tools SQL clients Analytics tools Client Running Queue 1 Queue 2 4 Slots 2 Slots Release slot if a query exceeds timeout 3 3
  • 20. Coming soon: Query monitoring rules • Allows automatic handling of runaway (poorly written) queries • Metrics with operators and values (e.g. query_cpu_time > 1000) create a predicate. • Multiple predicates can be AND-ed together to create a rule. • Multiple rules can be defined for a queue in WLM. These rules are OR-ed together. If { rule } then [action] { rule : metric operator value } eg: rows_scanned > 100000 • Metric : cpu_time, query_blocks_read, rows scanned, query execution time, cpu & io skew per slice, join_row_count, etc. • Operator : <, >, == • Value : integer [action] : hop, log, abort
  • 21. Coming soon: Query monitoring rules Monitor and control cluster resources consumed by a query Get notified, abort and reprioritize long- running / bad queries Pre-defined templates for common use cases
  • 22. Amazon Redshift is easy to use Provisioning in minutes Automatic Patching SQL - Data loading Backups built-in Security is built-in Compression is built-in
  • 23. And is getting easier… Automatic and incremental background VACUUM (coming soon)  Reclaims space and sorts when Redshift clusters are idle  VACUUM is initiated when performance can be enhanced  Improves ETL and query performance Automatic data compression for CTAS  CREATE TABLE AS (CTAS) command creates a new table  The new table leverages compression automatically Automatic compression for new tables (coming soon)  All newly created tables will leverage default encoding  Provides higher compression rates 010101010101
  • 24. And is getting easier… Enhanced localization  Support for Timestamp with Time zone : New TIMESTAMPTZ data type to input complete timestamp values that include the date, the time of day, and a time zone. Eg: 30 Nov 07:37:16 2016 PST  Support for Multi-byte (UTF-8) characters for tables, columns, and other database object names Resource management  Connection limits: You can now set a limit on the number of database connections a user is permitted to have open concurrently  Query Monitoring rules (coming soon) Table level restore  Restore tables that you might have dropped accidentally  Reconcile data from an older table that you might have updated or deleted unintentionally
  • 25. Coming soon: Ingestion improvements Faster migrations  Schema Conversion Tool  Already supports schema conversion from Oracle, Teradata, Netezza and Greenplum  Coming soon: Support for Vertica and SQL Server  AWS Database Migration Service  Supports data migration with CDC from Oracle, SQL Server, PostgreSQL, MySQL and Aurora  Will add more DW engines as sources Data Loading  Enhanced JSON & AVRO ingestion performance
  • 26. Durability and availability Automated Backups Cross-region backups Cluster-level mirroring Streaming restore Monitoring Ticketing
  • 27. Compute node Durability 1. Multiple copies of a block within the cluster 2. Continuous and incremental backups to Amazon S3 (automatic) 3. Continuous and incremental backups across regions (checkbox enable) 4. Streaming restore – database is available for query once metadata restored. Data streams down in background or when queried. Enables cross-AZ restores. Amazon S3 Region 1 Region 2 Compute node Compute node Amazon S3
  • 28. 1. Disk failures 2. Availability Zone failures 3. Region level failures 4. Node failures Fault tolerance Compute node Amazon S3 Region 1 Region 2 Compute node Compute node Amazon S3
  • 29. Node fault tolerance Leader nodeClient Data-path monitoring agents Compute node Compute node Compute node Node level monitoring can detect SW/HW issues and take action
  • 30. Node fault tolerance Leader nodeClient Data-path monitoring agents Compute node Compute node Compute node Failure is detected at one of the compute nodes
  • 31. Node fault tolerance Leader nodeClient Data-path monitoring agents Compute node Compute node Compute node Redshift parks the connections Next, the node is replaced
  • 32. Node fault tolerance Leader nodeClient Data-path monitoring agents Compute node Compute node Compute node Queries are re-submitted (coming soon)
  • 33. Node fault tolerance Leader nodeClient Data-path monitoring agents Compute node Compute node Compute node Cluster-level monitoring agents Additional monitoring layer for the leader node and network
  • 34. Amazon Redshift is secure End-to-End data encryption Alerts and notifications Amazon VPC AWS KMS and HSM Audit logging Certifications & Compliance
  • 35. Leader node Compute node 10 GigE (HPC) Ingestion Backup Restore Customer VPC Internal VPC BI tools SQL clientsAnalytics tools Compute node Compute node JDBC/ODBC  Load encrypted from S3  SSL to secure data in transit  ECDHE perfect forward secrecy  Amazon VPC for network isolation  Encryption to secure data at rest  All blocks on disks and in S3 encrypted  Block key, cluster key, master key (AES-256)  On-premises HSM & AWS CloudHSM support  Audit logging and AWS CloudTrail integration  SOC 1/2/3, PCI-DSS, FedRAMP, BAA Amazon Redshift is secure Amazon S3 Amazon EMR Amazon Dynamo DB SSH
  • 36. We have added even more security features... IAM support for data LOAD/UNLOAD  Use IAM roles to perform LOAD/UNLOAD operations  Cluster is given IAM credentials  Cluster can be granted access to specific S3 buckets  Simplify credentials management  More secure Enhanced VPC Routing  All query traffic only flows through customer VPC  Strict data traffic management between Amazon Redshift and other data sources Secure Simple
  • 37. BI tools SQL clientsAnalytics tools Client AWS Redshift ADFS Corporate Directory IAM User groups Individual user Coming soon: IAM Authentication for DB users Identity providers IdP registers with IAM 1 1
  • 38. BI tools SQL clientsAnalytics tools Client AWS Redshift ADFS Corporate Directory IAM User groups Individual user Single Sign-On Coming soon: IAM Authentication for DB users Identity providers End-users can leverage SSO 2 2
  • 39. BI tools SQL clientsAnalytics tools Client AWS Redshift ADFS Corporate Active Directory IAM Amazon Redshift ODBC/JDBC User groups Individual user Single Sign-On Coming soon: IAM Authentication for DB users Identity providers New Redshift ODBC/JDBC drivers. Grab the ticket (userid) and get a SAML assertion 3 3
  • 40. BI tools SQL clientsAnalytics tools Client AWS Redshift ADFS Corporate Active Directory IAM Amazon Redshift ODBC/JDBC User groups Individual user Coming soon: IAM Authentication for DB users Identity providers Send SAML assertion to IAM. Obtain IAM role credentials 4 4
  • 41. BI tools SQL clientsAnalytics tools Client AWS Redshift ADFS Corporate Active Directory IAM Amazon Redshift ODBC/JDBC User groups Individual user Coming soon: IAM Authentication for DB users Identity providers Use IAM role to obtain temporary cluster credentials. Use temporary credentials to log into the database 5 5
  • 42. Amazon Redshift shift Contact us at redshift-pm@amazon.com Available now  Queue hopping  10X VACUUM performance improvement  Node fault tolerance  Enhanced VPC routing  IAM support for Copy/Unload  Auto compression for CTAS  TimestampTZ datatype Coming soon  Query Monitoring rules  Automatic and incremental background VACUUM  Short query bias  Power start  IAM Authentication for DB users  Auto compression for new tables  Enhanced JSON & AVRO ingestion performance