SlideShare a Scribd company logo
RRain	
  
1	
  
Archive	
  is	
  a	
  No	
  Brainer	
  
	
  
Speakers	
  &	
  Topics	
  
2	
  
Philip Howard,
Research Director
Bloor
Deirdre Mahon,
VP Marketing
RainStor
§  	
  What	
  is	
  an	
  Archive	
  
§  	
  Industry	
  Trends	
  
§  	
  Key	
  Requirements	
  
§  	
  Best	
  Prac>ces	
  
§  	
  Customer	
  Examples	
  
Database archiving
Philip Howard
Research Director, Bloor Research
telling the right storyConfidential © Bloor Research 2013
Agenda
" What is database archiving?
" Why is it increasingly important?
" What sort of features do you need?
" What trends do we see and what
differentiates products?
telling the right storyConfidential © Bloor Research 2013
What is database archiving?
Online, low cost, highly compressed storage
that requires no change to access methods
Not back-up
Not e-mail archive
Not CSV or XML files
telling the right storyConfidential © Bloor Research 2013
Two scenarios
Access support for
originating application
SQL support
telling the right storyConfidential © Bloor Research 2013
Why is database archiving
increasingly on the agenda?
" Availability of cloud-based
archiving
" Availability of Hadoop/HDFS-
based archiving
" Synergy with data migration
telling the right storyConfidential © Bloor Research 2013
What you need 1
You need to know what data to archive
telling the right storyConfidential © Bloor Research 2013
What you need 2
You don’t just archive a record, you archive all the other data related to
that record – to preserve referential integrity – which means discovering
and understanding business entities in their entirety.
telling the right storyConfidential © Bloor Research 2013
What you need 3
" High compression rates
" Low cost storage
telling the right storyConfidential © Bloor Research 2013
What you need 4
Loading
and
access
Without indexes
telling the right storyConfidential © Bloor Research 2013
What you need 5
Information Lifecycle Management not Industrial Light & Magic
telling the right storyConfidential © Bloor Research 2013
What you need 6
telling the right storyConfidential © Bloor Research 2013
The trend towards Hadoop
But Hadoop/HDFS is insufficient on its own
because the compression is not good enough
and neither is the security
telling the right storyConfidential © Bloor Research 2013
Other trends
" Compression will (almost) become
commoditised (but not yet)
" Deployments will built on top of Hadoop/
HDFS or in the cloud (or both)
" In data warehousing environments data
virtualisation (federation) will be used to
interconnect warehouses, marts and archives
" Differentiation will focus on:
" Ease of establishing what data to archive
" Performance – both for loading and retrieval
telling the right storyConfidential © Bloor Research 2013
Conclusion
" Database archiving looks more and more like
a mandatory activity
" DIY approaches won’t cut it because of
a) the work involved and
b) because you won’t get either the cost
savings or performance you could do
" Deployments will increasingly be on low-cost
clustered hardware or in the cloud
telling the right storyConfidential © Bloor Research 2013
RainStor®	
  
18	
  
Create	
  Value	
  from	
  Your	
  Historical	
  Data	
  	
  
and	
  Meet	
  Regulatory	
  Demands.	
  
The	
  Data	
  Archive	
  
RainStor®	
  -­‐	
  Proven	
  
19	
  
20	
  of	
  	
  
World’s	
  Largest	
  
Communica>ons	
  
Providers	
  
15	
  Strategic	
  	
  
Solu>on	
  &	
  	
  
Technology	
  	
  
Partners	
  
10	
  of	
  	
  
World’s	
  Biggest	
  
Banks	
  &	
  Financial	
  
Ins>tu>ons	
  
	
  
Drivers	
  &	
  Business	
  Challenges	
  Solved	
  
20	
  
10X	
  ReducGon	
  
(Compared	
  to	
  tradi>onal)	
  	
  
Cost	
  
Deployed	
  in	
  90	
  Days	
  
(End-­‐to-­‐end	
  Solu>on)	
  
Complexity	
  
Meets	
  &	
  Exceeds	
  
(Industry	
  &	
  Regulatory)	
  Compliance	
  
Historical	
  AnalyGcs	
  
(Standards-­‐based)	
  
Create	
  
Value	
  
Archive	
  Solu>ons	
  
Analy>cal	
  Archive	
  
Compliance	
  Archive	
  
21	
  
Comply
Analy>cal	
  Archive:	
  End-­‐to-­‐end	
  
QUERY/	
  
ANALYZE	
  
SQL	
  
BI	
  Tools;	
  Hive,	
  
MapReduce	
  	
  
SCALE	
  -­‐	
  Any	
  PlaWorm	
  
COMPRESS	
  LOAD/	
  
VALIDATE	
  
Billions	
  
Records/Day	
  
10-­‐40X	
  
(90%+)	
  
AVAILABILITY	
  
ReplicaGon	
  
DW	
  
Source	
  
Move	
  
RETAIN	
  /
DISPOSE	
  
Rules	
  
Based	
  
IN	
   STORE	
   QUERY	
   GOVERN	
  
SECURE	
  -­‐	
  Enterprise-­‐grade	
  
	
  	
  
Analy>cal	
  Archive	
  -­‐	
  Key	
  Capabili>es	
  
23	
  
QUERY	
   GOVERN	
  
§  Standard	
  SQL	
  92,	
  99	
  
§  MapReduce,	
  Pig,	
  Hive	
  
§  BI	
  Tools	
  
§  Rules	
  based	
  Data	
  Disposi>on	
  
§  WORM	
  (17a-­‐4)	
  
§  Legal	
  Hold	
  
§  Record-­‐level	
  Reten>on	
  
§  Audit	
  Trail	
  
DATA	
  IN	
  
§  Works	
  with	
  standard	
  ETL	
  
§  ODBC/JDBC	
  Compa>ble	
  
§  FastConnect™	
  for	
  Teradata	
  
§  Validate	
  -­‐	
  Fingerprint	
  
STORE	
  
§  Compression	
  -­‐	
  20-­‐40X	
  
§  Immutable	
  Data	
  Model	
  
§  Encryp>on	
  &	
  Masking	
  
§  Authen>ca>on	
  
§  Schema	
  Evolu>on	
  
CAPACITY	
  BUY-­‐BACK	
  
INSTANT	
  ACCESS	
   NO	
  FINES	
  
SAVE	
  YOU	
  MONEY	
  
Fits	
  with	
  Your	
  Enterprise	
  
24	
  
EDW’S	
  
Deployment	
  PlaWorms	
  
Scale-­‐out	
  	
  NAS	
  
HDFS	
  	
  
Cluster	
  /	
  DAS	
  
Cloud	
  
Worm	
  
Teradata	
  -­‐	
  Analy>cal	
  Archive	
  Solu>on	
  
QUERY/	
  
ANALYZE	
  
SQL	
  
BI	
  Tools;	
  Hive,	
  
MapReduce	
  	
  
SCALE	
  -­‐	
  Any	
  PlaWorm	
  
COMPRESS	
  LOAD/	
  
VALIDATE	
  
Billions	
  
Records/Day	
  
10-­‐40X	
  
(90%+)	
  
AVAILABILITY	
  
ReplicaGon	
  
TERADATA	
  
FastConnect™	
  
RETAIN	
  /
DISPOSE	
  
Rules	
  
Based	
  
GOVERN	
  
SECURE	
  -­‐	
  Enterprise-­‐grade	
  
	
  	
  
FastForward™	
  
SEC	
  17a-­‐4(f)	
  Compliance	
  Archive	
  Requirements	
  
26	
  
Records	
  stored	
  in	
  non-­‐eraseable	
  media	
  (WORM)	
  
Recording	
  process	
  must	
  be	
  verifiable	
  
Fully	
  Accessible	
  to	
  AuthoriGes	
  &	
  Backed-­‐up	
  
Records	
  should	
  be	
  Recognizable	
  &	
  IdenGfiable	
  
Downloadable	
  to	
  any	
  acceptable	
  medium	
  	
  
27	
  
Global	
  Financial	
  Services	
  
Lower	
  Compliant	
  Data	
  Reten>on	
  Costs	
  by	
  a	
  Decimal	
  Point!	
  
Challenges	
  
§  Cost:	
  Data	
  volumes	
  in	
  disparate	
  trading	
  
applica>ons	
  growing	
  at	
  70-­‐100%	
  /	
  Year	
  -­‐	
  Storage	
  
costs	
  rising	
  @	
  60%	
  /	
  Year	
  
§  Compliance:	
  Must	
  provide	
  performant	
  EBS	
  and	
  
other	
  queries	
  for	
  SEC	
  
	
  
SoluGon	
  
§  A	
  RainStor	
  Archive	
  for	
  storing	
  and	
  repor>ng	
  
against	
  historical	
  trade	
  data	
  
§  13	
  years	
  of	
  history	
  loaded	
  from	
  Sybase	
  IQ	
  
§  Daily	
  feed	
  from	
  trading	
  applica>on	
  to	
  RainStor	
  
§  Runs	
  on	
  low-­‐cost	
  NAS	
  Tier	
  3	
  storage	
  and	
  VMs	
  
§  RainStor	
  completely	
  replaced	
  Sybase	
  IQ	
  
ü  90%	
  cost	
  savings	
  -­‐	
  $5M	
  ROI	
  
ü  6	
  Projects	
  live	
  -­‐	
  13	
  more	
  in	
  
progress.	
  
90%	
  
Storage	
  Cost	
  
Reduc>on	
  
“ It’s like shrink-wrapping your
data…forever!”
	
  –	
  VP,	
  Technology	
  
Benefits	
  
ü  30X	
  Data	
  Compression 	
   	
  	
  
ü  3X	
  Faster	
  Query	
  Compared	
  to	
  Sybase	
  
28	
  
	
  
Retain	
  Cri>cal	
  Analy>cs	
  Data	
  at	
  Lowest	
  Cost	
  
	
  
§  Ini>ally	
  60TB	
  Offload	
  
	
  Business	
  &	
  
	
  Compliance	
  Queries	
  
§  Run	
  Na>vely	
  on	
  
Hadoop	
  
	
  SQL	
  +	
  MapReduce	
  	
  
40X	
  Compression	
  
RAINSTOR	
  SOLUTION:	
  	
  Offload	
  Historical	
  Data	
  from	
  Teradata	
  to	
  RainStor	
  
Meets	
  SLAs	
  for	
  Business	
  Query	
  	
   Savings	
  on	
  TD	
  Licenses	
  
Capacity	
  Buy-­‐Back	
  -­‐	
  $Millions	
  Saved	
  on	
  Sopware	
  &	
  Hardware	
  
Enterprise	
  DW	
  
FastConnect™	
  
Dell	
  Servers	
  	
  
R720s	
  
Cloudera	
  Hadoop	
  
400TB	
  
ü ü ü
§  Gone	
  through	
  the	
  pain	
  so	
  you	
  don't	
  have	
  to.	
  
–  Crea>ng	
  an	
  archive	
  is	
  not	
  easy!	
  
–  RainStor	
  Makes	
  it	
  simple,	
  cost	
  effec>ve,	
  compliant-­‐ready	
  &	
  fast	
  to	
  deploy	
  
§  Solving	
  archiving	
  problems	
  for	
  world	
  leaders	
  -­‐	
  10	
  years	
  
of	
  proven	
  experience.	
  
–  Enabled	
  customers	
  to	
  deploy	
  cost	
  efficiently	
  without	
  compromise	
  	
  
–  Support	
  and	
  service	
  rated	
  as	
  world	
  class	
  by	
  our	
  customers	
  
§  Technology	
  soluGons	
  that	
  create	
  business	
  value.	
  
–  Transforms	
  archiving	
  to	
  be	
  a	
  strategic	
  asset.	
  
Why	
  RainStor®	
  
 	
   	
   	
  	
   	
  Thank	
  You	
  
30	
  
Archive	
  is	
  a	
  
No	
  Brainer	
  

More Related Content

What's hot

An introduction to Big Data
An introduction to Big DataAn introduction to Big Data
An introduction to Big Data
ForwardSprint
 
IMCSummit 2015 - Day 2 Developer Track - The Internet of Analytics – Discover...
IMCSummit 2015 - Day 2 Developer Track - The Internet of Analytics – Discover...IMCSummit 2015 - Day 2 Developer Track - The Internet of Analytics – Discover...
IMCSummit 2015 - Day 2 Developer Track - The Internet of Analytics – Discover...
In-Memory Computing Summit
 
Introduction to Kudu - StampedeCon 2016
Introduction to Kudu - StampedeCon 2016Introduction to Kudu - StampedeCon 2016
Introduction to Kudu - StampedeCon 2016
StampedeCon
 
Nov 2010 HUG: Business Intelligence for Big Data
Nov 2010 HUG: Business Intelligence for Big DataNov 2010 HUG: Business Intelligence for Big Data
Nov 2010 HUG: Business Intelligence for Big Data
Yahoo Developer Network
 
Next Generation Hadoop Introduction
Next Generation Hadoop IntroductionNext Generation Hadoop Introduction
Next Generation Hadoop Introduction
Adam Muise
 
Data Warehouse Optimization
Data Warehouse OptimizationData Warehouse Optimization
Data Warehouse Optimization
Cloudera, Inc.
 
start_your_datacenter_sds_v3
start_your_datacenter_sds_v3start_your_datacenter_sds_v3
start_your_datacenter_sds_v3
David Byte
 
Empowering you with Democratized Data Access, Data Science and Machine Learning
Empowering you with Democratized Data Access, Data Science and Machine LearningEmpowering you with Democratized Data Access, Data Science and Machine Learning
Empowering you with Democratized Data Access, Data Science and Machine Learning
DataWorks Summit
 
Why hadoop for data science?
Why hadoop for data science?Why hadoop for data science?
Why hadoop for data science?
Hortonworks
 
DataStax Training – Everything you need to become a Cassandra Rockstar
DataStax Training – Everything you need to become a Cassandra RockstarDataStax Training – Everything you need to become a Cassandra Rockstar
DataStax Training – Everything you need to become a Cassandra Rockstar
DataStax
 
Hadoop Reporting and Analysis - Jaspersoft
Hadoop Reporting and Analysis - JaspersoftHadoop Reporting and Analysis - Jaspersoft
Hadoop Reporting and Analysis - Jaspersoft
Hortonworks
 
Accelerating workloads and bursting data with Google Dataproc & Alluxio
Accelerating workloads and bursting data with Google Dataproc & AlluxioAccelerating workloads and bursting data with Google Dataproc & Alluxio
Accelerating workloads and bursting data with Google Dataproc & Alluxio
Alluxio, Inc.
 
Standing Up an Effective Enterprise Data Hub -- Technology and Beyond
Standing Up an Effective Enterprise Data Hub -- Technology and BeyondStanding Up an Effective Enterprise Data Hub -- Technology and Beyond
Standing Up an Effective Enterprise Data Hub -- Technology and Beyond
Cloudera, Inc.
 
Webinar | From Zero to 1 Million with Google Cloud Platform and DataStax
Webinar | From Zero to 1 Million with Google Cloud Platform and DataStaxWebinar | From Zero to 1 Million with Google Cloud Platform and DataStax
Webinar | From Zero to 1 Million with Google Cloud Platform and DataStax
DataStax
 
Key trends in Big Data and new reference architecture from Hewlett Packard En...
Key trends in Big Data and new reference architecture from Hewlett Packard En...Key trends in Big Data and new reference architecture from Hewlett Packard En...
Key trends in Big Data and new reference architecture from Hewlett Packard En...
Ontico
 
Cloudera Breakfast Series, Analytics Part 1: Use All Your Data
Cloudera Breakfast Series, Analytics Part 1: Use All Your DataCloudera Breakfast Series, Analytics Part 1: Use All Your Data
Cloudera Breakfast Series, Analytics Part 1: Use All Your Data
Cloudera, Inc.
 
Big data on Azure for Architects
Big data on Azure for ArchitectsBig data on Azure for Architects
Big data on Azure for Architects
Tomasz Kopacz
 
Rob peglar introduction_analytics _big data_hadoop
Rob peglar introduction_analytics _big data_hadoopRob peglar introduction_analytics _big data_hadoop
Rob peglar introduction_analytics _big data_hadoop
Ghassan Al-Yafie
 
Innovation in the Data Warehouse - StampedeCon 2016
Innovation in the Data Warehouse - StampedeCon 2016Innovation in the Data Warehouse - StampedeCon 2016
Innovation in the Data Warehouse - StampedeCon 2016
StampedeCon
 
Big Data/Hadoop Infrastructure Considerations
Big Data/Hadoop Infrastructure ConsiderationsBig Data/Hadoop Infrastructure Considerations
Big Data/Hadoop Infrastructure Considerations
Richard McDougall
 

What's hot (20)

An introduction to Big Data
An introduction to Big DataAn introduction to Big Data
An introduction to Big Data
 
IMCSummit 2015 - Day 2 Developer Track - The Internet of Analytics – Discover...
IMCSummit 2015 - Day 2 Developer Track - The Internet of Analytics – Discover...IMCSummit 2015 - Day 2 Developer Track - The Internet of Analytics – Discover...
IMCSummit 2015 - Day 2 Developer Track - The Internet of Analytics – Discover...
 
Introduction to Kudu - StampedeCon 2016
Introduction to Kudu - StampedeCon 2016Introduction to Kudu - StampedeCon 2016
Introduction to Kudu - StampedeCon 2016
 
Nov 2010 HUG: Business Intelligence for Big Data
Nov 2010 HUG: Business Intelligence for Big DataNov 2010 HUG: Business Intelligence for Big Data
Nov 2010 HUG: Business Intelligence for Big Data
 
Next Generation Hadoop Introduction
Next Generation Hadoop IntroductionNext Generation Hadoop Introduction
Next Generation Hadoop Introduction
 
Data Warehouse Optimization
Data Warehouse OptimizationData Warehouse Optimization
Data Warehouse Optimization
 
start_your_datacenter_sds_v3
start_your_datacenter_sds_v3start_your_datacenter_sds_v3
start_your_datacenter_sds_v3
 
Empowering you with Democratized Data Access, Data Science and Machine Learning
Empowering you with Democratized Data Access, Data Science and Machine LearningEmpowering you with Democratized Data Access, Data Science and Machine Learning
Empowering you with Democratized Data Access, Data Science and Machine Learning
 
Why hadoop for data science?
Why hadoop for data science?Why hadoop for data science?
Why hadoop for data science?
 
DataStax Training – Everything you need to become a Cassandra Rockstar
DataStax Training – Everything you need to become a Cassandra RockstarDataStax Training – Everything you need to become a Cassandra Rockstar
DataStax Training – Everything you need to become a Cassandra Rockstar
 
Hadoop Reporting and Analysis - Jaspersoft
Hadoop Reporting and Analysis - JaspersoftHadoop Reporting and Analysis - Jaspersoft
Hadoop Reporting and Analysis - Jaspersoft
 
Accelerating workloads and bursting data with Google Dataproc & Alluxio
Accelerating workloads and bursting data with Google Dataproc & AlluxioAccelerating workloads and bursting data with Google Dataproc & Alluxio
Accelerating workloads and bursting data with Google Dataproc & Alluxio
 
Standing Up an Effective Enterprise Data Hub -- Technology and Beyond
Standing Up an Effective Enterprise Data Hub -- Technology and BeyondStanding Up an Effective Enterprise Data Hub -- Technology and Beyond
Standing Up an Effective Enterprise Data Hub -- Technology and Beyond
 
Webinar | From Zero to 1 Million with Google Cloud Platform and DataStax
Webinar | From Zero to 1 Million with Google Cloud Platform and DataStaxWebinar | From Zero to 1 Million with Google Cloud Platform and DataStax
Webinar | From Zero to 1 Million with Google Cloud Platform and DataStax
 
Key trends in Big Data and new reference architecture from Hewlett Packard En...
Key trends in Big Data and new reference architecture from Hewlett Packard En...Key trends in Big Data and new reference architecture from Hewlett Packard En...
Key trends in Big Data and new reference architecture from Hewlett Packard En...
 
Cloudera Breakfast Series, Analytics Part 1: Use All Your Data
Cloudera Breakfast Series, Analytics Part 1: Use All Your DataCloudera Breakfast Series, Analytics Part 1: Use All Your Data
Cloudera Breakfast Series, Analytics Part 1: Use All Your Data
 
Big data on Azure for Architects
Big data on Azure for ArchitectsBig data on Azure for Architects
Big data on Azure for Architects
 
Rob peglar introduction_analytics _big data_hadoop
Rob peglar introduction_analytics _big data_hadoopRob peglar introduction_analytics _big data_hadoop
Rob peglar introduction_analytics _big data_hadoop
 
Innovation in the Data Warehouse - StampedeCon 2016
Innovation in the Data Warehouse - StampedeCon 2016Innovation in the Data Warehouse - StampedeCon 2016
Innovation in the Data Warehouse - StampedeCon 2016
 
Big Data/Hadoop Infrastructure Considerations
Big Data/Hadoop Infrastructure ConsiderationsBig Data/Hadoop Infrastructure Considerations
Big Data/Hadoop Infrastructure Considerations
 

Viewers also liked

Why Consider #FlashStorage in your #DataCenter
Why Consider #FlashStorage in your #DataCenterWhy Consider #FlashStorage in your #DataCenter
Why Consider #FlashStorage in your #DataCenter
Tegile Systems
 
Pramata Tech Dinosaurs ePaper - Social Sharing
Pramata Tech Dinosaurs ePaper - Social SharingPramata Tech Dinosaurs ePaper - Social Sharing
Pramata Tech Dinosaurs ePaper - Social Sharing
Tidemark Systems Inc.
 
Getting started with performance testing
Getting started with performance testingGetting started with performance testing
Getting started with performance testing
Testplant
 
Running SagePFW in a Private Cloud
Running SagePFW in a Private CloudRunning SagePFW in a Private Cloud
Running SagePFW in a Private Cloud
Vertical Solutions
 
Rsa2012 下一代安全的战略思考-绿盟科技赵粮
Rsa2012 下一代安全的战略思考-绿盟科技赵粮Rsa2012 下一代安全的战略思考-绿盟科技赵粮
Rsa2012 下一代安全的战略思考-绿盟科技赵粮
NSFOCUS
 
Wedia Social Media presentation at DigitalDays
Wedia Social Media presentation at DigitalDaysWedia Social Media presentation at DigitalDays
Wedia Social Media presentation at DigitalDays
Panos Kontopoulos
 
Innovation In The Workplace Andrew James
Innovation In The Workplace   Andrew JamesInnovation In The Workplace   Andrew James
Innovation In The Workplace Andrew James
Konica Minolta
 
Top 10 Business Continuity Disasters
Top 10 Business Continuity DisastersTop 10 Business Continuity Disasters
Top 10 Business Continuity Disasters
Rentsys Recovery Services
 
Visual Studio 2013 - Recursos da IDE
Visual Studio 2013 - Recursos da IDEVisual Studio 2013 - Recursos da IDE
Visual Studio 2013 - Recursos da IDE
Stefanini
 
New Research: Cloud, Cost & Complexity Impact IAM & IT
New Research: Cloud, Cost & Complexity Impact IAM & ITNew Research: Cloud, Cost & Complexity Impact IAM & IT
New Research: Cloud, Cost & Complexity Impact IAM & IT
Symplified
 
Dr Ravi Gupta
Dr Ravi GuptaDr Ravi Gupta
5 Reasons to Recycle in the D.C. Metro Area
5 Reasons to Recycle in the D.C. Metro Area5 Reasons to Recycle in the D.C. Metro Area
5 Reasons to Recycle in the D.C. Metro Area
Sims Recycling Solutions
 
TXT Next Presentation
TXT Next Presentation TXT Next Presentation
TXT Next Presentation
TXT e-solutions
 
Perceptive Software Scope
Perceptive Software ScopePerceptive Software Scope
Perceptive Software Scope
Perceptive Software Pty Ltd
 
Presence Agent y Presence Scripting para personas con limitaciones visuales
Presence Agent y Presence Scripting para personas con limitaciones visualesPresence Agent y Presence Scripting para personas con limitaciones visuales
Presence Agent y Presence Scripting para personas con limitaciones visuales
Presence Technology
 
Enriched Insights in Finance: Blending Data, Boosting Performance
Enriched Insights in Finance: Blending Data, Boosting PerformanceEnriched Insights in Finance: Blending Data, Boosting Performance
Enriched Insights in Finance: Blending Data, Boosting Performance
Prophix Software
 

Viewers also liked (17)

Why Consider #FlashStorage in your #DataCenter
Why Consider #FlashStorage in your #DataCenterWhy Consider #FlashStorage in your #DataCenter
Why Consider #FlashStorage in your #DataCenter
 
Pramata Tech Dinosaurs ePaper - Social Sharing
Pramata Tech Dinosaurs ePaper - Social SharingPramata Tech Dinosaurs ePaper - Social Sharing
Pramata Tech Dinosaurs ePaper - Social Sharing
 
Getting started with performance testing
Getting started with performance testingGetting started with performance testing
Getting started with performance testing
 
Running SagePFW in a Private Cloud
Running SagePFW in a Private CloudRunning SagePFW in a Private Cloud
Running SagePFW in a Private Cloud
 
Rsa2012 下一代安全的战略思考-绿盟科技赵粮
Rsa2012 下一代安全的战略思考-绿盟科技赵粮Rsa2012 下一代安全的战略思考-绿盟科技赵粮
Rsa2012 下一代安全的战略思考-绿盟科技赵粮
 
Wedia Social Media presentation at DigitalDays
Wedia Social Media presentation at DigitalDaysWedia Social Media presentation at DigitalDays
Wedia Social Media presentation at DigitalDays
 
Innovation In The Workplace Andrew James
Innovation In The Workplace   Andrew JamesInnovation In The Workplace   Andrew James
Innovation In The Workplace Andrew James
 
Top 10 Business Continuity Disasters
Top 10 Business Continuity DisastersTop 10 Business Continuity Disasters
Top 10 Business Continuity Disasters
 
Visual Studio 2013 - Recursos da IDE
Visual Studio 2013 - Recursos da IDEVisual Studio 2013 - Recursos da IDE
Visual Studio 2013 - Recursos da IDE
 
New Research: Cloud, Cost & Complexity Impact IAM & IT
New Research: Cloud, Cost & Complexity Impact IAM & ITNew Research: Cloud, Cost & Complexity Impact IAM & IT
New Research: Cloud, Cost & Complexity Impact IAM & IT
 
Dr Ravi Gupta
Dr Ravi GuptaDr Ravi Gupta
Dr Ravi Gupta
 
5 Reasons to Recycle in the D.C. Metro Area
5 Reasons to Recycle in the D.C. Metro Area5 Reasons to Recycle in the D.C. Metro Area
5 Reasons to Recycle in the D.C. Metro Area
 
TXT Next Presentation
TXT Next Presentation TXT Next Presentation
TXT Next Presentation
 
Perceptive Software Scope
Perceptive Software ScopePerceptive Software Scope
Perceptive Software Scope
 
Presence Agent y Presence Scripting para personas con limitaciones visuales
Presence Agent y Presence Scripting para personas con limitaciones visualesPresence Agent y Presence Scripting para personas con limitaciones visuales
Presence Agent y Presence Scripting para personas con limitaciones visuales
 
Enriched Insights in Finance: Blending Data, Boosting Performance
Enriched Insights in Finance: Blending Data, Boosting PerformanceEnriched Insights in Finance: Blending Data, Boosting Performance
Enriched Insights in Finance: Blending Data, Boosting Performance
 
Microsoft
MicrosoftMicrosoft
Microsoft
 

Similar to Archiving is a No-brainer - Bloor Analyst and RainStor Executive Discuss

From limited Hadoop compute capacity to increased data scientist efficiency
From limited Hadoop compute capacity to increased data scientist efficiencyFrom limited Hadoop compute capacity to increased data scientist efficiency
From limited Hadoop compute capacity to increased data scientist efficiency
Alluxio, Inc.
 
Data Orchestration Platform for the Cloud
Data Orchestration Platform for the CloudData Orchestration Platform for the Cloud
Data Orchestration Platform for the Cloud
Alluxio, Inc.
 
Houd controle over uw data
Houd controle over uw dataHoud controle over uw data
Houd controle over uw data
ICT-Partners
 
Accelerate Analytics and ML in the Hybrid Cloud Era
Accelerate Analytics and ML in the Hybrid Cloud EraAccelerate Analytics and ML in the Hybrid Cloud Era
Accelerate Analytics and ML in the Hybrid Cloud Era
Alluxio, Inc.
 
Alluxio 2.0 Deep Dive – Simplifying data access for cloud workloads
Alluxio 2.0 Deep Dive – Simplifying data access for cloud workloadsAlluxio 2.0 Deep Dive – Simplifying data access for cloud workloads
Alluxio 2.0 Deep Dive – Simplifying data access for cloud workloads
Alluxio, Inc.
 
The Future of Data Management: The Enterprise Data Hub
The Future of Data Management: The Enterprise Data HubThe Future of Data Management: The Enterprise Data Hub
The Future of Data Management: The Enterprise Data Hub
Cloudera, Inc.
 
MT129 Isilon Data Lake Overview
MT129 Isilon Data Lake OverviewMT129 Isilon Data Lake Overview
MT129 Isilon Data Lake Overview
Dell EMC World
 
10 Reasons Snowflake Is Great for Analytics
10 Reasons Snowflake Is Great for Analytics10 Reasons Snowflake Is Great for Analytics
10 Reasons Snowflake Is Great for Analytics
Senturus
 
Big Data on Azure Tutorial
Big Data on Azure TutorialBig Data on Azure Tutorial
Big Data on Azure Tutorial
rustd
 
Alluxio Data Orchestration Platform for the Cloud
Alluxio Data Orchestration Platform for the CloudAlluxio Data Orchestration Platform for the Cloud
Alluxio Data Orchestration Platform for the Cloud
Shubham Tagra
 
Turning Data into Business Value with a Modern Data Platform
Turning Data into Business Value with a Modern Data PlatformTurning Data into Business Value with a Modern Data Platform
Turning Data into Business Value with a Modern Data Platform
Cloudera, Inc.
 
Achieving Separation of Compute and Storage in a Cloud World
Achieving Separation of Compute and Storage in a Cloud WorldAchieving Separation of Compute and Storage in a Cloud World
Achieving Separation of Compute and Storage in a Cloud World
Alluxio, Inc.
 
How to Build Multi-disciplinary Analytics Applications on a Shared Data Platform
How to Build Multi-disciplinary Analytics Applications on a Shared Data PlatformHow to Build Multi-disciplinary Analytics Applications on a Shared Data Platform
How to Build Multi-disciplinary Analytics Applications on a Shared Data Platform
Cloudera, Inc.
 
Data Orchestration for the Hybrid Cloud Era
Data Orchestration for the Hybrid Cloud EraData Orchestration for the Hybrid Cloud Era
Data Orchestration for the Hybrid Cloud Era
Alluxio, Inc.
 
Accelerate Analytics and ML in the Hybrid Cloud Era
Accelerate Analytics and ML in the Hybrid Cloud EraAccelerate Analytics and ML in the Hybrid Cloud Era
Accelerate Analytics and ML in the Hybrid Cloud Era
Alluxio, Inc.
 
Presentation dell™ power vault™ md3
Presentation   dell™ power vault™ md3Presentation   dell™ power vault™ md3
Presentation dell™ power vault™ md3
xKinAnx
 
ADV Slides: Platforming Your Data for Success – Databases, Hadoop, Managed Ha...
ADV Slides: Platforming Your Data for Success – Databases, Hadoop, Managed Ha...ADV Slides: Platforming Your Data for Success – Databases, Hadoop, Managed Ha...
ADV Slides: Platforming Your Data for Success – Databases, Hadoop, Managed Ha...
DATAVERSITY
 
Accelerating workloads and bursting data with Google Dataproc & Alluxio
Accelerating workloads and bursting data with Google Dataproc & AlluxioAccelerating workloads and bursting data with Google Dataproc & Alluxio
Accelerating workloads and bursting data with Google Dataproc & Alluxio
Big Data Aplications Meetup
 
Cloudian Webinar - 7 Key Reasons why Object Storage lowers Storage TCO
Cloudian Webinar - 7 Key Reasons why Object Storage lowers Storage TCOCloudian Webinar - 7 Key Reasons why Object Storage lowers Storage TCO
Cloudian Webinar - 7 Key Reasons why Object Storage lowers Storage TCO
Storage Switzerland
 
Big Data Infrastructure
Big Data InfrastructureBig Data Infrastructure
Big Data Infrastructure
Trivadis
 

Similar to Archiving is a No-brainer - Bloor Analyst and RainStor Executive Discuss (20)

From limited Hadoop compute capacity to increased data scientist efficiency
From limited Hadoop compute capacity to increased data scientist efficiencyFrom limited Hadoop compute capacity to increased data scientist efficiency
From limited Hadoop compute capacity to increased data scientist efficiency
 
Data Orchestration Platform for the Cloud
Data Orchestration Platform for the CloudData Orchestration Platform for the Cloud
Data Orchestration Platform for the Cloud
 
Houd controle over uw data
Houd controle over uw dataHoud controle over uw data
Houd controle over uw data
 
Accelerate Analytics and ML in the Hybrid Cloud Era
Accelerate Analytics and ML in the Hybrid Cloud EraAccelerate Analytics and ML in the Hybrid Cloud Era
Accelerate Analytics and ML in the Hybrid Cloud Era
 
Alluxio 2.0 Deep Dive – Simplifying data access for cloud workloads
Alluxio 2.0 Deep Dive – Simplifying data access for cloud workloadsAlluxio 2.0 Deep Dive – Simplifying data access for cloud workloads
Alluxio 2.0 Deep Dive – Simplifying data access for cloud workloads
 
The Future of Data Management: The Enterprise Data Hub
The Future of Data Management: The Enterprise Data HubThe Future of Data Management: The Enterprise Data Hub
The Future of Data Management: The Enterprise Data Hub
 
MT129 Isilon Data Lake Overview
MT129 Isilon Data Lake OverviewMT129 Isilon Data Lake Overview
MT129 Isilon Data Lake Overview
 
10 Reasons Snowflake Is Great for Analytics
10 Reasons Snowflake Is Great for Analytics10 Reasons Snowflake Is Great for Analytics
10 Reasons Snowflake Is Great for Analytics
 
Big Data on Azure Tutorial
Big Data on Azure TutorialBig Data on Azure Tutorial
Big Data on Azure Tutorial
 
Alluxio Data Orchestration Platform for the Cloud
Alluxio Data Orchestration Platform for the CloudAlluxio Data Orchestration Platform for the Cloud
Alluxio Data Orchestration Platform for the Cloud
 
Turning Data into Business Value with a Modern Data Platform
Turning Data into Business Value with a Modern Data PlatformTurning Data into Business Value with a Modern Data Platform
Turning Data into Business Value with a Modern Data Platform
 
Achieving Separation of Compute and Storage in a Cloud World
Achieving Separation of Compute and Storage in a Cloud WorldAchieving Separation of Compute and Storage in a Cloud World
Achieving Separation of Compute and Storage in a Cloud World
 
How to Build Multi-disciplinary Analytics Applications on a Shared Data Platform
How to Build Multi-disciplinary Analytics Applications on a Shared Data PlatformHow to Build Multi-disciplinary Analytics Applications on a Shared Data Platform
How to Build Multi-disciplinary Analytics Applications on a Shared Data Platform
 
Data Orchestration for the Hybrid Cloud Era
Data Orchestration for the Hybrid Cloud EraData Orchestration for the Hybrid Cloud Era
Data Orchestration for the Hybrid Cloud Era
 
Accelerate Analytics and ML in the Hybrid Cloud Era
Accelerate Analytics and ML in the Hybrid Cloud EraAccelerate Analytics and ML in the Hybrid Cloud Era
Accelerate Analytics and ML in the Hybrid Cloud Era
 
Presentation dell™ power vault™ md3
Presentation   dell™ power vault™ md3Presentation   dell™ power vault™ md3
Presentation dell™ power vault™ md3
 
ADV Slides: Platforming Your Data for Success – Databases, Hadoop, Managed Ha...
ADV Slides: Platforming Your Data for Success – Databases, Hadoop, Managed Ha...ADV Slides: Platforming Your Data for Success – Databases, Hadoop, Managed Ha...
ADV Slides: Platforming Your Data for Success – Databases, Hadoop, Managed Ha...
 
Accelerating workloads and bursting data with Google Dataproc & Alluxio
Accelerating workloads and bursting data with Google Dataproc & AlluxioAccelerating workloads and bursting data with Google Dataproc & Alluxio
Accelerating workloads and bursting data with Google Dataproc & Alluxio
 
Cloudian Webinar - 7 Key Reasons why Object Storage lowers Storage TCO
Cloudian Webinar - 7 Key Reasons why Object Storage lowers Storage TCOCloudian Webinar - 7 Key Reasons why Object Storage lowers Storage TCO
Cloudian Webinar - 7 Key Reasons why Object Storage lowers Storage TCO
 
Big Data Infrastructure
Big Data InfrastructureBig Data Infrastructure
Big Data Infrastructure
 

More from RainStor

Big Data Analytics on Hadoop RainStor Infographic
Big Data Analytics on Hadoop RainStor InfographicBig Data Analytics on Hadoop RainStor Infographic
Big Data Analytics on Hadoop RainStor Infographic
RainStor
 
TDWI Checklist Report: Active Data Archiving
TDWI Checklist Report:  Active Data ArchivingTDWI Checklist Report:  Active Data Archiving
TDWI Checklist Report: Active Data Archiving
RainStor
 
Rain stor isilon_emc_real_Examine the Real Cost of Storing & Analyzing Your M...
Rain stor isilon_emc_real_Examine the Real Cost of Storing & Analyzing Your M...Rain stor isilon_emc_real_Examine the Real Cost of Storing & Analyzing Your M...
Rain stor isilon_emc_real_Examine the Real Cost of Storing & Analyzing Your M...
RainStor
 
Smarter Management for Your Data Growth
Smarter Management for Your Data GrowthSmarter Management for Your Data Growth
Smarter Management for Your Data Growth
RainStor
 
Big Data Retention Opportunity or Burden? - Featuring Merv Adrian July 2010
Big Data Retention Opportunity or Burden? - Featuring Merv Adrian July 2010Big Data Retention Opportunity or Burden? - Featuring Merv Adrian July 2010
Big Data Retention Opportunity or Burden? - Featuring Merv Adrian July 2010
RainStor
 
RainStor 3.5 Overview
RainStor 3.5 OverviewRainStor 3.5 Overview
RainStor 3.5 Overview
RainStor
 

More from RainStor (6)

Big Data Analytics on Hadoop RainStor Infographic
Big Data Analytics on Hadoop RainStor InfographicBig Data Analytics on Hadoop RainStor Infographic
Big Data Analytics on Hadoop RainStor Infographic
 
TDWI Checklist Report: Active Data Archiving
TDWI Checklist Report:  Active Data ArchivingTDWI Checklist Report:  Active Data Archiving
TDWI Checklist Report: Active Data Archiving
 
Rain stor isilon_emc_real_Examine the Real Cost of Storing & Analyzing Your M...
Rain stor isilon_emc_real_Examine the Real Cost of Storing & Analyzing Your M...Rain stor isilon_emc_real_Examine the Real Cost of Storing & Analyzing Your M...
Rain stor isilon_emc_real_Examine the Real Cost of Storing & Analyzing Your M...
 
Smarter Management for Your Data Growth
Smarter Management for Your Data GrowthSmarter Management for Your Data Growth
Smarter Management for Your Data Growth
 
Big Data Retention Opportunity or Burden? - Featuring Merv Adrian July 2010
Big Data Retention Opportunity or Burden? - Featuring Merv Adrian July 2010Big Data Retention Opportunity or Burden? - Featuring Merv Adrian July 2010
Big Data Retention Opportunity or Burden? - Featuring Merv Adrian July 2010
 
RainStor 3.5 Overview
RainStor 3.5 OverviewRainStor 3.5 Overview
RainStor 3.5 Overview
 

Recently uploaded

AI Fusion Buddy Review: Brand New, Groundbreaking Gemini-Powered AI App
AI Fusion Buddy Review: Brand New, Groundbreaking Gemini-Powered AI AppAI Fusion Buddy Review: Brand New, Groundbreaking Gemini-Powered AI App
AI Fusion Buddy Review: Brand New, Groundbreaking Gemini-Powered AI App
Google
 
E-commerce Development Services- Hornet Dynamics
E-commerce Development Services- Hornet DynamicsE-commerce Development Services- Hornet Dynamics
E-commerce Development Services- Hornet Dynamics
Hornet Dynamics
 
socradar-q1-2024-aviation-industry-report.pdf
socradar-q1-2024-aviation-industry-report.pdfsocradar-q1-2024-aviation-industry-report.pdf
socradar-q1-2024-aviation-industry-report.pdf
SOCRadar
 
Oracle Database 19c New Features for DBAs and Developers.pptx
Oracle Database 19c New Features for DBAs and Developers.pptxOracle Database 19c New Features for DBAs and Developers.pptx
Oracle Database 19c New Features for DBAs and Developers.pptx
Remote DBA Services
 
Hand Rolled Applicative User Validation Code Kata
Hand Rolled Applicative User ValidationCode KataHand Rolled Applicative User ValidationCode Kata
Hand Rolled Applicative User Validation Code Kata
Philip Schwarz
 
GreenCode-A-VSCode-Plugin--Dario-Jurisic
GreenCode-A-VSCode-Plugin--Dario-JurisicGreenCode-A-VSCode-Plugin--Dario-Jurisic
GreenCode-A-VSCode-Plugin--Dario-Jurisic
Green Software Development
 
How to write a program in any programming language
How to write a program in any programming languageHow to write a program in any programming language
How to write a program in any programming language
Rakesh Kumar R
 
DDS-Security 1.2 - What's New? Stronger security for long-running systems
DDS-Security 1.2 - What's New? Stronger security for long-running systemsDDS-Security 1.2 - What's New? Stronger security for long-running systems
DDS-Security 1.2 - What's New? Stronger security for long-running systems
Gerardo Pardo-Castellote
 
Vitthal Shirke Java Microservices Resume.pdf
Vitthal Shirke Java Microservices Resume.pdfVitthal Shirke Java Microservices Resume.pdf
Vitthal Shirke Java Microservices Resume.pdf
Vitthal Shirke
 
Atelier - Innover avec l’IA Générative et les graphes de connaissances
Atelier - Innover avec l’IA Générative et les graphes de connaissancesAtelier - Innover avec l’IA Générative et les graphes de connaissances
Atelier - Innover avec l’IA Générative et les graphes de connaissances
Neo4j
 
openEuler Case Study - The Journey to Supply Chain Security
openEuler Case Study - The Journey to Supply Chain SecurityopenEuler Case Study - The Journey to Supply Chain Security
openEuler Case Study - The Journey to Supply Chain Security
Shane Coughlan
 
Neo4j - Product Vision and Knowledge Graphs - GraphSummit Paris
Neo4j - Product Vision and Knowledge Graphs - GraphSummit ParisNeo4j - Product Vision and Knowledge Graphs - GraphSummit Paris
Neo4j - Product Vision and Knowledge Graphs - GraphSummit Paris
Neo4j
 
Graspan: A Big Data System for Big Code Analysis
Graspan: A Big Data System for Big Code AnalysisGraspan: A Big Data System for Big Code Analysis
Graspan: A Big Data System for Big Code Analysis
Aftab Hussain
 
Measures in SQL (SIGMOD 2024, Santiago, Chile)
Measures in SQL (SIGMOD 2024, Santiago, Chile)Measures in SQL (SIGMOD 2024, Santiago, Chile)
Measures in SQL (SIGMOD 2024, Santiago, Chile)
Julian Hyde
 
Energy consumption of Database Management - Florina Jonuzi
Energy consumption of Database Management - Florina JonuziEnergy consumption of Database Management - Florina Jonuzi
Energy consumption of Database Management - Florina Jonuzi
Green Software Development
 
Using Xen Hypervisor for Functional Safety
Using Xen Hypervisor for Functional SafetyUsing Xen Hypervisor for Functional Safety
Using Xen Hypervisor for Functional Safety
Ayan Halder
 
Revolutionizing Visual Effects Mastering AI Face Swaps.pdf
Revolutionizing Visual Effects Mastering AI Face Swaps.pdfRevolutionizing Visual Effects Mastering AI Face Swaps.pdf
Revolutionizing Visual Effects Mastering AI Face Swaps.pdf
Undress Baby
 
Transform Your Communication with Cloud-Based IVR Solutions
Transform Your Communication with Cloud-Based IVR SolutionsTransform Your Communication with Cloud-Based IVR Solutions
Transform Your Communication with Cloud-Based IVR Solutions
TheSMSPoint
 
Automated software refactoring with OpenRewrite and Generative AI.pptx.pdf
Automated software refactoring with OpenRewrite and Generative AI.pptx.pdfAutomated software refactoring with OpenRewrite and Generative AI.pptx.pdf
Automated software refactoring with OpenRewrite and Generative AI.pptx.pdf
timtebeek1
 
SMS API Integration in Saudi Arabia| Best SMS API Service
SMS API Integration in Saudi Arabia| Best SMS API ServiceSMS API Integration in Saudi Arabia| Best SMS API Service
SMS API Integration in Saudi Arabia| Best SMS API Service
Yara Milbes
 

Recently uploaded (20)

AI Fusion Buddy Review: Brand New, Groundbreaking Gemini-Powered AI App
AI Fusion Buddy Review: Brand New, Groundbreaking Gemini-Powered AI AppAI Fusion Buddy Review: Brand New, Groundbreaking Gemini-Powered AI App
AI Fusion Buddy Review: Brand New, Groundbreaking Gemini-Powered AI App
 
E-commerce Development Services- Hornet Dynamics
E-commerce Development Services- Hornet DynamicsE-commerce Development Services- Hornet Dynamics
E-commerce Development Services- Hornet Dynamics
 
socradar-q1-2024-aviation-industry-report.pdf
socradar-q1-2024-aviation-industry-report.pdfsocradar-q1-2024-aviation-industry-report.pdf
socradar-q1-2024-aviation-industry-report.pdf
 
Oracle Database 19c New Features for DBAs and Developers.pptx
Oracle Database 19c New Features for DBAs and Developers.pptxOracle Database 19c New Features for DBAs and Developers.pptx
Oracle Database 19c New Features for DBAs and Developers.pptx
 
Hand Rolled Applicative User Validation Code Kata
Hand Rolled Applicative User ValidationCode KataHand Rolled Applicative User ValidationCode Kata
Hand Rolled Applicative User Validation Code Kata
 
GreenCode-A-VSCode-Plugin--Dario-Jurisic
GreenCode-A-VSCode-Plugin--Dario-JurisicGreenCode-A-VSCode-Plugin--Dario-Jurisic
GreenCode-A-VSCode-Plugin--Dario-Jurisic
 
How to write a program in any programming language
How to write a program in any programming languageHow to write a program in any programming language
How to write a program in any programming language
 
DDS-Security 1.2 - What's New? Stronger security for long-running systems
DDS-Security 1.2 - What's New? Stronger security for long-running systemsDDS-Security 1.2 - What's New? Stronger security for long-running systems
DDS-Security 1.2 - What's New? Stronger security for long-running systems
 
Vitthal Shirke Java Microservices Resume.pdf
Vitthal Shirke Java Microservices Resume.pdfVitthal Shirke Java Microservices Resume.pdf
Vitthal Shirke Java Microservices Resume.pdf
 
Atelier - Innover avec l’IA Générative et les graphes de connaissances
Atelier - Innover avec l’IA Générative et les graphes de connaissancesAtelier - Innover avec l’IA Générative et les graphes de connaissances
Atelier - Innover avec l’IA Générative et les graphes de connaissances
 
openEuler Case Study - The Journey to Supply Chain Security
openEuler Case Study - The Journey to Supply Chain SecurityopenEuler Case Study - The Journey to Supply Chain Security
openEuler Case Study - The Journey to Supply Chain Security
 
Neo4j - Product Vision and Knowledge Graphs - GraphSummit Paris
Neo4j - Product Vision and Knowledge Graphs - GraphSummit ParisNeo4j - Product Vision and Knowledge Graphs - GraphSummit Paris
Neo4j - Product Vision and Knowledge Graphs - GraphSummit Paris
 
Graspan: A Big Data System for Big Code Analysis
Graspan: A Big Data System for Big Code AnalysisGraspan: A Big Data System for Big Code Analysis
Graspan: A Big Data System for Big Code Analysis
 
Measures in SQL (SIGMOD 2024, Santiago, Chile)
Measures in SQL (SIGMOD 2024, Santiago, Chile)Measures in SQL (SIGMOD 2024, Santiago, Chile)
Measures in SQL (SIGMOD 2024, Santiago, Chile)
 
Energy consumption of Database Management - Florina Jonuzi
Energy consumption of Database Management - Florina JonuziEnergy consumption of Database Management - Florina Jonuzi
Energy consumption of Database Management - Florina Jonuzi
 
Using Xen Hypervisor for Functional Safety
Using Xen Hypervisor for Functional SafetyUsing Xen Hypervisor for Functional Safety
Using Xen Hypervisor for Functional Safety
 
Revolutionizing Visual Effects Mastering AI Face Swaps.pdf
Revolutionizing Visual Effects Mastering AI Face Swaps.pdfRevolutionizing Visual Effects Mastering AI Face Swaps.pdf
Revolutionizing Visual Effects Mastering AI Face Swaps.pdf
 
Transform Your Communication with Cloud-Based IVR Solutions
Transform Your Communication with Cloud-Based IVR SolutionsTransform Your Communication with Cloud-Based IVR Solutions
Transform Your Communication with Cloud-Based IVR Solutions
 
Automated software refactoring with OpenRewrite and Generative AI.pptx.pdf
Automated software refactoring with OpenRewrite and Generative AI.pptx.pdfAutomated software refactoring with OpenRewrite and Generative AI.pptx.pdf
Automated software refactoring with OpenRewrite and Generative AI.pptx.pdf
 
SMS API Integration in Saudi Arabia| Best SMS API Service
SMS API Integration in Saudi Arabia| Best SMS API ServiceSMS API Integration in Saudi Arabia| Best SMS API Service
SMS API Integration in Saudi Arabia| Best SMS API Service
 

Archiving is a No-brainer - Bloor Analyst and RainStor Executive Discuss

  • 1. RRain   1   Archive  is  a  No  Brainer    
  • 2. Speakers  &  Topics   2   Philip Howard, Research Director Bloor Deirdre Mahon, VP Marketing RainStor §   What  is  an  Archive   §   Industry  Trends   §   Key  Requirements   §   Best  Prac>ces   §   Customer  Examples  
  • 3. Database archiving Philip Howard Research Director, Bloor Research
  • 4. telling the right storyConfidential © Bloor Research 2013 Agenda " What is database archiving? " Why is it increasingly important? " What sort of features do you need? " What trends do we see and what differentiates products?
  • 5. telling the right storyConfidential © Bloor Research 2013 What is database archiving? Online, low cost, highly compressed storage that requires no change to access methods Not back-up Not e-mail archive Not CSV or XML files
  • 6. telling the right storyConfidential © Bloor Research 2013 Two scenarios Access support for originating application SQL support
  • 7. telling the right storyConfidential © Bloor Research 2013 Why is database archiving increasingly on the agenda? " Availability of cloud-based archiving " Availability of Hadoop/HDFS- based archiving " Synergy with data migration
  • 8. telling the right storyConfidential © Bloor Research 2013 What you need 1 You need to know what data to archive
  • 9. telling the right storyConfidential © Bloor Research 2013 What you need 2 You don’t just archive a record, you archive all the other data related to that record – to preserve referential integrity – which means discovering and understanding business entities in their entirety.
  • 10. telling the right storyConfidential © Bloor Research 2013 What you need 3 " High compression rates " Low cost storage
  • 11. telling the right storyConfidential © Bloor Research 2013 What you need 4 Loading and access Without indexes
  • 12. telling the right storyConfidential © Bloor Research 2013 What you need 5 Information Lifecycle Management not Industrial Light & Magic
  • 13. telling the right storyConfidential © Bloor Research 2013 What you need 6
  • 14. telling the right storyConfidential © Bloor Research 2013 The trend towards Hadoop But Hadoop/HDFS is insufficient on its own because the compression is not good enough and neither is the security
  • 15. telling the right storyConfidential © Bloor Research 2013 Other trends " Compression will (almost) become commoditised (but not yet) " Deployments will built on top of Hadoop/ HDFS or in the cloud (or both) " In data warehousing environments data virtualisation (federation) will be used to interconnect warehouses, marts and archives " Differentiation will focus on: " Ease of establishing what data to archive " Performance – both for loading and retrieval
  • 16. telling the right storyConfidential © Bloor Research 2013 Conclusion " Database archiving looks more and more like a mandatory activity " DIY approaches won’t cut it because of a) the work involved and b) because you won’t get either the cost savings or performance you could do " Deployments will increasingly be on low-cost clustered hardware or in the cloud
  • 17. telling the right storyConfidential © Bloor Research 2013
  • 18. RainStor®   18   Create  Value  from  Your  Historical  Data     and  Meet  Regulatory  Demands.   The  Data  Archive  
  • 19. RainStor®  -­‐  Proven   19   20  of     World’s  Largest   Communica>ons   Providers   15  Strategic     Solu>on  &     Technology     Partners   10  of     World’s  Biggest   Banks  &  Financial   Ins>tu>ons    
  • 20. Drivers  &  Business  Challenges  Solved   20   10X  ReducGon   (Compared  to  tradi>onal)     Cost   Deployed  in  90  Days   (End-­‐to-­‐end  Solu>on)   Complexity   Meets  &  Exceeds   (Industry  &  Regulatory)  Compliance   Historical  AnalyGcs   (Standards-­‐based)   Create   Value  
  • 21. Archive  Solu>ons   Analy>cal  Archive   Compliance  Archive   21   Comply
  • 22. Analy>cal  Archive:  End-­‐to-­‐end   QUERY/   ANALYZE   SQL   BI  Tools;  Hive,   MapReduce     SCALE  -­‐  Any  PlaWorm   COMPRESS  LOAD/   VALIDATE   Billions   Records/Day   10-­‐40X   (90%+)   AVAILABILITY   ReplicaGon   DW   Source   Move   RETAIN  / DISPOSE   Rules   Based   IN   STORE   QUERY   GOVERN   SECURE  -­‐  Enterprise-­‐grade      
  • 23. Analy>cal  Archive  -­‐  Key  Capabili>es   23   QUERY   GOVERN   §  Standard  SQL  92,  99   §  MapReduce,  Pig,  Hive   §  BI  Tools   §  Rules  based  Data  Disposi>on   §  WORM  (17a-­‐4)   §  Legal  Hold   §  Record-­‐level  Reten>on   §  Audit  Trail   DATA  IN   §  Works  with  standard  ETL   §  ODBC/JDBC  Compa>ble   §  FastConnect™  for  Teradata   §  Validate  -­‐  Fingerprint   STORE   §  Compression  -­‐  20-­‐40X   §  Immutable  Data  Model   §  Encryp>on  &  Masking   §  Authen>ca>on   §  Schema  Evolu>on   CAPACITY  BUY-­‐BACK   INSTANT  ACCESS   NO  FINES   SAVE  YOU  MONEY  
  • 24. Fits  with  Your  Enterprise   24   EDW’S   Deployment  PlaWorms   Scale-­‐out    NAS   HDFS     Cluster  /  DAS   Cloud   Worm  
  • 25. Teradata  -­‐  Analy>cal  Archive  Solu>on   QUERY/   ANALYZE   SQL   BI  Tools;  Hive,   MapReduce     SCALE  -­‐  Any  PlaWorm   COMPRESS  LOAD/   VALIDATE   Billions   Records/Day   10-­‐40X   (90%+)   AVAILABILITY   ReplicaGon   TERADATA   FastConnect™   RETAIN  / DISPOSE   Rules   Based   GOVERN   SECURE  -­‐  Enterprise-­‐grade       FastForward™  
  • 26. SEC  17a-­‐4(f)  Compliance  Archive  Requirements   26   Records  stored  in  non-­‐eraseable  media  (WORM)   Recording  process  must  be  verifiable   Fully  Accessible  to  AuthoriGes  &  Backed-­‐up   Records  should  be  Recognizable  &  IdenGfiable   Downloadable  to  any  acceptable  medium    
  • 27. 27   Global  Financial  Services   Lower  Compliant  Data  Reten>on  Costs  by  a  Decimal  Point!   Challenges   §  Cost:  Data  volumes  in  disparate  trading   applica>ons  growing  at  70-­‐100%  /  Year  -­‐  Storage   costs  rising  @  60%  /  Year   §  Compliance:  Must  provide  performant  EBS  and   other  queries  for  SEC     SoluGon   §  A  RainStor  Archive  for  storing  and  repor>ng   against  historical  trade  data   §  13  years  of  history  loaded  from  Sybase  IQ   §  Daily  feed  from  trading  applica>on  to  RainStor   §  Runs  on  low-­‐cost  NAS  Tier  3  storage  and  VMs   §  RainStor  completely  replaced  Sybase  IQ   ü  90%  cost  savings  -­‐  $5M  ROI   ü  6  Projects  live  -­‐  13  more  in   progress.   90%   Storage  Cost   Reduc>on   “ It’s like shrink-wrapping your data…forever!”  –  VP,  Technology   Benefits   ü  30X  Data  Compression       ü  3X  Faster  Query  Compared  to  Sybase  
  • 28. 28     Retain  Cri>cal  Analy>cs  Data  at  Lowest  Cost     §  Ini>ally  60TB  Offload    Business  &    Compliance  Queries   §  Run  Na>vely  on   Hadoop    SQL  +  MapReduce     40X  Compression   RAINSTOR  SOLUTION:    Offload  Historical  Data  from  Teradata  to  RainStor   Meets  SLAs  for  Business  Query     Savings  on  TD  Licenses   Capacity  Buy-­‐Back  -­‐  $Millions  Saved  on  Sopware  &  Hardware   Enterprise  DW   FastConnect™   Dell  Servers     R720s   Cloudera  Hadoop   400TB   ü ü ü
  • 29. §  Gone  through  the  pain  so  you  don't  have  to.   –  Crea>ng  an  archive  is  not  easy!   –  RainStor  Makes  it  simple,  cost  effec>ve,  compliant-­‐ready  &  fast  to  deploy   §  Solving  archiving  problems  for  world  leaders  -­‐  10  years   of  proven  experience.   –  Enabled  customers  to  deploy  cost  efficiently  without  compromise     –  Support  and  service  rated  as  world  class  by  our  customers   §  Technology  soluGons  that  create  business  value.   –  Transforms  archiving  to  be  a  strategic  asset.   Why  RainStor®  
  • 30.            Thank  You   30   Archive  is  a   No  Brainer