optimize your vertica data management infrastructure

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Optimize Your Vertica Data Management InfrastructureSrinivas Vadlamani, Chief ArchitectJanuary 2017


My background

Co-founder and Chief Architect at Talena. Prior to Talena, I was an early architect at Couchbase and Aster Data, helping design some of their key datamanagement capabilities.


ing

Data Management Drivers

ApplicationIteration

Compliance

70% of businesses lost data over the past

two years

40% of businesses hitby ransomware in 2016

Robust testing requires up-to-date data

90% of enterprises delayapplication rollouts waiting

for production data

Average Global 2000 company has seven copies of prod data

Storage costs for archival growing by

35% yearly

$900K average cost of

a data loss incident

$1.08M cost to implement

manual test data efforts

$300K average yearly cost of

managing archives

BUSI

NES

S CH

ALLE

NG

ESFI

NAN

CIAL

IM

PACT

Data Loss

Source: EMC, CA, Ponemon


Key Big Data Protection Principles

Replication and backup are not the

same

You need an incremental

forever architecture

It really is about

recovery, not backup

Even commodity storage is expensive


Replication vs BackupReplication: ideal for hardware failures

Backup: ideal to protect against human errors and application corruption

Need both as part of your Vertica data protection strategy


Why Incremental-Forever?

Data volumes are getting too large for traditional backup methods. Backing up hundreds of terabytes on a weekly basis is not feasible as a backup policy


A Recovery-centric ArchitectureHow quickly you recover impacts your business and brand

Your recovery architecture needs to handle changes to the production topology over time

Your recovery flexibility (whole database or at a schema level) will influence your recovery point and recovery time objectives


Speeding Up Application Delivery

Real versus

Synthetic Data

Supporting Complianc

e Initiatives

Minimizing Network

Overhead


What’s Different In The Cloud

Metadata managemen

t is made more

complex

PROBLEM

Storage optimization

becomes that much

more difficult

PROBLEM

Relying on traditional

backup mechanisms

does not scale

PROBLEM


The Talena Architecture

• Deep de-duplication and compression with app-aware architecture

• Incremental-forever backup architecture• High availability via erasure coding in distributed cluster

architecture

Smart Storage Optimizer



Native querying and analytics via active compute layer

Unbounded scale with a Hadoop-native architecture


Active Compute Services Distributed File System



• Google-like catalog shortens data recovery time

• Automatic schema generation for mirroring and backups

• Granular recovery at an object level

• Recovery to multiple topologies

• Native integration with LDAP and Kerberos for authentication

• Role-based access control defines specific privileges

• Transparent data encryption

• Masking for PII data



Metadata Catalog Data Orchestration ServicesSecurity Services




GUI CLI API


• ‘Single pane of glass’ for multiple use cases and data platforms• Agentless architecture minimizes management overhead• GUI, CLI, REST-based Talena API options

Metadata Catalog Data Orchestration ServicesSecurity Services


Talena and vbr.pyvbr.py Talena

Recovery to different Vertica version

No Yes

Recovery to different Vertica topology

No Yes

Google-like metadata catalog for rapid discovery

No Yes

Built-in storage optimization

No Yes

UI for automated policy and workflow creation

No Yes

Ability to support test data management

No Yes

Inherent scalable infrastructure

No Yes

Data masking support No Yes

Sampling support No Yes


Q&A We’ll send you a link to our eBook “The Vertica Backup Guide”

Additional resources: talena-inc.com/resources and talena-inc.com/blog

Ping us with any additional questions: [email protected]


Q and A

optimize your vertica data management infrastructure

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