Introducing DataStax Enterprise 4.7

Introducing DataStax Enterprise 4.7
Purpose built for web, mobile, and IoT applications
Robin Schumacher
VP Products
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Webinar Housekeeping

Agenda
• Overview of DataStax
• Common need of modern Web, mobile, and IoT applications
• Overview of what’s new in DSE 4.7
• Details of DSE 4.7:
• DSE Search enhancements
• DSE Analytics enhancements
• DSE In-Memory enhancements
• DSE Advanced Security enhancements
• Other DSE enhancements
• What’s new in OpsCenter 5.1?
• Sneak peek at OpsCenter 5.2
• Wrap up
3

Your Life With DataStax
5
• DataStax delivers Apache Cassandra in a
database platform purpose built for the
performance and availability demands of
Web, Mobile, and IOT applications.
• Gives enterprises a secure always-on
database that remains operationally simple
when scaled in a single datacenter or
across multiple datacenters and clouds.

Users Spanning All Verticals
6

Cassandra – What’s the Difference?
7
Cassandra can then
DELIVER…
 Disaster Avoidance
 Multi Datacenter and Cloud
 Predictable Performance
Cassandra is DESIGNED
to solve…
 Relentless Availability
 High Performance
 Linear Scale
Cassandra is DIFFERENT
because…
 NO Primary or Master
 Fully Distributed
 Operationally Simple

Cassandra – Leading in Performance

What do all Modern Web/Mobile/IoT Apps Have in Common?

Mixed Workload!
• All modern Web/Mobile/IoT applications have “mixed workload” requirements.
• Transactional, analytical, search, in-memory, etc., workloads have different data
access patterns, needs, and demands.
• Having mixed workloads run on one database is bad because the different
workload compete for data and compute resources and often block each other.
• Architects have typically “sharded” or separated workloads by using different
databases /vendors for an application.
• Difficult to do because you have multiple databases to deal with and pay for, data
is constantly being unloaded/loaded into all the systems.
• Security risk – multiple opportunities for hackers.
©2015 DataStax Confidential. Do not distribute without consent. Transactions Analytics Search

DSE – the Only Database Platform Solving Mixed Workload
©2015 DataStax Confidential. Do not distribute without consent.
Typical Sharded Mixed Workload Application DataStax Enterprise
Multiple databases/vendors/education One database platform/vendor/education
Manually separate & maintain data across different systems Automatic maintenance & separation of data in one system
Oftentimes requires expensive extract-transform-load tools No need to ETL tools
Multiple security paradigms/multiple hacker opportunities One, uniform security paradigm
Multiple management tools needed One management tool needed

It’s Easy with DSE
12
Going into
production with
Cassandra?
Need mixed
workload
support?

Mixed Workload Management – How Does it Work?
• When DataStax Enterprise is installed, you specify what nodes will be dedicated
to OLTP, analytic, and enterprise search processing.
• Existing clusters can also be expanded to include analytic/search nodes.
• Replica groups are created that keep all data distributed and replicated across
the transactional, analytic groups, and search groups.
• Reads and writes can be handled on any node.

Announcing DataStax Enterprise 4.7
• Faster and more flexible enterprise search, upgraded analytics with
auto-high availability, enhanced in-memory computing support,
improved security, and production-certified Cassandra 2.1.
• DSE continues to be the first and best database choice for Web,
Mobile and IoT applications that have mixed workloads.
14
DataStax Enterprise 4.7

Let’s Talk About Search…
16©2015 DataStax Confidential. Do not distribute without consent.

DSE Search – “Live Indexing”
17
What is it? Benefit
Live Indexing makes new,
incoming data accessible
to search requests very
quickly.
• Ensures little to no gap between new data entering a
system and when customers can find it
• Not available in open source Solr or Elasticsearch

DSE Search – Enabling “Search-Lytics”
18
What is it? Benefit
Spark SparkSQL query
language can use Solr
syntax to search and
analyze data.
• Greatly extends SparkSQL query abilities to be even more
powerful
• Delivers potential for faster response times for Spark
queries
Example wildcard query using both DSE Analytics and DSE Search:
val table = sc.cassandraTable("music","solr")
val result =
table.select("id","artist_name").where("solr_query='artist_name:Miles*'").collect

DSE Search – Faster, More Flexible, and Upgraded
19
What Benefit
Fault tolerant search automatically
retries search queries on other nodes if
original search node containing data
goes down
• Faster response times for queries that are interrupted
• No need for manual intervention or application code to
retry search queries
Run DSE Analytics and DSE Search
on same node(s)
• Reduces amount of hardware needed for use cases that
allow analytics and search to run together
• Reduces amount of data replicated between nodes
Smart Query Routing transparently
sends search queries to the best
performing nodes in a cluster.
• Helps ensure fastest possible response times for each
individual search request
• Transparent to application; no additional work needed on
part of developers or admins
• Not available in open source Solr or Elasticsearch
Production certification of Solr 4.10 • Delivers over 22 new features that help developers build
applications that need search support

Does Elasticsearch or Apache Solr have…
20
Live indexing that makes data quickly available for search? No.
Intelligent query routing that ensures best search response times? No.
Ability to tightly integrate Spark analytics and search? No.
Functionality to auto-retry failed search requests? No.
Ability to easily scale across multiple data center / clouds? No.

DSE Search
“We had another, distinct Elasticsearch cluster running for search tasks. With DSE, we get
Spark built-in to a database cluster as well as search capabilities via DSE Search, which
removes the need to have separate clusters of Spark and Elasticsearch. We’re using DSE
Search today and will be migrating our separate Spark cluster to DSE soon.” – CIO, Wattgo
21

DSE Analytics – Always On and Upgraded
22
What Benefit
Automatic high availability for real time
analytics (Spark)
• Ensures analytic operations don’t go down
• Removes need for manual involvement in providing failover for
down analytics nodes
Production certification for machine
learning analytics (Spark Mlib)
• Delivers the ability for developers to create applications that utilize
machine learning (e.g. a healthcare app that predicts ER wait times)
New Spark tuning support in DSE
Performance Service
• Provides insight into Spark performance
• Automatically collects important Spark diagnostic data
• Reduces the time to troubleshoot and tune analytics performance
Production certification of Spark 1.2 • Increased performance, improved streaming data support, and
simpler development
JDBC Support • Services applications and tools (e.g. BI tools) wanting to run analytic
operations on Cassandra via JDBC

British Gas Tackles Internet-of-Things with DataStax
Connected Homes, a new business unit, handles IoT-based customer systems
Provides remote control over thermostats and boilers via smart phones/tablets
Delivers analytics on energy usage to customers
Will be using predictive analysis to forecast things like boiler failures
Uses DataStax Enterprise for transactional data consumption and real-time analytics

DSE In-Memory – More Memory Please
24
What Benefit
Increased memory utilization
that uses both Java and non-
Java RAM options
• Increases the amount of data that in in-memory tables can store
by about 50x
• Good for the read-intensive parts of an application where data
changes very little or changes are confined to specific load periods
DSE In-Memory:
• Delivers in-memory computing abilities to Cassandra for applications that
need both in-memory and disk data management.
• Transparent to applications and easy to control / modify.
• Easily monitored in OpsCenter, with alerts and forecasting of future growth
push-button simple.

Improved Data Protection and Security
25
What Benefit
Enhanced transparent data
encryption (TDE) that
separates the encryption keys
(used to ‘unlock’ encrypted
data) from the actual data
• Adds extra data protection by keeping sensitive, encrypted data
and the keys needed to utilize the data apart and on different
servers (think not keeping your ATM card and PIN together in your
wallet)
• Works with partner security products like Vormetric

Netflix Ensures Constant Uptime with DataStax Enterprise
World’s leading streaming media provider with digital revenue $1.5BN+
95% of all Netflix data stored in DSE
Introduction of ‘Profiles’ drove throughput to over 10M transactions per second
Does 1 trillion transactions/day with DSE
Replaced Oracle in six data centers, worldwide, 100% in the cloud
Moved to DSE for advanced security; PCI and SOX compliance
26

Certified Cassandra 2.1
27
What Benefit
Production-certification for
Cassandra 2.1
• Delivers many customer-requested enhancements that improve
maintenance operations and simplify application development
• Supplies dramatic performance increases depending on the use
case (e.g. 75-95% faster)

Intuit Services Millions of Concurrent Customers with DataStax
TurboTax mission critical to Intuit driving 34% of revenue
Turned from Oracle to DataStax for high velocity, always on architecture
Fantastic performance, exceeded Intuit’s 99.99% SLA by delivering 100% uptime
Fast snapshots, rolling upgrades and easy management with Cassandra
56

Mapping DSE 4.7 to Key Personas
29
4.7 Feature Area Developer Admin/Operations CIO/CTO
DSE Search New features for more quickly
developing apps needing
search, no need to code search
retry operations, and no manual
data sharding
Simpler administration,
easier monitoring, and
reduced tuning efforts, and
no separate search system
to manage
Quicker access to new search data for
customers, less hardware costs for
applications needing both search and
analytics, and no need for additional
search vendor
DSE Analytics Additional analytic tools (e.g.
machine learning) for building
analytical app components, and
no manual data sharding
Simplified analytics tuning
and less involvement
needed for analytics high
availability, and no
separate analytics DB to
manage
Constant uptime and smarter
capabilities for analytics applications
and no need for additional analytics
vendor
DSE In-Memory Simple application development
for both disk-based and in-
memory use cases, and no
manual data sharding
Another option to speed
performance for
applications, and no in-
memory cache to manage
Fast application performance and no
need for additional in-memory vendor
DSE Security No application burden
encountered when accessing
sensitive, encrypted data
More options for encrypting
and guarding sensitive data
More protection against hackers and
data thieves
DSE Cassandra 2.1 New features for developing
Web, Mobile, IoT apps
Easier and faster
maintenance operations
Greater speed and capabilities for
critical business systems

Mapping DSE 4.7 to Key Business Challenges
30
Challenge Addressed in DSE 4.7…
Meeting/exceeding performance
SLA’s for IoT, Web, Mobile apps
• More efficient consistency maintenance (repair) functionality in
Cassandra 2.1
• General Cassandra speed improvements in version 2.1
• Improved search speeds with b
• Enhanced DSE In-Memory
Quickly searching for, locating, and
analyzing customer requested data
in IoT, Web, Mobile apps.
• DSE Search Live Indexing
• Smart search query routing
• Automatic retry for search query failures
• Automatic high-availability for Spark analytics
• Ability to run Search and Analytics on same nodes in a cluster
• Extending SparkSQL with Solr search abilities
• New Solr 4.10 application development features
Data privacy and preventing data
breaches.
• Enhanced transparent data encryption that provides separation
of data and keys needed to access encrypted data

OpsCenter 5.1!
• Support for Cassandra incremental repairs in Repair Service.
• Easier monitoring for in-memory option.
• Alerts for transparent data encryption off-server key management.
• Integration with Spark console.
• Percentile graphs.

Sneak Peek – OpsCenter 5.2!
• More easily provision/add new datacenters and cloud zones.
• Enhanced security with LDAP/Active directory support.
• More intelligent monitoring with built-in guidance on finding hotspots and
bottlenecks, with recommendations on improvements.
• More efficient maintenance of data consistency across a cluster.

DataStax Enterprise Editions
33

For More Information…
• Downloads of DSE 4.7 and OpsCenter 5.1.2 now available.
• Downloads of DSE Sandbox.
• Online documentation.
• End Point NoSQL benchmark white paper.
• Customer case studies.
• Lots more…

DSE – The Database Platform for Web, Mobile, and IoT

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Introducing DataStax Enterprise 4.7

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