Moving beyond relational database with SQL Server and HPE Elastic Platform for AnalyticsTurn your critical data into real-time business insights

September 2018

Agenda

– Analytics at the heart of the digital transformation

– HPE’s Elastic Platform for Analytics (EPA) – a platform for the edge to core data analytics pipeline

– Moving beyond the relational DB with SQL Server…..in action!

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Reaching toward transformation

Obstacles to overcome – Architectural limitations of existing data lakes and batch-oriented systems for handling new workloads

– Difficult to capture and analyze all forms of data when needed

– Overwhelming flow of new data types from the edge

– Data protection, curation and governance in a still-evolving technological space

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Desired outcomes

Analysis on human data

Analysis on machine data

Analysis on IoT streams

Analysis in the product

Resilient and protected

Real-time insight

Predictive capability

HPE Elastic Platform for AnalyticsInfrastructure for edge to core analytics

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Aruba and Edgeline

Workload-optimized compute

HPE Elastic Platform benefits

– Independently scale compute and resource tiers

– Add compute nodes without repartitioning data

– Shift node purpose on-the-fly

– Rapidly deploy, move workloads and models with containers

– Own or consume IT with HPE Flexible Capacity

Streaming, fast data analytics Interactive ML / AI Batch

HPE Enterprise Solutions and performance-validated configurationsPerformance | Security | Best practices

CoreIntelligent Edge

Tiered storage for big data analytics

Hot Warm ColdDate lake

Process Train

Data storage for AI workflows

High speed switching fabric

What are the benefits of an elastic platform?

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Scale nodes / resourcesindependently

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Add compute nodeswithout repartitioning data

Shift node purposeon-the-fly

In-memory Interactive Batch

…

Containers enable rapiddeployment and movementof workloads and models

HPE Flexible Capacity forconsumption-based IT

Better access to all your data

Data lake

Provide analytics over all my data structured and unstructured

SQL

Data virtualization

Combine data from many sources without moving or replicating it

T-SQL

Analytics Apps

Open database

connectivity

NoSQL Relational databases

Big Data

External tables

Scale-out data mart

Scale out compute & storage for faster analytics over Big Data

SQL Server

Scale-out data mart

HDFS NoSQL Relational

Spark

Scalable, shared storage HDFS

Spark Streaming

Easily design and deploy a Big Data cluster

Easily design and deploy a Big Data cluster using Microsoft’s Kubernetes-based Big Data distribution

Hadoop Distributed File System (HDFS) storage, SQL Server relational engine, and Spark analytics are deployed as containers in one easy-to manage package

Now, SQL Server can read and write to HDFS files natively, locally on each data node.

Kubernetes pod

SQL Server

HDFS Data Node

Spark

Scale Big Data on demand

SQL Server can now read directly from HDFS

Elastically scale compute and storage on demand using HDFS-based storage pools and SQL Server-based compute pools

Apps, BI, and analytics access Big Data through the SQL Server master instance

SQL Server master instance

Persistent storage

Custom apps AnalyticsBI

SQL Server

HDFS Data Node

Spark

Kubernetes pod

SQL Server

HDFS Data Node

Spark SQL Server

HDFS Data Node

Spark

Node Node Node

SQL

SQL Server aligns with EPA

Compute pool

SQL Compute Node

SQL Compute Node

SQL Compute Node…

Compute pool

SQL Compute Node

IoT data

Directly read from

HDFS

Persistent storage

…

Storage pool

SQL ServerSpark

HDFS Data Node

SQL ServerSpark

HDFS Data Node

SQL ServerSpark

HDFS Data Node

Kubernetes pod

AnalyticsCustomapps BI

SQL Server master instance

Node Node Node Node Node Node Node

SQL

Data mart

SQL Data Node

SQL Data Node

Compute pool

SQL Compute Node

Storage Storage

SQL Server in action!!

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HPE EPA for SQL Server

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Thank you

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