Converging Database Transactions and Analytics

•

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delivered at the Gartner Data and Analytics 2018 show in Texas. This presentation discusses real-time applications and their impact on existing data infrastructures

Technology

Converging Analytics
and Transactions to
Unlock Real-Time
Opportunities
by Mike Boyarski
@boyarski
@memsql

2
People Respond to
Superior Customer Experience

3
Loyalty Revenue Insight
People Respond to
Superior Customer Experience
And that drives …

4
Real-Time
Applications are
shaping the
customer
experience

8
And They Span Industries
Financial Services
- Fraud detection
- Portfolio management
- Risk management
Media and Communications
- Operational monitoring
- Advertising analytics
- Content personalization
Energy and Utilities
- Predictive maintenance
- Supply chain optimization
- Grid management
Healthcare
- Real-time patient care
- Prescription management
- Contract management

9
What makes an application a
“Real-Time Application”?

10
Live Data Scalable
Intelligent Operational

11
Let’s review the impact of
Real-Time Applications on
existing data infrastructures

12
Real-Time Applications demand:
§ Live Data Architecture
§ Scalability
§ Transaction and Analytics Convergence

14
Traditional Data Architecture
Data Warehouse
Application
Sources
Data
Integration
Operational Data
Store
Application
ETL

15
Traditional Data Architecture
Data Warehouse
Application
Sources
Data
Integration
Operational Data
Store
Application
ETL
Batch data
Integration
processes
!

16
Traditional Data Architecture
Data Warehouse
Application
Sources
Data
Integration
Operational Data
Store
Application
ETL
!
Multiple
specialized
databases

17
Traditional Data Architecture
Data Warehouse
Application
Sources
Data
Integration
Operational Data
Store
Application
ETL
!
Stale data due
to architecture
complexity

18
Live Data Architecture
Application
Sources
Data
Integration
Operational and
Analytic Data Store
Application
Change
Data
Capture

19
Live Data Architecture
Application
Sources
Data
Integration
Operational and
Analytic Data Store
Application
Change
Data
Capture
Real-Time Data
Synchronization
a

20
Live Data Architecture
Application
Sources
Data
Integration
Operational and
Analytic Data Store
Application
Change
Data
Capture
Converged Operational
Database and Data Warehouse
a

21
Live Data Architecture
Application
Sources
Data
Integration
Operational and
Analytic Data Store
Application
Change
Data
Capture
Accurate live data
view
a

Planned Concurrency Large Scale Concurrency
Scale Up Scale Out

MemSQL scales across nodes
As a distributed database, MemSQL scales out
with industry standard servers or cloud instances

25
Transactions and Analytics
Convergence

29
But this introduces complexity and drag

30
Convergence drives simplicity and speed

31
Operational
- ACID Transactions
- Fast data ingestion
- ANSI SQL
- Secure
Convergence drives simplicity and speed

32
Analytic
- Fast queries
- Large concurrency
- Petabyte scale
Convergence drives simplicity and speed
Operational
- ACID Transactions
- Fast data ingestion
- ANSI SQL
- Secure

MemSQL Unified Architecture
33
Historical Data
Disk-optimized tables
with compression for
fast analytic queries
Live Data
Memory optimized tables
for analyzing real-time
events
Streaming Ingest
Real-time data pipelines
with exactly-once
semantics

MemSQL: The Database for Real-Time Applications
Converging Transactions and Analytics at Scale
34
Run
Anywhere
Any cloud, hybrid, or multicloud
On-premises
Low cost standard hardware
Scale
Transactions and Analytics
Petabyte scale
In-memory and disk-based
Unified mixed workload architecture
Power
Real-Time Applications
Fast ingestion and queries
Operational capabilities
Multi-model and data support

36
Stop by the MemSQL
booth (#212), enter to win
a Google Home!

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Converging Database Transactions and Analytics

1. Converging Analytics and Transactions to Unlock Real-Time Opportunities by Mike Boyarski @boyarski @memsql

2. 2 People Respond to Superior Customer Experience

3. 3 Loyalty Revenue Insight People Respond to Superior Customer Experience And that drives …

4. 4 Real-Time Applications are shaping the customer experience

5. 5 They optimize the travel experience

6. 6 Enrich shopping experience

7. 7 Improve the banking experience

8. 8 And They Span Industries Financial Services - Fraud detection - Portfolio management - Risk management Media and Communications - Operational monitoring - Advertising analytics - Content personalization Energy and Utilities - Predictive maintenance - Supply chain optimization - Grid management Healthcare - Real-time patient care - Prescription management - Contract management

9. 9 What makes an application a “Real-Time Application”?

10. 10 Live Data Scalable Intelligent Operational

11. 11 Let’s review the impact of Real-Time Applications on existing data infrastructures

12. 12 Real-Time Applications demand: § Live Data Architecture § Scalability § Transaction and Analytics Convergence

13. 13 Live Data Architecture

14. 14 Traditional Data Architecture Data Warehouse Application Sources Data Integration Operational Data Store Application ETL

15. 15 Traditional Data Architecture Data Warehouse Application Sources Data Integration Operational Data Store Application ETL Batch data Integration processes !

16. 16 Traditional Data Architecture Data Warehouse Application Sources Data Integration Operational Data Store Application ETL ! Multiple specialized databases

17. 17 Traditional Data Architecture Data Warehouse Application Sources Data Integration Operational Data Store Application ETL ! Stale data due to architecture complexity

18. 18 Live Data Architecture Application Sources Data Integration Operational and Analytic Data Store Application Change Data Capture

19. 19 Live Data Architecture Application Sources Data Integration Operational and Analytic Data Store Application Change Data Capture Real-Time Data Synchronization a

20. 20 Live Data Architecture Application Sources Data Integration Operational and Analytic Data Store Application Change Data Capture Converged Operational Database and Data Warehouse a

21. 21 Live Data Architecture Application Sources Data Integration Operational and Analytic Data Store Application Change Data Capture Accurate live data view a

22. 22 Scalability

23. Planned Concurrency Large Scale Concurrency Scale Up Scale Out

24. MemSQL scales across nodes As a distributed database, MemSQL scales out with industry standard servers or cloud instances

25. 25 Transactions and Analytics Convergence

26. 26 We started with transactions

27. 27 Then did analytics and transactions

28. 28 So we separated the two

29. 29 But this introduces complexity and drag

30. 30 Convergence drives simplicity and speed

31. 31 Operational - ACID Transactions - Fast data ingestion - ANSI SQL - Secure Convergence drives simplicity and speed

32. 32 Analytic - Fast queries - Large concurrency - Petabyte scale Convergence drives simplicity and speed Operational - ACID Transactions - Fast data ingestion - ANSI SQL - Secure

33. MemSQL Unified Architecture 33 Historical Data Disk-optimized tables with compression for fast analytic queries Live Data Memory optimized tables for analyzing real-time events Streaming Ingest Real-time data pipelines with exactly-once semantics

34. MemSQL: The Database for Real-Time Applications Converging Transactions and Analytics at Scale 34 Run Anywhere Any cloud, hybrid, or multicloud On-premises Low cost standard hardware Scale Transactions and Analytics Petabyte scale In-memory and disk-based Unified mixed workload architecture Power Real-Time Applications Fast ingestion and queries Operational capabilities Multi-model and data support

35. 35 Let’s Show a Demo!

36. 36 Stop by the MemSQL booth (#212), enter to win a Google Home!

Converging Database Transactions and Analytics

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