SlideShare une entreprise Scribd logo
1  sur  12
© 2015 MapR Technologies 1
© 2015 MapR Technologies 2
SEMI-STRUCTURED
DATA
STRUCTURED DATA
1980 2000 20101990 2020
Data Is Doubling Every Two Years
Unstructured data will account
for more than 80% of the data
collected by organizations
Source: Human-Computer Interaction & Knowledge Discovery in Complex Unstructured, Big Data
TotalDataStored
IT
Resources
© 2015 MapR Technologies 3
1980 2000 20101990 2020
Fixed schema
DBA controls structure
Dynamic / Flexible schema
Application controls structure
NON-RELATIONAL DATASTORESRELATIONAL DATABASES
GBs-TBs TBs-PBsVolume
Database
Data Increasingly Stored in Non-Relational Datastores
Structure
Development
Structured Structured, semi-structured and unstructured
Planned (release cycle = months-years) Iterative (release cycle = days-weeks)
© 2015 MapR Technologies 4
How To Bring SQL Into An Unstructured Future?
Familiarity of SQL Flexibility of NoSQL
• SQL
• BI (Tableau, MicroStrategy,
etc.)
• Low latency
• Scalability
• No schema management
– HDFS (Parquet, JSON, etc.)
– HBase
– …
• No transform or silos of data
© 2015 MapR Technologies 5
Industry's First
Schema-free SQL engine
for Big Data
© 2015 MapR Technologies 6
Apache Drill Brings Flexibility & Performance
Access to any data type, any data source
• Relational
• Nested data
• Schema-less
Rapid time to insights
• Query data in-situ
• No Schemas required
• Easy to get started
Integration with existing tools
• ANSI SQL
• BI tool integration
Scale in all dimensions
• TB-PB of scale
• 1000’s of users
• 1000’s of nodes
Granular Security
• Authentication
• Row/column level controls
• De-centralized
© 2015 MapR Technologies 7
Extending Self Service to Schema-free data
Agility&BusinessValue
Use cases for BI
IT-Driven BI
Self-Service BI
Schema-Free
Data Exploration
IT-Driven BI IT-Driven BI
Self-Service BI
Analyst-driven with
no IT dependency
Analyst-driven with
IT support for ETL
IT-created
reports, spreadsheets
1980s -1990s 2000s Now
© 2015 MapR Technologies 8
Enabling “As-It-Happens” Business with Instant Analytics
Hadoop data Data modeling Transformation
Data
movement
(optional)
Users
Hadoop data Users
Governed
approach
Exploratory
approach
New Business questionsSource data evolution
Total time to insight: weeks to months
Total time to insight: minutes
© 2015 MapR Technologies 9
Drill’s Role in the Enterprise Data Architecture
Raw data
• JSON, CSV, ...
“Optimized” data
• Parquet, …
Centrally-structured
data
• Schemas in Hive
Metastore
Relational data
• Highly-structured data
Hive, Impala, Spark SQL
Oracle, Teradata
Exploration
(known and unknown questions)
© 2015 MapR Technologies 10
MapR with Drill is Top-Ranked SQL-on-Hadoop
Source: Gigaom Research, 2015
Key:
• Number indicates companies relative strength across all vectors
• Size of ball indicates company’s relative strength along individual vector
Like other vendors’
offerings, Drill
handles BI and
interactive queries with
great aplomb, but it is
designed to serve these
workloads with data
complexity that goes
well beyond the flat
structured data that
other SQL-on-
Hadoop systems deal
with.
© 2015 MapR Technologies 11
Drill Benefits
Business users Technical IT
Business Analyst,
Data scientists,
VP of Hadoop Dev.,
Director of BI & Analytics,
Enterprise architect
• Self Service access to
Hadoop data from BI
tools
• Agility with no IT
intervention
• Interactive performance
• Drive Hadoop adoption
in company
• Enable better/new BI in
raw, real time and new
data types
• Reduce cost of
traditional systems
© 2015 MapR Technologies 12
Additional Resources
Resource Hub:
MapR.com/Drill
Tutorial:
Apache Drill in
10 Minutes
Whitepaper:
Faster Time to
Value

Contenu connexe

Plus de MapR Technologies

Data Warehouse Modernization: Accelerating Time-To-Action
Data Warehouse Modernization: Accelerating Time-To-Action Data Warehouse Modernization: Accelerating Time-To-Action
Data Warehouse Modernization: Accelerating Time-To-Action MapR Technologies
 
Live Tutorial – Streaming Real-Time Events Using Apache APIs
Live Tutorial – Streaming Real-Time Events Using Apache APIsLive Tutorial – Streaming Real-Time Events Using Apache APIs
Live Tutorial – Streaming Real-Time Events Using Apache APIsMapR Technologies
 
Bringing Structure, Scalability, and Services to Cloud-Scale Storage
Bringing Structure, Scalability, and Services to Cloud-Scale StorageBringing Structure, Scalability, and Services to Cloud-Scale Storage
Bringing Structure, Scalability, and Services to Cloud-Scale StorageMapR Technologies
 
Live Machine Learning Tutorial: Churn Prediction
Live Machine Learning Tutorial: Churn PredictionLive Machine Learning Tutorial: Churn Prediction
Live Machine Learning Tutorial: Churn PredictionMapR Technologies
 
An Introduction to the MapR Converged Data Platform
An Introduction to the MapR Converged Data PlatformAn Introduction to the MapR Converged Data Platform
An Introduction to the MapR Converged Data PlatformMapR Technologies
 
How to Leverage the Cloud for Business Solutions | Strata Data Conference Lon...
How to Leverage the Cloud for Business Solutions | Strata Data Conference Lon...How to Leverage the Cloud for Business Solutions | Strata Data Conference Lon...
How to Leverage the Cloud for Business Solutions | Strata Data Conference Lon...MapR Technologies
 
Best Practices for Data Convergence in Healthcare
Best Practices for Data Convergence in HealthcareBest Practices for Data Convergence in Healthcare
Best Practices for Data Convergence in HealthcareMapR Technologies
 
Geo-Distributed Big Data and Analytics
Geo-Distributed Big Data and AnalyticsGeo-Distributed Big Data and Analytics
Geo-Distributed Big Data and AnalyticsMapR Technologies
 
MapR Product Update - Spring 2017
MapR Product Update - Spring 2017MapR Product Update - Spring 2017
MapR Product Update - Spring 2017MapR Technologies
 
3 Benefits of Multi-Temperature Data Management for Data Analytics
3 Benefits of Multi-Temperature Data Management for Data Analytics3 Benefits of Multi-Temperature Data Management for Data Analytics
3 Benefits of Multi-Temperature Data Management for Data AnalyticsMapR Technologies
 
Cisco & MapR bring 3 Superpowers to SAP HANA Deployments
Cisco & MapR bring 3 Superpowers to SAP HANA DeploymentsCisco & MapR bring 3 Superpowers to SAP HANA Deployments
Cisco & MapR bring 3 Superpowers to SAP HANA DeploymentsMapR Technologies
 
MapR and Cisco Make IT Better
MapR and Cisco Make IT BetterMapR and Cisco Make IT Better
MapR and Cisco Make IT BetterMapR Technologies
 
Evolving from RDBMS to NoSQL + SQL
Evolving from RDBMS to NoSQL + SQLEvolving from RDBMS to NoSQL + SQL
Evolving from RDBMS to NoSQL + SQLMapR Technologies
 
Evolving Beyond the Data Lake: A Story of Wind and Rain
Evolving Beyond the Data Lake: A Story of Wind and RainEvolving Beyond the Data Lake: A Story of Wind and Rain
Evolving Beyond the Data Lake: A Story of Wind and RainMapR Technologies
 
Open Source Innovations in the MapR Ecosystem Pack 2.0
Open Source Innovations in the MapR Ecosystem Pack 2.0Open Source Innovations in the MapR Ecosystem Pack 2.0
Open Source Innovations in the MapR Ecosystem Pack 2.0MapR Technologies
 
How Spark is Enabling the New Wave of Converged Cloud Applications
How Spark is Enabling the New Wave of Converged Cloud Applications How Spark is Enabling the New Wave of Converged Cloud Applications
How Spark is Enabling the New Wave of Converged Cloud Applications MapR Technologies
 
MapR 5.2: Getting More Value from the MapR Converged Data Platform
MapR 5.2: Getting More Value from the MapR Converged Data PlatformMapR 5.2: Getting More Value from the MapR Converged Data Platform
MapR 5.2: Getting More Value from the MapR Converged Data PlatformMapR Technologies
 
MapR on Azure: Getting Value from Big Data in the Cloud -
MapR on Azure: Getting Value from Big Data in the Cloud -MapR on Azure: Getting Value from Big Data in the Cloud -
MapR on Azure: Getting Value from Big Data in the Cloud -MapR Technologies
 
Handling the Extremes: Scaling and Streaming in Finance
Handling the Extremes: Scaling and Streaming in FinanceHandling the Extremes: Scaling and Streaming in Finance
Handling the Extremes: Scaling and Streaming in FinanceMapR Technologies
 
Baptist Health: Solving Healthcare Problems with Big Data
Baptist Health: Solving Healthcare Problems with Big DataBaptist Health: Solving Healthcare Problems with Big Data
Baptist Health: Solving Healthcare Problems with Big DataMapR Technologies
 

Plus de MapR Technologies (20)

Data Warehouse Modernization: Accelerating Time-To-Action
Data Warehouse Modernization: Accelerating Time-To-Action Data Warehouse Modernization: Accelerating Time-To-Action
Data Warehouse Modernization: Accelerating Time-To-Action
 
Live Tutorial – Streaming Real-Time Events Using Apache APIs
Live Tutorial – Streaming Real-Time Events Using Apache APIsLive Tutorial – Streaming Real-Time Events Using Apache APIs
Live Tutorial – Streaming Real-Time Events Using Apache APIs
 
Bringing Structure, Scalability, and Services to Cloud-Scale Storage
Bringing Structure, Scalability, and Services to Cloud-Scale StorageBringing Structure, Scalability, and Services to Cloud-Scale Storage
Bringing Structure, Scalability, and Services to Cloud-Scale Storage
 
Live Machine Learning Tutorial: Churn Prediction
Live Machine Learning Tutorial: Churn PredictionLive Machine Learning Tutorial: Churn Prediction
Live Machine Learning Tutorial: Churn Prediction
 
An Introduction to the MapR Converged Data Platform
An Introduction to the MapR Converged Data PlatformAn Introduction to the MapR Converged Data Platform
An Introduction to the MapR Converged Data Platform
 
How to Leverage the Cloud for Business Solutions | Strata Data Conference Lon...
How to Leverage the Cloud for Business Solutions | Strata Data Conference Lon...How to Leverage the Cloud for Business Solutions | Strata Data Conference Lon...
How to Leverage the Cloud for Business Solutions | Strata Data Conference Lon...
 
Best Practices for Data Convergence in Healthcare
Best Practices for Data Convergence in HealthcareBest Practices for Data Convergence in Healthcare
Best Practices for Data Convergence in Healthcare
 
Geo-Distributed Big Data and Analytics
Geo-Distributed Big Data and AnalyticsGeo-Distributed Big Data and Analytics
Geo-Distributed Big Data and Analytics
 
MapR Product Update - Spring 2017
MapR Product Update - Spring 2017MapR Product Update - Spring 2017
MapR Product Update - Spring 2017
 
3 Benefits of Multi-Temperature Data Management for Data Analytics
3 Benefits of Multi-Temperature Data Management for Data Analytics3 Benefits of Multi-Temperature Data Management for Data Analytics
3 Benefits of Multi-Temperature Data Management for Data Analytics
 
Cisco & MapR bring 3 Superpowers to SAP HANA Deployments
Cisco & MapR bring 3 Superpowers to SAP HANA DeploymentsCisco & MapR bring 3 Superpowers to SAP HANA Deployments
Cisco & MapR bring 3 Superpowers to SAP HANA Deployments
 
MapR and Cisco Make IT Better
MapR and Cisco Make IT BetterMapR and Cisco Make IT Better
MapR and Cisco Make IT Better
 
Evolving from RDBMS to NoSQL + SQL
Evolving from RDBMS to NoSQL + SQLEvolving from RDBMS to NoSQL + SQL
Evolving from RDBMS to NoSQL + SQL
 
Evolving Beyond the Data Lake: A Story of Wind and Rain
Evolving Beyond the Data Lake: A Story of Wind and RainEvolving Beyond the Data Lake: A Story of Wind and Rain
Evolving Beyond the Data Lake: A Story of Wind and Rain
 
Open Source Innovations in the MapR Ecosystem Pack 2.0
Open Source Innovations in the MapR Ecosystem Pack 2.0Open Source Innovations in the MapR Ecosystem Pack 2.0
Open Source Innovations in the MapR Ecosystem Pack 2.0
 
How Spark is Enabling the New Wave of Converged Cloud Applications
How Spark is Enabling the New Wave of Converged Cloud Applications How Spark is Enabling the New Wave of Converged Cloud Applications
How Spark is Enabling the New Wave of Converged Cloud Applications
 
MapR 5.2: Getting More Value from the MapR Converged Data Platform
MapR 5.2: Getting More Value from the MapR Converged Data PlatformMapR 5.2: Getting More Value from the MapR Converged Data Platform
MapR 5.2: Getting More Value from the MapR Converged Data Platform
 
MapR on Azure: Getting Value from Big Data in the Cloud -
MapR on Azure: Getting Value from Big Data in the Cloud -MapR on Azure: Getting Value from Big Data in the Cloud -
MapR on Azure: Getting Value from Big Data in the Cloud -
 
Handling the Extremes: Scaling and Streaming in Finance
Handling the Extremes: Scaling and Streaming in FinanceHandling the Extremes: Scaling and Streaming in Finance
Handling the Extremes: Scaling and Streaming in Finance
 
Baptist Health: Solving Healthcare Problems with Big Data
Baptist Health: Solving Healthcare Problems with Big DataBaptist Health: Solving Healthcare Problems with Big Data
Baptist Health: Solving Healthcare Problems with Big Data
 

Dernier

The Ultimate Guide to Choosing WordPress Pros and Cons
The Ultimate Guide to Choosing WordPress Pros and ConsThe Ultimate Guide to Choosing WordPress Pros and Cons
The Ultimate Guide to Choosing WordPress Pros and ConsPixlogix Infotech
 
What's New in Teams Calling, Meetings and Devices March 2024
What's New in Teams Calling, Meetings and Devices March 2024What's New in Teams Calling, Meetings and Devices March 2024
What's New in Teams Calling, Meetings and Devices March 2024Stephanie Beckett
 
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)Mark Simos
 
Advanced Computer Architecture – An Introduction
Advanced Computer Architecture – An IntroductionAdvanced Computer Architecture – An Introduction
Advanced Computer Architecture – An IntroductionDilum Bandara
 
Search Engine Optimization SEO PDF for 2024.pdf
Search Engine Optimization SEO PDF for 2024.pdfSearch Engine Optimization SEO PDF for 2024.pdf
Search Engine Optimization SEO PDF for 2024.pdfRankYa
 
DSPy a system for AI to Write Prompts and Do Fine Tuning
DSPy a system for AI to Write Prompts and Do Fine TuningDSPy a system for AI to Write Prompts and Do Fine Tuning
DSPy a system for AI to Write Prompts and Do Fine TuningLars Bell
 
Unleash Your Potential - Namagunga Girls Coding Club
Unleash Your Potential - Namagunga Girls Coding ClubUnleash Your Potential - Namagunga Girls Coding Club
Unleash Your Potential - Namagunga Girls Coding ClubKalema Edgar
 
TrustArc Webinar - How to Build Consumer Trust Through Data Privacy
TrustArc Webinar - How to Build Consumer Trust Through Data PrivacyTrustArc Webinar - How to Build Consumer Trust Through Data Privacy
TrustArc Webinar - How to Build Consumer Trust Through Data PrivacyTrustArc
 
From Family Reminiscence to Scholarly Archive .
From Family Reminiscence to Scholarly Archive .From Family Reminiscence to Scholarly Archive .
From Family Reminiscence to Scholarly Archive .Alan Dix
 
WordPress Websites for Engineers: Elevate Your Brand
WordPress Websites for Engineers: Elevate Your BrandWordPress Websites for Engineers: Elevate Your Brand
WordPress Websites for Engineers: Elevate Your Brandgvaughan
 
New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024BookNet Canada
 
Human Factors of XR: Using Human Factors to Design XR Systems
Human Factors of XR: Using Human Factors to Design XR SystemsHuman Factors of XR: Using Human Factors to Design XR Systems
Human Factors of XR: Using Human Factors to Design XR SystemsMark Billinghurst
 
Unraveling Multimodality with Large Language Models.pdf
Unraveling Multimodality with Large Language Models.pdfUnraveling Multimodality with Large Language Models.pdf
Unraveling Multimodality with Large Language Models.pdfAlex Barbosa Coqueiro
 
Developer Data Modeling Mistakes: From Postgres to NoSQL
Developer Data Modeling Mistakes: From Postgres to NoSQLDeveloper Data Modeling Mistakes: From Postgres to NoSQL
Developer Data Modeling Mistakes: From Postgres to NoSQLScyllaDB
 
Dev Dives: Streamline document processing with UiPath Studio Web
Dev Dives: Streamline document processing with UiPath Studio WebDev Dives: Streamline document processing with UiPath Studio Web
Dev Dives: Streamline document processing with UiPath Studio WebUiPathCommunity
 
Anypoint Exchange: It’s Not Just a Repo!
Anypoint Exchange: It’s Not Just a Repo!Anypoint Exchange: It’s Not Just a Repo!
Anypoint Exchange: It’s Not Just a Repo!Manik S Magar
 
Designing IA for AI - Information Architecture Conference 2024
Designing IA for AI - Information Architecture Conference 2024Designing IA for AI - Information Architecture Conference 2024
Designing IA for AI - Information Architecture Conference 2024Enterprise Knowledge
 
SIP trunking in Janus @ Kamailio World 2024
SIP trunking in Janus @ Kamailio World 2024SIP trunking in Janus @ Kamailio World 2024
SIP trunking in Janus @ Kamailio World 2024Lorenzo Miniero
 
DevEX - reference for building teams, processes, and platforms
DevEX - reference for building teams, processes, and platformsDevEX - reference for building teams, processes, and platforms
DevEX - reference for building teams, processes, and platformsSergiu Bodiu
 

Dernier (20)

The Ultimate Guide to Choosing WordPress Pros and Cons
The Ultimate Guide to Choosing WordPress Pros and ConsThe Ultimate Guide to Choosing WordPress Pros and Cons
The Ultimate Guide to Choosing WordPress Pros and Cons
 
What's New in Teams Calling, Meetings and Devices March 2024
What's New in Teams Calling, Meetings and Devices March 2024What's New in Teams Calling, Meetings and Devices March 2024
What's New in Teams Calling, Meetings and Devices March 2024
 
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)
Tampa BSides - Chef's Tour of Microsoft Security Adoption Framework (SAF)
 
Advanced Computer Architecture – An Introduction
Advanced Computer Architecture – An IntroductionAdvanced Computer Architecture – An Introduction
Advanced Computer Architecture – An Introduction
 
Search Engine Optimization SEO PDF for 2024.pdf
Search Engine Optimization SEO PDF for 2024.pdfSearch Engine Optimization SEO PDF for 2024.pdf
Search Engine Optimization SEO PDF for 2024.pdf
 
DSPy a system for AI to Write Prompts and Do Fine Tuning
DSPy a system for AI to Write Prompts and Do Fine TuningDSPy a system for AI to Write Prompts and Do Fine Tuning
DSPy a system for AI to Write Prompts and Do Fine Tuning
 
Unleash Your Potential - Namagunga Girls Coding Club
Unleash Your Potential - Namagunga Girls Coding ClubUnleash Your Potential - Namagunga Girls Coding Club
Unleash Your Potential - Namagunga Girls Coding Club
 
TrustArc Webinar - How to Build Consumer Trust Through Data Privacy
TrustArc Webinar - How to Build Consumer Trust Through Data PrivacyTrustArc Webinar - How to Build Consumer Trust Through Data Privacy
TrustArc Webinar - How to Build Consumer Trust Through Data Privacy
 
E-Vehicle_Hacking_by_Parul Sharma_null_owasp.pptx
E-Vehicle_Hacking_by_Parul Sharma_null_owasp.pptxE-Vehicle_Hacking_by_Parul Sharma_null_owasp.pptx
E-Vehicle_Hacking_by_Parul Sharma_null_owasp.pptx
 
From Family Reminiscence to Scholarly Archive .
From Family Reminiscence to Scholarly Archive .From Family Reminiscence to Scholarly Archive .
From Family Reminiscence to Scholarly Archive .
 
WordPress Websites for Engineers: Elevate Your Brand
WordPress Websites for Engineers: Elevate Your BrandWordPress Websites for Engineers: Elevate Your Brand
WordPress Websites for Engineers: Elevate Your Brand
 
New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
 
Human Factors of XR: Using Human Factors to Design XR Systems
Human Factors of XR: Using Human Factors to Design XR SystemsHuman Factors of XR: Using Human Factors to Design XR Systems
Human Factors of XR: Using Human Factors to Design XR Systems
 
Unraveling Multimodality with Large Language Models.pdf
Unraveling Multimodality with Large Language Models.pdfUnraveling Multimodality with Large Language Models.pdf
Unraveling Multimodality with Large Language Models.pdf
 
Developer Data Modeling Mistakes: From Postgres to NoSQL
Developer Data Modeling Mistakes: From Postgres to NoSQLDeveloper Data Modeling Mistakes: From Postgres to NoSQL
Developer Data Modeling Mistakes: From Postgres to NoSQL
 
Dev Dives: Streamline document processing with UiPath Studio Web
Dev Dives: Streamline document processing with UiPath Studio WebDev Dives: Streamline document processing with UiPath Studio Web
Dev Dives: Streamline document processing with UiPath Studio Web
 
Anypoint Exchange: It’s Not Just a Repo!
Anypoint Exchange: It’s Not Just a Repo!Anypoint Exchange: It’s Not Just a Repo!
Anypoint Exchange: It’s Not Just a Repo!
 
Designing IA for AI - Information Architecture Conference 2024
Designing IA for AI - Information Architecture Conference 2024Designing IA for AI - Information Architecture Conference 2024
Designing IA for AI - Information Architecture Conference 2024
 
SIP trunking in Janus @ Kamailio World 2024
SIP trunking in Janus @ Kamailio World 2024SIP trunking in Janus @ Kamailio World 2024
SIP trunking in Janus @ Kamailio World 2024
 
DevEX - reference for building teams, processes, and platforms
DevEX - reference for building teams, processes, and platformsDevEX - reference for building teams, processes, and platforms
DevEX - reference for building teams, processes, and platforms
 

Introduction to Apache Drill 1.0

  • 1. © 2015 MapR Technologies 1
  • 2. © 2015 MapR Technologies 2 SEMI-STRUCTURED DATA STRUCTURED DATA 1980 2000 20101990 2020 Data Is Doubling Every Two Years Unstructured data will account for more than 80% of the data collected by organizations Source: Human-Computer Interaction & Knowledge Discovery in Complex Unstructured, Big Data TotalDataStored IT Resources
  • 3. © 2015 MapR Technologies 3 1980 2000 20101990 2020 Fixed schema DBA controls structure Dynamic / Flexible schema Application controls structure NON-RELATIONAL DATASTORESRELATIONAL DATABASES GBs-TBs TBs-PBsVolume Database Data Increasingly Stored in Non-Relational Datastores Structure Development Structured Structured, semi-structured and unstructured Planned (release cycle = months-years) Iterative (release cycle = days-weeks)
  • 4. © 2015 MapR Technologies 4 How To Bring SQL Into An Unstructured Future? Familiarity of SQL Flexibility of NoSQL • SQL • BI (Tableau, MicroStrategy, etc.) • Low latency • Scalability • No schema management – HDFS (Parquet, JSON, etc.) – HBase – … • No transform or silos of data
  • 5. © 2015 MapR Technologies 5 Industry's First Schema-free SQL engine for Big Data
  • 6. © 2015 MapR Technologies 6 Apache Drill Brings Flexibility & Performance Access to any data type, any data source • Relational • Nested data • Schema-less Rapid time to insights • Query data in-situ • No Schemas required • Easy to get started Integration with existing tools • ANSI SQL • BI tool integration Scale in all dimensions • TB-PB of scale • 1000’s of users • 1000’s of nodes Granular Security • Authentication • Row/column level controls • De-centralized
  • 7. © 2015 MapR Technologies 7 Extending Self Service to Schema-free data Agility&BusinessValue Use cases for BI IT-Driven BI Self-Service BI Schema-Free Data Exploration IT-Driven BI IT-Driven BI Self-Service BI Analyst-driven with no IT dependency Analyst-driven with IT support for ETL IT-created reports, spreadsheets 1980s -1990s 2000s Now
  • 8. © 2015 MapR Technologies 8 Enabling “As-It-Happens” Business with Instant Analytics Hadoop data Data modeling Transformation Data movement (optional) Users Hadoop data Users Governed approach Exploratory approach New Business questionsSource data evolution Total time to insight: weeks to months Total time to insight: minutes
  • 9. © 2015 MapR Technologies 9 Drill’s Role in the Enterprise Data Architecture Raw data • JSON, CSV, ... “Optimized” data • Parquet, … Centrally-structured data • Schemas in Hive Metastore Relational data • Highly-structured data Hive, Impala, Spark SQL Oracle, Teradata Exploration (known and unknown questions)
  • 10. © 2015 MapR Technologies 10 MapR with Drill is Top-Ranked SQL-on-Hadoop Source: Gigaom Research, 2015 Key: • Number indicates companies relative strength across all vectors • Size of ball indicates company’s relative strength along individual vector Like other vendors’ offerings, Drill handles BI and interactive queries with great aplomb, but it is designed to serve these workloads with data complexity that goes well beyond the flat structured data that other SQL-on- Hadoop systems deal with.
  • 11. © 2015 MapR Technologies 11 Drill Benefits Business users Technical IT Business Analyst, Data scientists, VP of Hadoop Dev., Director of BI & Analytics, Enterprise architect • Self Service access to Hadoop data from BI tools • Agility with no IT intervention • Interactive performance • Drive Hadoop adoption in company • Enable better/new BI in raw, real time and new data types • Reduce cost of traditional systems
  • 12. © 2015 MapR Technologies 12 Additional Resources Resource Hub: MapR.com/Drill Tutorial: Apache Drill in 10 Minutes Whitepaper: Faster Time to Value