SlideShare a Scribd company logo
1 of 2
Download to read offline
Key Benefits
Fast Analytics.
Achieve up to 100x performance
improvements.
Massive Scalability.
Linear scaling lets you analyze any
amount of data or level of detail while
maintaining quality and performance,
on-premises or in cloud or hybrid
environments.
Business Agility.
Customize, iterate and launch
analytic applications faster. Reduce
friction and react in real-time
to dynamic market conditions,
increasing analytic sophistication,
changing user needs, and evolving
data analytics infrastructure.
Extreme Value.
Improve price-performance up to
200x compared with traditional
systems or analytic appliances.
High-Performance Analytics for the Enterprise
Tackle big data 2.0 initiatives with Actian Matrix. Its massively parallel architecture,
columnar database structure and in-database analytics deliver unrivaled
performance and scalability. Query optimization and extensibility frameworks and
a library of advanced analytic functions help you transform big data into actionable
insights and business value.
Massively Parallel Processing Architecture
Actian Matrix is geared to the demands of massive data, many users and significant
analytic complexity.
• 	Columnar Database Structure: Query all of your data and get precisely the
data you need, without the burden of handling extraneous data returned by
traditional row-oriented databases.
• 	Adaptive Compression: Maximize query performance while conserving
storage resources thanks to data compression that adapts to match data types.
• 	Dynamic Compilation: Queries compiled at execution deliver performance up
to 100 times faster for analytic joins and up to 50 times faster for more complex
queries and aggregations.
• 	High-Speed Network Interconnect: Communication between nodes within
an Actian Matrix cluster takes place using a custom UDP-based protocol,
supporting near-linear scalability.
• 	In-Memory Analytics: High-performance and parallelism support a 10-100x
improvement in analytic performance.
• 	Adaptive Workload Management: Analytic workloads of groups and
applications are intelligently balanced based on defined priorities and available
resources so you can deliver timely insights to all users. Resource groups can
be defined by user, department, application, or query type; and each group can
be assigned a unique priority weighting. More efficient workload management
and more productive users lead to more analytic value.
Unconstrained Analytics
Analyze efficiently. The Actian Matrix Optimizer Framework adjusts concurrent
queries, handles more than 1,000 joins, and dynamically shares computing
resources to run analytics across an unlimited number of nodes. Complex analytics
are converted into simpler logical components. Each query travels the optimal path
given the traffic conditions at run time. Actian makes it easy to create and add your
own optimizations for: SQL, Planning, Execution, Communications and I/O.
Extreme SQL Rewrite Optimization
Rewrites logical query expressions to alternative yet semantically equivalent
forms. Applies fundamental non-rule-based as well as iterative rule-based
transformations that are re-expressed as SQL text and then re-parsed. Predicate
optimizations improve when and how data is filtered during execution of a
query plan.
Actian Analytics Database -
Matrix
Data Sheet
Extreme Join Optimization
After an incoming SQL query has been optimized, our patented Planning Optimizer quickly selects the best
planning scenario, reducing options from billions, at runtime. Plan queries with many tables by partially
ordering them prior to exhaustive physical planning. Integrated Planning and Execution Optimizers
improve table grouping for exceptional query performance.
Extreme Execution Optimization
The Execution Optimizer creates a query plan and executes the query, ensuring efficient routing of data
across the cluster. A planning execution optimizer improves query planning and execution performance.
The result is superior join order, sort order exploitation and data distribution.
Analyze any data, any way. The Actian Matrix Extensibility Framework opens the core database to diverse
data sources and analytics through our On-Demand Integration modules. A library of 700+ advanced analytic
functions can be accessed from Actian Matrix to expedite analytic processing. Added functions can easily be
created and made available for reuse by any user or visualization tool.
Analyze on the fly. Bring in data from a data warehouse and leverage Hadoop analytics before or in the midst
of a query. It’s the perfect solution for offloading analytics from a data warehouse or bringing in internet and
already analyzed social media data.
Easy Integration and Deployment
Use the Freshest Data from Any Source: Massively parallel data loads and schema-neutrality ensure
applications and users of fast access to the most current data available without ongoing database tuning.
Use Any Dashboard, BI and DI Tools: Actian Matrix works seamlessly with Tableau, MicroStrategy, IBM,
Cognos and SAP Business Objects, as well as Informatica and other data integration platforms.
Deploy with Maximum Flexibility: Deploy Actian Matrix on-premises, on a public cloud such as Amazon EC2
or Rackspace, or on the MicroStrategy Cloud.
Choose the Best Servers and Storage: Actian Matrix supports with data center standards for servers and
storage. Take advantage of hardware innovations now, not 12-18 months from now when they become
available in an analytic appliance.
DATA
Accelerate
BI
Accelerate
Analytics
Traditional
Enterprise
Social
Internet
of Things
SaaS
Delight Customers
Improve
Competitive Edge
Reduce Risk
and Cost
Innovate
NoSQL
Actian Analytics Accelerators
Actian Analytics Platform™
Accelerate
Hadoop
VALUE
www.actian.com
500 Arguello Street, Ste. 200, Redwood City, CA 94063
+1.888.446.4737 [Toll Free] | +1.650.587.5500 [Tel]
© 2014 Actian Corporation. Actian, Big Data for the Rest of Us, Accelerating Big Data 2.0, and Actian
Analytics Platform are trademarks of Actian Corporation and its subsidiaries. All other trademarks, trade
names, service marks, and logos referenced herein belong to their respective companies. (DS06-0514)

More Related Content

What's hot

Data visualization with sql analytics
Data visualization with sql analyticsData visualization with sql analytics
Data visualization with sql analyticsDatabricks
 
Leveraging cloud database connectors to automate analytics in alteryx
Leveraging cloud database connectors to automate analytics in alteryxLeveraging cloud database connectors to automate analytics in alteryx
Leveraging cloud database connectors to automate analytics in alteryxGrazitti Interactive
 
Develop scalable analytical solutions with Azure Data Factory & Azure SQL Dat...
Develop scalable analytical solutions with Azure Data Factory & Azure SQL Dat...Develop scalable analytical solutions with Azure Data Factory & Azure SQL Dat...
Develop scalable analytical solutions with Azure Data Factory & Azure SQL Dat...Microsoft Tech Community
 
Azure Data Factory | Moving On-Premise Data to Azure Cloud | Microsoft Azure ...
Azure Data Factory | Moving On-Premise Data to Azure Cloud | Microsoft Azure ...Azure Data Factory | Moving On-Premise Data to Azure Cloud | Microsoft Azure ...
Azure Data Factory | Moving On-Premise Data to Azure Cloud | Microsoft Azure ...Edureka!
 
Managing R&D Data on Parallel Compute Infrastructure
Managing R&D Data on Parallel Compute InfrastructureManaging R&D Data on Parallel Compute Infrastructure
Managing R&D Data on Parallel Compute InfrastructureDatabricks
 
A complete-guide-to-oracle-to-redshift-migration
A complete-guide-to-oracle-to-redshift-migrationA complete-guide-to-oracle-to-redshift-migration
A complete-guide-to-oracle-to-redshift-migrationbindu1512
 
Unleash the power of Azure Data Factory
Unleash the power of Azure Data Factory Unleash the power of Azure Data Factory
Unleash the power of Azure Data Factory Sergio Zenatti Filho
 
Introduction to Cortana Analytics
Introduction to Cortana AnalyticsIntroduction to Cortana Analytics
Introduction to Cortana AnalyticsChris Testa-O'Neill
 
Data Governance a Business Value Driven Approach
Data Governance a Business Value Driven ApproachData Governance a Business Value Driven Approach
Data Governance a Business Value Driven ApproachTridant
 
Microsoft SharePoint - Extend PowerPivot with Panorma NovaView Presentation
Microsoft SharePoint - Extend PowerPivot with Panorma NovaView PresentationMicrosoft SharePoint - Extend PowerPivot with Panorma NovaView Presentation
Microsoft SharePoint - Extend PowerPivot with Panorma NovaView PresentationMicrosoft Private Cloud
 
Azure Analysis Services (Azure Bootcamp 2018)
Azure Analysis Services (Azure Bootcamp 2018)Azure Analysis Services (Azure Bootcamp 2018)
Azure Analysis Services (Azure Bootcamp 2018)Turner Kunkel
 
Building a MLOps Platform Around MLflow to Enable Model Productionalization i...
Building a MLOps Platform Around MLflow to Enable Model Productionalization i...Building a MLOps Platform Around MLflow to Enable Model Productionalization i...
Building a MLOps Platform Around MLflow to Enable Model Productionalization i...Databricks
 
Intro to Delta Lake
Intro to Delta LakeIntro to Delta Lake
Intro to Delta LakeDatabricks
 
Azure Data Factory v2
Azure Data Factory v2Azure Data Factory v2
Azure Data Factory v2inovex GmbH
 
Spark Summit Keynote by Seshu Adunuthula
Spark Summit Keynote by Seshu AdunuthulaSpark Summit Keynote by Seshu Adunuthula
Spark Summit Keynote by Seshu AdunuthulaSpark Summit
 
Azure data analytics platform - A reference architecture
Azure data analytics platform - A reference architecture Azure data analytics platform - A reference architecture
Azure data analytics platform - A reference architecture Rajesh Kumar
 
Azure cafe marketplace with looker data analytics
Azure cafe marketplace with looker data analyticsAzure cafe marketplace with looker data analytics
Azure cafe marketplace with looker data analyticsMark Kromer
 
Cepta The Future of Data with Power BI
Cepta The Future of Data with Power BICepta The Future of Data with Power BI
Cepta The Future of Data with Power BIKellyn Pot'Vin-Gorman
 
Introducing MLflow for End-to-End Machine Learning on Databricks
Introducing MLflow for End-to-End Machine Learning on DatabricksIntroducing MLflow for End-to-End Machine Learning on Databricks
Introducing MLflow for End-to-End Machine Learning on DatabricksDatabricks
 
Snowflake + Power BI: Cloud Analytics for Everyone
Snowflake + Power BI: Cloud Analytics for EveryoneSnowflake + Power BI: Cloud Analytics for Everyone
Snowflake + Power BI: Cloud Analytics for EveryoneAngel Abundez
 

What's hot (20)

Data visualization with sql analytics
Data visualization with sql analyticsData visualization with sql analytics
Data visualization with sql analytics
 
Leveraging cloud database connectors to automate analytics in alteryx
Leveraging cloud database connectors to automate analytics in alteryxLeveraging cloud database connectors to automate analytics in alteryx
Leveraging cloud database connectors to automate analytics in alteryx
 
Develop scalable analytical solutions with Azure Data Factory & Azure SQL Dat...
Develop scalable analytical solutions with Azure Data Factory & Azure SQL Dat...Develop scalable analytical solutions with Azure Data Factory & Azure SQL Dat...
Develop scalable analytical solutions with Azure Data Factory & Azure SQL Dat...
 
Azure Data Factory | Moving On-Premise Data to Azure Cloud | Microsoft Azure ...
Azure Data Factory | Moving On-Premise Data to Azure Cloud | Microsoft Azure ...Azure Data Factory | Moving On-Premise Data to Azure Cloud | Microsoft Azure ...
Azure Data Factory | Moving On-Premise Data to Azure Cloud | Microsoft Azure ...
 
Managing R&D Data on Parallel Compute Infrastructure
Managing R&D Data on Parallel Compute InfrastructureManaging R&D Data on Parallel Compute Infrastructure
Managing R&D Data on Parallel Compute Infrastructure
 
A complete-guide-to-oracle-to-redshift-migration
A complete-guide-to-oracle-to-redshift-migrationA complete-guide-to-oracle-to-redshift-migration
A complete-guide-to-oracle-to-redshift-migration
 
Unleash the power of Azure Data Factory
Unleash the power of Azure Data Factory Unleash the power of Azure Data Factory
Unleash the power of Azure Data Factory
 
Introduction to Cortana Analytics
Introduction to Cortana AnalyticsIntroduction to Cortana Analytics
Introduction to Cortana Analytics
 
Data Governance a Business Value Driven Approach
Data Governance a Business Value Driven ApproachData Governance a Business Value Driven Approach
Data Governance a Business Value Driven Approach
 
Microsoft SharePoint - Extend PowerPivot with Panorma NovaView Presentation
Microsoft SharePoint - Extend PowerPivot with Panorma NovaView PresentationMicrosoft SharePoint - Extend PowerPivot with Panorma NovaView Presentation
Microsoft SharePoint - Extend PowerPivot with Panorma NovaView Presentation
 
Azure Analysis Services (Azure Bootcamp 2018)
Azure Analysis Services (Azure Bootcamp 2018)Azure Analysis Services (Azure Bootcamp 2018)
Azure Analysis Services (Azure Bootcamp 2018)
 
Building a MLOps Platform Around MLflow to Enable Model Productionalization i...
Building a MLOps Platform Around MLflow to Enable Model Productionalization i...Building a MLOps Platform Around MLflow to Enable Model Productionalization i...
Building a MLOps Platform Around MLflow to Enable Model Productionalization i...
 
Intro to Delta Lake
Intro to Delta LakeIntro to Delta Lake
Intro to Delta Lake
 
Azure Data Factory v2
Azure Data Factory v2Azure Data Factory v2
Azure Data Factory v2
 
Spark Summit Keynote by Seshu Adunuthula
Spark Summit Keynote by Seshu AdunuthulaSpark Summit Keynote by Seshu Adunuthula
Spark Summit Keynote by Seshu Adunuthula
 
Azure data analytics platform - A reference architecture
Azure data analytics platform - A reference architecture Azure data analytics platform - A reference architecture
Azure data analytics platform - A reference architecture
 
Azure cafe marketplace with looker data analytics
Azure cafe marketplace with looker data analyticsAzure cafe marketplace with looker data analytics
Azure cafe marketplace with looker data analytics
 
Cepta The Future of Data with Power BI
Cepta The Future of Data with Power BICepta The Future of Data with Power BI
Cepta The Future of Data with Power BI
 
Introducing MLflow for End-to-End Machine Learning on Databricks
Introducing MLflow for End-to-End Machine Learning on DatabricksIntroducing MLflow for End-to-End Machine Learning on Databricks
Introducing MLflow for End-to-End Machine Learning on Databricks
 
Snowflake + Power BI: Cloud Analytics for Everyone
Snowflake + Power BI: Cloud Analytics for EveryoneSnowflake + Power BI: Cloud Analytics for Everyone
Snowflake + Power BI: Cloud Analytics for Everyone
 

Similar to High-Performance Analytics for Big Data with Actian Matrix

Data Modernization_Harinath Susairaj.pptx
Data Modernization_Harinath Susairaj.pptxData Modernization_Harinath Susairaj.pptx
Data Modernization_Harinath Susairaj.pptxArunPandiyan890855
 
How Yellowbrick Data Integrates to Existing Environments Webcast
How Yellowbrick Data Integrates to Existing Environments WebcastHow Yellowbrick Data Integrates to Existing Environments Webcast
How Yellowbrick Data Integrates to Existing Environments WebcastYellowbrick Data
 
How a Semantic Layer Makes Data Mesh Work at Scale
How a Semantic Layer Makes  Data Mesh Work at ScaleHow a Semantic Layer Makes  Data Mesh Work at Scale
How a Semantic Layer Makes Data Mesh Work at ScaleDATAVERSITY
 
Sql Server 2012 Datasheet
Sql Server 2012 DatasheetSql Server 2012 Datasheet
Sql Server 2012 DatasheetMILL5
 
Webinar | Introducing DataStax Enterprise 4.6
Webinar | Introducing DataStax Enterprise 4.6Webinar | Introducing DataStax Enterprise 4.6
Webinar | Introducing DataStax Enterprise 4.6DataStax
 
Analytics at the Speed of Thought: Actian Express Overview
Analytics at the Speed of Thought: Actian Express Overview Analytics at the Speed of Thought: Actian Express Overview
Analytics at the Speed of Thought: Actian Express Overview Actian Corporation
 
Ibm pure data system for analytics n3001
Ibm pure data system for analytics n3001Ibm pure data system for analytics n3001
Ibm pure data system for analytics n3001Abhishek Satyam
 
State of the Union: Database & Analytics
State of the Union: Database & AnalyticsState of the Union: Database & Analytics
State of the Union: Database & AnalyticsAmazon Web Services
 
Co 4, session 2, aws analytics services
Co 4, session 2, aws analytics servicesCo 4, session 2, aws analytics services
Co 4, session 2, aws analytics servicesm vaishnavi
 
Alteryx Tutorial Step by Step Guide for Beginners
Alteryx Tutorial Step by Step Guide for BeginnersAlteryx Tutorial Step by Step Guide for Beginners
Alteryx Tutorial Step by Step Guide for BeginnersVishnuGone
 
AWS reinvent 2019 recap - Riyadh - Database and Analytics - Assif Abbasi
AWS reinvent 2019 recap - Riyadh - Database and Analytics - Assif AbbasiAWS reinvent 2019 recap - Riyadh - Database and Analytics - Assif Abbasi
AWS reinvent 2019 recap - Riyadh - Database and Analytics - Assif AbbasiAWS Riyadh User Group
 
SQL in Hadoop To Boldly Go Where no Data Warehouse Has Gone Before
SQL in Hadoop  To Boldly Go Where no Data Warehouse Has Gone BeforeSQL in Hadoop  To Boldly Go Where no Data Warehouse Has Gone Before
SQL in Hadoop To Boldly Go Where no Data Warehouse Has Gone BeforeEdgar Alejandro Villegas
 
Data Mesh using Microsoft Fabric
Data Mesh using Microsoft FabricData Mesh using Microsoft Fabric
Data Mesh using Microsoft FabricNathan Bijnens
 
Actian Analytics Platform - Hadoop SQL Edition
Actian Analytics Platform - Hadoop SQL EditionActian Analytics Platform - Hadoop SQL Edition
Actian Analytics Platform - Hadoop SQL EditionAlessandro Salvatico
 
Chip ICT | Hgst storage brochure
Chip ICT | Hgst storage brochureChip ICT | Hgst storage brochure
Chip ICT | Hgst storage brochureMarco van der Hart
 
DS_2016_StreamAnalytix_real_time_streaming_analytics_platform
DS_2016_StreamAnalytix_real_time_streaming_analytics_platformDS_2016_StreamAnalytix_real_time_streaming_analytics_platform
DS_2016_StreamAnalytix_real_time_streaming_analytics_platformAditya Singh
 
Qubole on AWS - White paper
Qubole on AWS - White paper Qubole on AWS - White paper
Qubole on AWS - White paper Vasu S
 
FSI201 FINRA’s Managed Data Lake – Next Gen Analytics in the Cloud
FSI201 FINRA’s Managed Data Lake – Next Gen Analytics in the CloudFSI201 FINRA’s Managed Data Lake – Next Gen Analytics in the Cloud
FSI201 FINRA’s Managed Data Lake – Next Gen Analytics in the CloudAmazon Web Services
 
Attributes of a Modern Data Warehouse - Gartner Catalyst
Attributes of a Modern Data Warehouse - Gartner CatalystAttributes of a Modern Data Warehouse - Gartner Catalyst
Attributes of a Modern Data Warehouse - Gartner CatalystJack Mardack
 

Similar to High-Performance Analytics for Big Data with Actian Matrix (20)

Data Modernization_Harinath Susairaj.pptx
Data Modernization_Harinath Susairaj.pptxData Modernization_Harinath Susairaj.pptx
Data Modernization_Harinath Susairaj.pptx
 
How Yellowbrick Data Integrates to Existing Environments Webcast
How Yellowbrick Data Integrates to Existing Environments WebcastHow Yellowbrick Data Integrates to Existing Environments Webcast
How Yellowbrick Data Integrates to Existing Environments Webcast
 
How a Semantic Layer Makes Data Mesh Work at Scale
How a Semantic Layer Makes  Data Mesh Work at ScaleHow a Semantic Layer Makes  Data Mesh Work at Scale
How a Semantic Layer Makes Data Mesh Work at Scale
 
Sql Server 2012 Datasheet
Sql Server 2012 DatasheetSql Server 2012 Datasheet
Sql Server 2012 Datasheet
 
Webinar | Introducing DataStax Enterprise 4.6
Webinar | Introducing DataStax Enterprise 4.6Webinar | Introducing DataStax Enterprise 4.6
Webinar | Introducing DataStax Enterprise 4.6
 
Analytics at the Speed of Thought: Actian Express Overview
Analytics at the Speed of Thought: Actian Express Overview Analytics at the Speed of Thought: Actian Express Overview
Analytics at the Speed of Thought: Actian Express Overview
 
4AA6-4492ENW
4AA6-4492ENW4AA6-4492ENW
4AA6-4492ENW
 
Ibm pure data system for analytics n3001
Ibm pure data system for analytics n3001Ibm pure data system for analytics n3001
Ibm pure data system for analytics n3001
 
State of the Union: Database & Analytics
State of the Union: Database & AnalyticsState of the Union: Database & Analytics
State of the Union: Database & Analytics
 
Co 4, session 2, aws analytics services
Co 4, session 2, aws analytics servicesCo 4, session 2, aws analytics services
Co 4, session 2, aws analytics services
 
Alteryx Tutorial Step by Step Guide for Beginners
Alteryx Tutorial Step by Step Guide for BeginnersAlteryx Tutorial Step by Step Guide for Beginners
Alteryx Tutorial Step by Step Guide for Beginners
 
AWS reinvent 2019 recap - Riyadh - Database and Analytics - Assif Abbasi
AWS reinvent 2019 recap - Riyadh - Database and Analytics - Assif AbbasiAWS reinvent 2019 recap - Riyadh - Database and Analytics - Assif Abbasi
AWS reinvent 2019 recap - Riyadh - Database and Analytics - Assif Abbasi
 
SQL in Hadoop To Boldly Go Where no Data Warehouse Has Gone Before
SQL in Hadoop  To Boldly Go Where no Data Warehouse Has Gone BeforeSQL in Hadoop  To Boldly Go Where no Data Warehouse Has Gone Before
SQL in Hadoop To Boldly Go Where no Data Warehouse Has Gone Before
 
Data Mesh using Microsoft Fabric
Data Mesh using Microsoft FabricData Mesh using Microsoft Fabric
Data Mesh using Microsoft Fabric
 
Actian Analytics Platform - Hadoop SQL Edition
Actian Analytics Platform - Hadoop SQL EditionActian Analytics Platform - Hadoop SQL Edition
Actian Analytics Platform - Hadoop SQL Edition
 
Chip ICT | Hgst storage brochure
Chip ICT | Hgst storage brochureChip ICT | Hgst storage brochure
Chip ICT | Hgst storage brochure
 
DS_2016_StreamAnalytix_real_time_streaming_analytics_platform
DS_2016_StreamAnalytix_real_time_streaming_analytics_platformDS_2016_StreamAnalytix_real_time_streaming_analytics_platform
DS_2016_StreamAnalytix_real_time_streaming_analytics_platform
 
Qubole on AWS - White paper
Qubole on AWS - White paper Qubole on AWS - White paper
Qubole on AWS - White paper
 
FSI201 FINRA’s Managed Data Lake – Next Gen Analytics in the Cloud
FSI201 FINRA’s Managed Data Lake – Next Gen Analytics in the CloudFSI201 FINRA’s Managed Data Lake – Next Gen Analytics in the Cloud
FSI201 FINRA’s Managed Data Lake – Next Gen Analytics in the Cloud
 
Attributes of a Modern Data Warehouse - Gartner Catalyst
Attributes of a Modern Data Warehouse - Gartner CatalystAttributes of a Modern Data Warehouse - Gartner Catalyst
Attributes of a Modern Data Warehouse - Gartner Catalyst
 

More from Edgar Alejandro Villegas

What's New in Predictive Analytics IBM SPSS - Apr 2016
What's New in Predictive Analytics IBM SPSS - Apr 2016What's New in Predictive Analytics IBM SPSS - Apr 2016
What's New in Predictive Analytics IBM SPSS - Apr 2016Edgar Alejandro Villegas
 
The Four Pillars of Analytics Technology Whitepaper
The Four Pillars of Analytics Technology WhitepaperThe Four Pillars of Analytics Technology Whitepaper
The Four Pillars of Analytics Technology WhitepaperEdgar Alejandro Villegas
 
SQL – The Natural Language for Analysis - Oracle - Whitepaper - 2431343
SQL – The Natural Language for Analysis - Oracle - Whitepaper - 2431343SQL – The Natural Language for Analysis - Oracle - Whitepaper - 2431343
SQL – The Natural Language for Analysis - Oracle - Whitepaper - 2431343Edgar Alejandro Villegas
 
Best Practices for Oracle Exadata and the Oracle Optimizer
Best Practices for Oracle Exadata and the Oracle OptimizerBest Practices for Oracle Exadata and the Oracle Optimizer
Best Practices for Oracle Exadata and the Oracle OptimizerEdgar Alejandro Villegas
 
Best Practices – Extreme Performance with Data Warehousing on Oracle Databa...
Best Practices –  Extreme Performance with Data Warehousing  on Oracle Databa...Best Practices –  Extreme Performance with Data Warehousing  on Oracle Databa...
Best Practices – Extreme Performance with Data Warehousing on Oracle Databa...Edgar Alejandro Villegas
 
Big Data and Enterprise Data - Oracle -1663869
Big Data and Enterprise Data - Oracle -1663869Big Data and Enterprise Data - Oracle -1663869
Big Data and Enterprise Data - Oracle -1663869Edgar Alejandro Villegas
 
Fast and Easy Analytics: - Tableau - Data Base Trends - Dbt06122013slides
Fast and Easy Analytics: - Tableau - Data Base Trends - Dbt06122013slidesFast and Easy Analytics: - Tableau - Data Base Trends - Dbt06122013slides
Fast and Easy Analytics: - Tableau - Data Base Trends - Dbt06122013slidesEdgar Alejandro Villegas
 
BITGLASS - DATA BREACH DISCOVERY DATASHEET
BITGLASS - DATA BREACH DISCOVERY DATASHEETBITGLASS - DATA BREACH DISCOVERY DATASHEET
BITGLASS - DATA BREACH DISCOVERY DATASHEETEdgar Alejandro Villegas
 
Four Pillars of Business Analytics - e-book - Actuate
Four Pillars of Business Analytics - e-book - ActuateFour Pillars of Business Analytics - e-book - Actuate
Four Pillars of Business Analytics - e-book - ActuateEdgar Alejandro Villegas
 
Analytics Trends 20145 - Deloitte - us-da-analytics-analytics-trends-2015
Analytics Trends 20145 -  Deloitte - us-da-analytics-analytics-trends-2015Analytics Trends 20145 -  Deloitte - us-da-analytics-analytics-trends-2015
Analytics Trends 20145 - Deloitte - us-da-analytics-analytics-trends-2015Edgar Alejandro Villegas
 

More from Edgar Alejandro Villegas (20)

What's New in Predictive Analytics IBM SPSS - Apr 2016
What's New in Predictive Analytics IBM SPSS - Apr 2016What's New in Predictive Analytics IBM SPSS - Apr 2016
What's New in Predictive Analytics IBM SPSS - Apr 2016
 
Oracle big data discovery 994294
Oracle big data discovery   994294Oracle big data discovery   994294
Oracle big data discovery 994294
 
Actian Ingres10.2 Datasheet
Actian Ingres10.2 DatasheetActian Ingres10.2 Datasheet
Actian Ingres10.2 Datasheet
 
Actian Matrix Whitepaper
 Actian Matrix Whitepaper Actian Matrix Whitepaper
Actian Matrix Whitepaper
 
Actian Vector Whitepaper
 Actian Vector Whitepaper Actian Vector Whitepaper
Actian Vector Whitepaper
 
Actian DataFlow Whitepaper
Actian DataFlow WhitepaperActian DataFlow Whitepaper
Actian DataFlow Whitepaper
 
The Four Pillars of Analytics Technology Whitepaper
The Four Pillars of Analytics Technology WhitepaperThe Four Pillars of Analytics Technology Whitepaper
The Four Pillars of Analytics Technology Whitepaper
 
Realtime analytics with_hadoop
Realtime analytics with_hadoopRealtime analytics with_hadoop
Realtime analytics with_hadoop
 
SQL – The Natural Language for Analysis - Oracle - Whitepaper - 2431343
SQL – The Natural Language for Analysis - Oracle - Whitepaper - 2431343SQL – The Natural Language for Analysis - Oracle - Whitepaper - 2431343
SQL – The Natural Language for Analysis - Oracle - Whitepaper - 2431343
 
Hadoop and Your Enterprise Data Warehouse
Hadoop and Your Enterprise Data WarehouseHadoop and Your Enterprise Data Warehouse
Hadoop and Your Enterprise Data Warehouse
 
Big Data SurVey - IOUG - 2013 - 594292
Big Data SurVey - IOUG - 2013 - 594292Big Data SurVey - IOUG - 2013 - 594292
Big Data SurVey - IOUG - 2013 - 594292
 
Best Practices for Oracle Exadata and the Oracle Optimizer
Best Practices for Oracle Exadata and the Oracle OptimizerBest Practices for Oracle Exadata and the Oracle Optimizer
Best Practices for Oracle Exadata and the Oracle Optimizer
 
Best Practices – Extreme Performance with Data Warehousing on Oracle Databa...
Best Practices –  Extreme Performance with Data Warehousing  on Oracle Databa...Best Practices –  Extreme Performance with Data Warehousing  on Oracle Databa...
Best Practices – Extreme Performance with Data Warehousing on Oracle Databa...
 
Big Data and Enterprise Data - Oracle -1663869
Big Data and Enterprise Data - Oracle -1663869Big Data and Enterprise Data - Oracle -1663869
Big Data and Enterprise Data - Oracle -1663869
 
Fast and Easy Analytics: - Tableau - Data Base Trends - Dbt06122013slides
Fast and Easy Analytics: - Tableau - Data Base Trends - Dbt06122013slidesFast and Easy Analytics: - Tableau - Data Base Trends - Dbt06122013slides
Fast and Easy Analytics: - Tableau - Data Base Trends - Dbt06122013slides
 
BITGLASS - DATA BREACH DISCOVERY DATASHEET
BITGLASS - DATA BREACH DISCOVERY DATASHEETBITGLASS - DATA BREACH DISCOVERY DATASHEET
BITGLASS - DATA BREACH DISCOVERY DATASHEET
 
Four Pillars of Business Analytics - e-book - Actuate
Four Pillars of Business Analytics - e-book - ActuateFour Pillars of Business Analytics - e-book - Actuate
Four Pillars of Business Analytics - e-book - Actuate
 
Sas hpa-va-bda-exadata-2389280
Sas hpa-va-bda-exadata-2389280Sas hpa-va-bda-exadata-2389280
Sas hpa-va-bda-exadata-2389280
 
Splice machine-bloor-webinar-data-lakes
Splice machine-bloor-webinar-data-lakesSplice machine-bloor-webinar-data-lakes
Splice machine-bloor-webinar-data-lakes
 
Analytics Trends 20145 - Deloitte - us-da-analytics-analytics-trends-2015
Analytics Trends 20145 -  Deloitte - us-da-analytics-analytics-trends-2015Analytics Trends 20145 -  Deloitte - us-da-analytics-analytics-trends-2015
Analytics Trends 20145 - Deloitte - us-da-analytics-analytics-trends-2015
 

Recently uploaded

Call me @ 9892124323 Cheap Rate Call Girls in Vashi with Real Photo 100% Secure
Call me @ 9892124323  Cheap Rate Call Girls in Vashi with Real Photo 100% SecureCall me @ 9892124323  Cheap Rate Call Girls in Vashi with Real Photo 100% Secure
Call me @ 9892124323 Cheap Rate Call Girls in Vashi with Real Photo 100% SecurePooja Nehwal
 
Zuja dropshipping via API with DroFx.pptx
Zuja dropshipping via API with DroFx.pptxZuja dropshipping via API with DroFx.pptx
Zuja dropshipping via API with DroFx.pptxolyaivanovalion
 
Delhi Call Girls CP 9711199171 ☎✔👌✔ Whatsapp Hard And Sexy Vip Call
Delhi Call Girls CP 9711199171 ☎✔👌✔ Whatsapp Hard And Sexy Vip CallDelhi Call Girls CP 9711199171 ☎✔👌✔ Whatsapp Hard And Sexy Vip Call
Delhi Call Girls CP 9711199171 ☎✔👌✔ Whatsapp Hard And Sexy Vip Callshivangimorya083
 
Schema on read is obsolete. Welcome metaprogramming..pdf
Schema on read is obsolete. Welcome metaprogramming..pdfSchema on read is obsolete. Welcome metaprogramming..pdf
Schema on read is obsolete. Welcome metaprogramming..pdfLars Albertsson
 
100-Concepts-of-AI by Anupama Kate .pptx
100-Concepts-of-AI by Anupama Kate .pptx100-Concepts-of-AI by Anupama Kate .pptx
100-Concepts-of-AI by Anupama Kate .pptxAnupama Kate
 
Al Barsha Escorts $#$ O565212860 $#$ Escort Service In Al Barsha
Al Barsha Escorts $#$ O565212860 $#$ Escort Service In Al BarshaAl Barsha Escorts $#$ O565212860 $#$ Escort Service In Al Barsha
Al Barsha Escorts $#$ O565212860 $#$ Escort Service In Al BarshaAroojKhan71
 
Midocean dropshipping via API with DroFx
Midocean dropshipping via API with DroFxMidocean dropshipping via API with DroFx
Midocean dropshipping via API with DroFxolyaivanovalion
 
Digital Advertising Lecture for Advanced Digital & Social Media Strategy at U...
Digital Advertising Lecture for Advanced Digital & Social Media Strategy at U...Digital Advertising Lecture for Advanced Digital & Social Media Strategy at U...
Digital Advertising Lecture for Advanced Digital & Social Media Strategy at U...Valters Lauzums
 
Data-Analysis for Chicago Crime Data 2023
Data-Analysis for Chicago Crime Data  2023Data-Analysis for Chicago Crime Data  2023
Data-Analysis for Chicago Crime Data 2023ymrp368
 
Best VIP Call Girls Noida Sector 22 Call Me: 8448380779
Best VIP Call Girls Noida Sector 22 Call Me: 8448380779Best VIP Call Girls Noida Sector 22 Call Me: 8448380779
Best VIP Call Girls Noida Sector 22 Call Me: 8448380779Delhi Call girls
 
Cheap Rate Call girls Sarita Vihar Delhi 9205541914 shot 1500 night
Cheap Rate Call girls Sarita Vihar Delhi 9205541914 shot 1500 nightCheap Rate Call girls Sarita Vihar Delhi 9205541914 shot 1500 night
Cheap Rate Call girls Sarita Vihar Delhi 9205541914 shot 1500 nightDelhi Call girls
 
Vip Model Call Girls (Delhi) Karol Bagh 9711199171✔️Body to body massage wit...
Vip Model  Call Girls (Delhi) Karol Bagh 9711199171✔️Body to body massage wit...Vip Model  Call Girls (Delhi) Karol Bagh 9711199171✔️Body to body massage wit...
Vip Model Call Girls (Delhi) Karol Bagh 9711199171✔️Body to body massage wit...shivangimorya083
 
CebaBaby dropshipping via API with DroFX.pptx
CebaBaby dropshipping via API with DroFX.pptxCebaBaby dropshipping via API with DroFX.pptx
CebaBaby dropshipping via API with DroFX.pptxolyaivanovalion
 
Introduction-to-Machine-Learning (1).pptx
Introduction-to-Machine-Learning (1).pptxIntroduction-to-Machine-Learning (1).pptx
Introduction-to-Machine-Learning (1).pptxfirstjob4
 
FESE Capital Markets Fact Sheet 2024 Q1.pdf
FESE Capital Markets Fact Sheet 2024 Q1.pdfFESE Capital Markets Fact Sheet 2024 Q1.pdf
FESE Capital Markets Fact Sheet 2024 Q1.pdfMarinCaroMartnezBerg
 
Ravak dropshipping via API with DroFx.pptx
Ravak dropshipping via API with DroFx.pptxRavak dropshipping via API with DroFx.pptx
Ravak dropshipping via API with DroFx.pptxolyaivanovalion
 
BDSM⚡Call Girls in Mandawali Delhi >༒8448380779 Escort Service
BDSM⚡Call Girls in Mandawali Delhi >༒8448380779 Escort ServiceBDSM⚡Call Girls in Mandawali Delhi >༒8448380779 Escort Service
BDSM⚡Call Girls in Mandawali Delhi >༒8448380779 Escort ServiceDelhi Call girls
 

Recently uploaded (20)

Call me @ 9892124323 Cheap Rate Call Girls in Vashi with Real Photo 100% Secure
Call me @ 9892124323  Cheap Rate Call Girls in Vashi with Real Photo 100% SecureCall me @ 9892124323  Cheap Rate Call Girls in Vashi with Real Photo 100% Secure
Call me @ 9892124323 Cheap Rate Call Girls in Vashi with Real Photo 100% Secure
 
Call Girls In Shalimar Bagh ( Delhi) 9953330565 Escorts Service
Call Girls In Shalimar Bagh ( Delhi) 9953330565 Escorts ServiceCall Girls In Shalimar Bagh ( Delhi) 9953330565 Escorts Service
Call Girls In Shalimar Bagh ( Delhi) 9953330565 Escorts Service
 
Zuja dropshipping via API with DroFx.pptx
Zuja dropshipping via API with DroFx.pptxZuja dropshipping via API with DroFx.pptx
Zuja dropshipping via API with DroFx.pptx
 
Delhi Call Girls CP 9711199171 ☎✔👌✔ Whatsapp Hard And Sexy Vip Call
Delhi Call Girls CP 9711199171 ☎✔👌✔ Whatsapp Hard And Sexy Vip CallDelhi Call Girls CP 9711199171 ☎✔👌✔ Whatsapp Hard And Sexy Vip Call
Delhi Call Girls CP 9711199171 ☎✔👌✔ Whatsapp Hard And Sexy Vip Call
 
Schema on read is obsolete. Welcome metaprogramming..pdf
Schema on read is obsolete. Welcome metaprogramming..pdfSchema on read is obsolete. Welcome metaprogramming..pdf
Schema on read is obsolete. Welcome metaprogramming..pdf
 
100-Concepts-of-AI by Anupama Kate .pptx
100-Concepts-of-AI by Anupama Kate .pptx100-Concepts-of-AI by Anupama Kate .pptx
100-Concepts-of-AI by Anupama Kate .pptx
 
Al Barsha Escorts $#$ O565212860 $#$ Escort Service In Al Barsha
Al Barsha Escorts $#$ O565212860 $#$ Escort Service In Al BarshaAl Barsha Escorts $#$ O565212860 $#$ Escort Service In Al Barsha
Al Barsha Escorts $#$ O565212860 $#$ Escort Service In Al Barsha
 
Midocean dropshipping via API with DroFx
Midocean dropshipping via API with DroFxMidocean dropshipping via API with DroFx
Midocean dropshipping via API with DroFx
 
Digital Advertising Lecture for Advanced Digital & Social Media Strategy at U...
Digital Advertising Lecture for Advanced Digital & Social Media Strategy at U...Digital Advertising Lecture for Advanced Digital & Social Media Strategy at U...
Digital Advertising Lecture for Advanced Digital & Social Media Strategy at U...
 
Data-Analysis for Chicago Crime Data 2023
Data-Analysis for Chicago Crime Data  2023Data-Analysis for Chicago Crime Data  2023
Data-Analysis for Chicago Crime Data 2023
 
Best VIP Call Girls Noida Sector 22 Call Me: 8448380779
Best VIP Call Girls Noida Sector 22 Call Me: 8448380779Best VIP Call Girls Noida Sector 22 Call Me: 8448380779
Best VIP Call Girls Noida Sector 22 Call Me: 8448380779
 
Cheap Rate Call girls Sarita Vihar Delhi 9205541914 shot 1500 night
Cheap Rate Call girls Sarita Vihar Delhi 9205541914 shot 1500 nightCheap Rate Call girls Sarita Vihar Delhi 9205541914 shot 1500 night
Cheap Rate Call girls Sarita Vihar Delhi 9205541914 shot 1500 night
 
CHEAP Call Girls in Saket (-DELHI )🔝 9953056974🔝(=)/CALL GIRLS SERVICE
CHEAP Call Girls in Saket (-DELHI )🔝 9953056974🔝(=)/CALL GIRLS SERVICECHEAP Call Girls in Saket (-DELHI )🔝 9953056974🔝(=)/CALL GIRLS SERVICE
CHEAP Call Girls in Saket (-DELHI )🔝 9953056974🔝(=)/CALL GIRLS SERVICE
 
Vip Model Call Girls (Delhi) Karol Bagh 9711199171✔️Body to body massage wit...
Vip Model  Call Girls (Delhi) Karol Bagh 9711199171✔️Body to body massage wit...Vip Model  Call Girls (Delhi) Karol Bagh 9711199171✔️Body to body massage wit...
Vip Model Call Girls (Delhi) Karol Bagh 9711199171✔️Body to body massage wit...
 
Sampling (random) method and Non random.ppt
Sampling (random) method and Non random.pptSampling (random) method and Non random.ppt
Sampling (random) method and Non random.ppt
 
CebaBaby dropshipping via API with DroFX.pptx
CebaBaby dropshipping via API with DroFX.pptxCebaBaby dropshipping via API with DroFX.pptx
CebaBaby dropshipping via API with DroFX.pptx
 
Introduction-to-Machine-Learning (1).pptx
Introduction-to-Machine-Learning (1).pptxIntroduction-to-Machine-Learning (1).pptx
Introduction-to-Machine-Learning (1).pptx
 
FESE Capital Markets Fact Sheet 2024 Q1.pdf
FESE Capital Markets Fact Sheet 2024 Q1.pdfFESE Capital Markets Fact Sheet 2024 Q1.pdf
FESE Capital Markets Fact Sheet 2024 Q1.pdf
 
Ravak dropshipping via API with DroFx.pptx
Ravak dropshipping via API with DroFx.pptxRavak dropshipping via API with DroFx.pptx
Ravak dropshipping via API with DroFx.pptx
 
BDSM⚡Call Girls in Mandawali Delhi >༒8448380779 Escort Service
BDSM⚡Call Girls in Mandawali Delhi >༒8448380779 Escort ServiceBDSM⚡Call Girls in Mandawali Delhi >༒8448380779 Escort Service
BDSM⚡Call Girls in Mandawali Delhi >༒8448380779 Escort Service
 

High-Performance Analytics for Big Data with Actian Matrix

  • 1. Key Benefits Fast Analytics. Achieve up to 100x performance improvements. Massive Scalability. Linear scaling lets you analyze any amount of data or level of detail while maintaining quality and performance, on-premises or in cloud or hybrid environments. Business Agility. Customize, iterate and launch analytic applications faster. Reduce friction and react in real-time to dynamic market conditions, increasing analytic sophistication, changing user needs, and evolving data analytics infrastructure. Extreme Value. Improve price-performance up to 200x compared with traditional systems or analytic appliances. High-Performance Analytics for the Enterprise Tackle big data 2.0 initiatives with Actian Matrix. Its massively parallel architecture, columnar database structure and in-database analytics deliver unrivaled performance and scalability. Query optimization and extensibility frameworks and a library of advanced analytic functions help you transform big data into actionable insights and business value. Massively Parallel Processing Architecture Actian Matrix is geared to the demands of massive data, many users and significant analytic complexity. • Columnar Database Structure: Query all of your data and get precisely the data you need, without the burden of handling extraneous data returned by traditional row-oriented databases. • Adaptive Compression: Maximize query performance while conserving storage resources thanks to data compression that adapts to match data types. • Dynamic Compilation: Queries compiled at execution deliver performance up to 100 times faster for analytic joins and up to 50 times faster for more complex queries and aggregations. • High-Speed Network Interconnect: Communication between nodes within an Actian Matrix cluster takes place using a custom UDP-based protocol, supporting near-linear scalability. • In-Memory Analytics: High-performance and parallelism support a 10-100x improvement in analytic performance. • Adaptive Workload Management: Analytic workloads of groups and applications are intelligently balanced based on defined priorities and available resources so you can deliver timely insights to all users. Resource groups can be defined by user, department, application, or query type; and each group can be assigned a unique priority weighting. More efficient workload management and more productive users lead to more analytic value. Unconstrained Analytics Analyze efficiently. The Actian Matrix Optimizer Framework adjusts concurrent queries, handles more than 1,000 joins, and dynamically shares computing resources to run analytics across an unlimited number of nodes. Complex analytics are converted into simpler logical components. Each query travels the optimal path given the traffic conditions at run time. Actian makes it easy to create and add your own optimizations for: SQL, Planning, Execution, Communications and I/O. Extreme SQL Rewrite Optimization Rewrites logical query expressions to alternative yet semantically equivalent forms. Applies fundamental non-rule-based as well as iterative rule-based transformations that are re-expressed as SQL text and then re-parsed. Predicate optimizations improve when and how data is filtered during execution of a query plan. Actian Analytics Database - Matrix Data Sheet
  • 2. Extreme Join Optimization After an incoming SQL query has been optimized, our patented Planning Optimizer quickly selects the best planning scenario, reducing options from billions, at runtime. Plan queries with many tables by partially ordering them prior to exhaustive physical planning. Integrated Planning and Execution Optimizers improve table grouping for exceptional query performance. Extreme Execution Optimization The Execution Optimizer creates a query plan and executes the query, ensuring efficient routing of data across the cluster. A planning execution optimizer improves query planning and execution performance. The result is superior join order, sort order exploitation and data distribution. Analyze any data, any way. The Actian Matrix Extensibility Framework opens the core database to diverse data sources and analytics through our On-Demand Integration modules. A library of 700+ advanced analytic functions can be accessed from Actian Matrix to expedite analytic processing. Added functions can easily be created and made available for reuse by any user or visualization tool. Analyze on the fly. Bring in data from a data warehouse and leverage Hadoop analytics before or in the midst of a query. It’s the perfect solution for offloading analytics from a data warehouse or bringing in internet and already analyzed social media data. Easy Integration and Deployment Use the Freshest Data from Any Source: Massively parallel data loads and schema-neutrality ensure applications and users of fast access to the most current data available without ongoing database tuning. Use Any Dashboard, BI and DI Tools: Actian Matrix works seamlessly with Tableau, MicroStrategy, IBM, Cognos and SAP Business Objects, as well as Informatica and other data integration platforms. Deploy with Maximum Flexibility: Deploy Actian Matrix on-premises, on a public cloud such as Amazon EC2 or Rackspace, or on the MicroStrategy Cloud. Choose the Best Servers and Storage: Actian Matrix supports with data center standards for servers and storage. Take advantage of hardware innovations now, not 12-18 months from now when they become available in an analytic appliance. DATA Accelerate BI Accelerate Analytics Traditional Enterprise Social Internet of Things SaaS Delight Customers Improve Competitive Edge Reduce Risk and Cost Innovate NoSQL Actian Analytics Accelerators Actian Analytics Platform™ Accelerate Hadoop VALUE www.actian.com 500 Arguello Street, Ste. 200, Redwood City, CA 94063 +1.888.446.4737 [Toll Free] | +1.650.587.5500 [Tel] © 2014 Actian Corporation. Actian, Big Data for the Rest of Us, Accelerating Big Data 2.0, and Actian Analytics Platform are trademarks of Actian Corporation and its subsidiaries. All other trademarks, trade names, service marks, and logos referenced herein belong to their respective companies. (DS06-0514)