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Actian Express – Hadoop SQL Edition includes Data Science Workbench, Data Flow Engine, Analytics Database, Management Console and Preloaded Data and Tableau Workbooks.
Category
Bigdata, Bigdata Analytics, Predictive Analytics
Features
•Multi-core parallelism & MPP •Vector Processing •Exploiting CPU Chip Cache •2nd Gen Column Store •Vectorized Compression •Performance Optimized Indexes
License
Proprietary Software
Price
Free, Paid
Pricing
Subscription
Free Trial
Available
Users Size
Small (<50 employees), Medium (50 to 1000 Enterprise (>1001 employees)
Company
Actian
What is best?
•Multi-core parallelism & MPP •Vector Processing •Exploiting CPU Chip Cache •2nd Gen Column Store •Vectorized Compression •Performance Optimized Indexes
What are the benefits?
• Provides fast and high performance analytics • Provides extensibility through open source technologies • Supports the latest ANSI SQL standards • Provides extensive SQL Support • Optimizes all available resources – memory, cache, and CPU • Ability to both read and append/update data in HDFS
PAT Rating™
Editor Rating
Aggregated User Rating
Rate Here
Ease of use
7.8
8.1
Features & Functionality
7.7
7.6
Advanced Features
7.8
7.9
Integration
7.7
8.1
Performance
7.8
8.4
Customer Support
7.7
7.9
Implementation
7.9
Renew & Recommend
8.1
Bottom Line
Actian Express – Hadoop SQL Edition includes Data Science Workbench, Data Flow Engine, Analytics Database, Management Console and Preloaded Data and Tableau Workbooks.
7.8
Editor Rating
8.0
Aggregated User Rating
1 rating
You have rated this
The Actian Analytics Platform turns Hadoop into a high-performance analytics platform, enabling organizations to improve the accuracy of predictions and decision making by analyzing data from more sources without sampling. Actian Express – Hadoop SQL Edition includes Data Science Workbench, Data Flow Engine, Analytics Database, Management Console and Preloaded Data and Tableau Workbooks.
The Data Science Workbench build visual workflows to prepare, blend and analyze Hadoop data and Data Flow Engine execute analytic workflows at least 10 times faster than MapReduce – without coding. The Analytics Database run high-performance SQL queries natively in Hadoop and the Management Console easily monitor and manage your Hadoop analytics platform.
The preloaded Data and Tableau Workbooks lets to use the platform immediately upon download. Actian has taken its record-breaking vector-based columnar analytics database and extended it to run natively in the Hadoop HDFS nodes using YARN for resource management.
With Actian Express – Hadoop SQL Edition, users have unlimited access to Actian’s library of connectors and operators, and advanced data science workbench with no limit to the number of Hadoop nodes accessed.
Actian VectorH is a high-performance MPP SQL engine with vectorized query execution that runs natively in Hadoop, powering modern decision support systems and Business intelligence. It enables developers, data scientists, and business analysts to query HDFS data and extract actionable insights from large and varied data sets stored in Hadoop. It enables them to quickly identify trends, correlations, and other patterns from weblogs, click-paths, demographic, psychographic, geographic, mobile, and other kinds of data.
Company size
Medium (50 to 1000)
User Role
Super User
User Industry
Entertainment
Rating
Ease of use8.1
VectorH also supports the latest ANSI SQL standards, is fully ACID compliant, and provides native DBMS security making Hadoop analytics secure, consumable, accessible and re-usable. VectorH features an automated Hadoop cluster resource management tool as well as a web-based management console that allow you to monitor analytic and query processing. VectorH granular, multi-channel customer profile analytics lets you examine the totality of your company’s customer data so you can identify, attract, retain, and discover the best means to connect to the most profitable customers.
Features & Functionality7.6
Advanced Features7.9
Integration8.1
Performance8.4
Training 7.9
Customer Support7.9
Implementation7.9
Renew & Recommend8.1
ADDITIONAL INFORMATION VectorH multi-core parallelism feature offers maximum performance with optimizations at the chip level to ensure maximum utilization of chip cores across all cluster nodes for record-breaking analytical data processing speeds. It also features performance optimized indexes allow you to quickly identify candidate data blocks and minimize Input/output processes. VectorH also features vectorized compression which allows you to compress the data by at least a factor of 10 to reduce the amount of Hadoop storage.
Vectorized compression
Actian VectorH is a high-performance MPP SQL engine with vectorized query execution that runs natively in Hadoop, powering modern decision support systems and Business intelligence. It enables developers, data scientists, and business analysts to query HDFS data and extract actionable insights from large and varied data sets stored in Hadoop. It enables them to quickly identify trends, correlations, and other patterns from weblogs, click-paths, demographic, psychographic, geographic, mobile, and other kinds of data.
Medium (50 to 1000)
Super User
Entertainment
VectorH also supports the latest ANSI SQL standards, is fully ACID compliant, and provides native DBMS security making Hadoop analytics secure, consumable, accessible and re-usable. VectorH features an automated Hadoop cluster resource management tool as well as a web-based management console that allow you to monitor analytic and query processing. VectorH granular, multi-channel customer profile analytics lets you examine the totality of your company’s customer data so you can identify, attract, retain, and discover the best means to connect to the most profitable customers.
ADDITIONAL INFORMATION
VectorH multi-core parallelism feature offers maximum performance with optimizations at the chip level to ensure maximum utilization of chip cores across all cluster nodes for record-breaking analytical data processing speeds. It also features performance optimized indexes allow you to quickly identify candidate data blocks and minimize Input/output processes. VectorH also features vectorized compression which allows you to compress the data by at least a factor of 10 to reduce the amount of Hadoop storage.