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Aster
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Review

Aster

Overview
Synopsis

Aster is a revolutionary technology which promises to do big data analysis in lighting fast speeds with minimum resource outlays. This highly charged suite for analysis is the best choice for visually stunning and swift representations for SQL, map reduce as well as in detail graphical representations.

Category

Database

Sub Category

Graph Database

License

Proprietary Software

Free Trial

Available

Users Size

Small (<50 employees), Medium (50 to 1000 employees), Enterprise (>1001 employees)

PAT Rating™ ( Beta)
Editor Rating
Aggregated User Rating
Rate Here
Ease of use
7.6
8.8
Features & Functionality
7.6
9.4
Advanced Features
7.6
4.4
Integration
7.6
0.0
Performance
7.6
0.0
Training
0.0
Customer Support
7.6
0.0
Implementation
0.0
Renew & Recommend
0.0
Bottom Line

Dynamic mix workload is another important feature of the Aster database which lets you maintain scalable performance in a heavy workload and a crowd of concurrent users. By using an analytic engine such as SQL during query runtime, the data from the hadoop can be used in the aster database where a large array of aster functions can be used to carry out complex data analysis and that too in bulk.

7.6
Editor Rating
2.5
Aggregated User Rating
3 ratings
You have rated this

Aster is a revolutionary technology which promises to do big data analysis in lighting fast speeds with minimum resource outlays. This highly charged suite for analysis is the best choice for visually stunning and swift representations for SQL, map reduce as well as in detail graphical representations. Its massive parallel design helps to boost performance by carrying out loads, queries, backups, installs etc. in parallel for rapid insight discoveries. Another feature of this award winning analytical suite is that you can couple up multiple analytic engines of your own choice ( SQL-MR, SQL-GR, R and SQL) based on your own preferences. As more powerful analytic engines are geared up, it makes sure that the performance is not reduced in query optimization, resource planning etc.

The snap framework can be incorporated into existing IT infrastructures and this integration is very easy to do. Dynamic mix workload is another important feature of the Aster database which lets you maintain scalable performance in a heavy workload and a crowd of concurrent users. By using an analytic engine such as SQL during query runtime, the data from the hadoop can be used in the aster database where a large array of aster functions can be used to carry out complex data analysis and that too in bulk.

The aster management console has been designed to maximize user convenience by making it easy to look over and manage all data and analytic processes. A feature such as a single system view provides complete transparency to the administrators even when the system scales to several hundred servers because it shows all those servers as a single entity. The workload in management does not depend upon the number of servers at work and it does not increase with increase in number of servers. Aster’s database online scaling feature provides the ease to the user to add or remove servers from a cluster with one click.

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Ease of use
Features & Functionality
Advanced Features
Integration
Performance
Training
Customer Support
Implementation
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