Query, data loading speed, simplicity, reliability, and ease of use are valuable features. Quality of the customer engagement from the Infobright team is also an important factor.
Project Manager at a tech company with 51-200 employees
Big Data Chronicles: Infobright as column-based database for analytics system
Last several months I was involved into the task of design and implementation of statistics/analytics system for the game in social network. There are a lot of users at the same time. All of them produce huge amount of events. One of the standards for analytics systems is providing fast queries for the collected data. Logically, I used OLAP cubes to collect all kinds of events needed for our team to analyze. Technically, the best way in our case is using column-based storage. I use Infobright. In our case regular RDBMS (SQL) storage or document-based DB like MongoDB is not enough because of performance. They should be used rather for OLTP, but not for MGD OLAP. From other hand, such cool gun as Hadoop-based solution would be overrun. So, Infobright is exactly the case. It was one of the best decisions I made as software architect for last several months:
- As it’s pure OLAP solution, so, I’m able to implement any ETL/Storage/Query scheme;
- As Infobright is column-based storage, all my even very sofisticated queries on even huge recordsets have extremely short execution time;
- As all huge functionality like aggregation/filtering is hidden in Inforbright’s internals, I concentrate on my business task, so, able to desing/implement/add new module/scheme/query very quickly.
Disclosure: I am a real user, and this review is based on my own experience and opinions.
Dynamic and creative, leading a business consultancy practice in analytics, business Intelligence, crm and strategy. at a tech services company with 1-10 employees
It is a game changer in analytics applications.
What is most valuable?
How has it helped my organization?
It has been a major game changer in analytics applications, as the time to market is very short in the data part.
What needs improvement?
There is need for additional DDL functions.
For how long have I used the solution?
I have used this solution for the past six years.
What do I think about the stability of the solution?
We never experienced stability issues.
What do I think about the scalability of the solution?
There were no scalability issues. You need a very small footprint as well as very low HW requirements for the data size and load tasks.
How are customer service and technical support?
The technical support is excellent.
Which solution did I use previously and why did I switch?
It has been our key engine in the columnar database landscape.
How was the initial setup?
The setup process is absolutely straightforward.
What's my experience with pricing, setup cost, and licensing?
The data size per year must be planned to make the best use of it and to choose the appropriate licensing package.
Which other solutions did I evaluate?
We looked at other columnar-based databases such as Vertica Systems.
What other advice do I have?
It is very straightforward and easy to work with. It is excellent for real-time analytics, sensor data and agile data model development/implementation.
Ad-hoc analytics are extremely reliable and easy to live with.
Disclosure: My company has a business relationship with this vendor other than being a customer: We have become partners.
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Updated: November 2024
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