Introduction to Infobright Analytics Database
우연히 알게된 Analytics Database Infobright 참신한 알고리즘으로 대단한 속도를 보여주는 것을 확인하였다.
이 오픈소스 DB는 참으로 참신한 아이디어인듯 하다. 흥미롭다. 개인적으로 대용량에 관심이 많은 나로써는 재미있는 오픈소스를 알게 되어 기쁘다.
물론 내 개인적인 테스트 DB로 테스트 결과이지만....자료는 정리되면 추후 테스트 결과를 올리겠다.
테스트 중 생각을 정리해보면, 대용량 시스템에 적합하지 않을까 생각해본다.
다양한 산업분야에 사용 될 수 있다는 생각에 테스트도 재미있다.
Infobright 4.0 – New Capabilities
• DomainExpert technology: By adding intelligence about a particular data domain—such as web, financial services or telecom—the Infobright database is automatically optimized for analytic performance. In release 4.0, online data types such as email addresses, URLs and IP addresses are included, and users can also easily add their own domain intelligence to meet their unique needs.
• Rough Query: Rough Query provides near-instantaneous results for users who need to drill down into very large volumes of data. Rather than execute a long-running query to find a specific answer, Rough Query enables a user to narrow down the results in an iterative manner, with sub-second response time, before the full query is run. The total query time can be reduced by 20 times using this capability.
• Distributed Load Processor (DLP): DLP delivers load speeds that scale linearly as it processes and compresses data using multiple remote servers, then transfers the compressed data to the IEE database. Load performance gains result because CPU-intensive data compression is distributed across multiple machines, and query performance is enhanced by offloading this work from the database server.
• DomainExpert technology: By adding intelligence about a particular data domain—such as web, financial services or telecom—the Infobright database is automatically optimized for analytic performance. In release 4.0, online data types such as email addresses, URLs and IP addresses are included, and users can also easily add their own domain intelligence to meet their unique needs.
• Rough Query: Rough Query provides near-instantaneous results for users who need to drill down into very large volumes of data. Rather than execute a long-running query to find a specific answer, Rough Query enables a user to narrow down the results in an iterative manner, with sub-second response time, before the full query is run. The total query time can be reduced by 20 times using this capability.
• Distributed Load Processor (DLP): DLP delivers load speeds that scale linearly as it processes and compresses data using multiple remote servers, then transfers the compressed data to the IEE database. Load performance gains result because CPU-intensive data compression is distributed across multiple machines, and query performance is enhanced by offloading this work from the database server.
• Hadoop Connector: Users looking to leverage Hadoop’s large-scale distributed batch processing benefits with Infobright’s fast ad-hoc analytic capabilities can do so easily using the Hadoop connector within the DLP. This tool provides a simple way to extract data from a Hadoop cluster and load it into IEE at very high speeds.
참고로 infobright community edition 버전으로 테스트 해볼 수 있고 enterprise도 존재한다.