BigTable

O Bigtable é um sistema de armazenamento de dados proprietário compactado, de alto desempenho construído no sistema do Google File e algumas outras tecnologias Google. Em 6 de maio de 2015, uma versão pública do Bigtable foi disponibilizada.[1][2]

O desenvolvimento do Bigtable começou em 2004[3] e agora é usado por várias aplicações do Google, como o indexamento web,[4] MapReduce, que é usado frequentemente para gerar modificar dados armazenados no Bigtable,[5] Google Maps,[6] Google Book Search, Google Earth, Blogger.com, Google Code, YouTube,[7] e Gmail.[8] As razões do Google para desenvolver seu próprio banco de dados incluem escalabilidade e melhor controle das características de desempenho.[9]

Bibliografia

Referências

  1. ↑ «Announcing Google Cloud Bigtable: The same database that powers Google Search, Gmail and Analytics is now available on Google Cloud Platform». Google Blog. 6 de maio de 2015. Consultado em 21 de setembro de 2016 
  2. ↑ «Get started with Google Cloud Datastore - a fast, powerful, NoSQL database» 
  3. ↑ Kumar, Aswini, Whitchcock, Andrew, ed., Google's Bigtable, First an overview. Bigtable has been in development since early 2004 and has been in active use for about eight months (about February 2005). .
  4. ↑ Chang et al. 2006.
  5. ↑ Chang et al. 2006, p. 3: ‘Bigtable can be used with MapReduce, a framework for running large-scale parallel computations developed at Google. We have written a set of wrappers that allow a Bigtable to be used both as an input source and as an output target for MapReduce jobs’
  6. ↑ Whitchcock, Andrew, Google's Bigtable, There are currently around 100 cells for services such as Print, Search History, Maps, and Orkut .
  7. ↑ Cordes, Kyle (12 de julho de 2007), YouTube Scalability (talk), Their new solution for thumbnails is to use Google’s Bigtable, which provides high performance for a large number of rows, fault tolerance, caching, etc. This is a nice (and rare?) example of actual synergy in an acquisition. .
  8. ↑ «How Entities and Indexes are Stored», Google App Engine, Google Code .
  9. ↑ Chang et al. 2006, Conclusion: ‘We have described Bigtable, a distributed system for storing structured data at Google... Our users like the performance and high availability provided by the Bigtable implementation, and that they can scale the capacity of their clusters by simply adding more machines to the system as their resource demands change over time... Finally, we have found that there are significant advantages to building our own storage solution at Google. We have gotten a substantial amount of flexibility from designing our own data model for Bigtable.’

Content Disclaimer

Informasi ini disarikan dari Wikipedia dan disajikan kembali untuk tujuan edukasi. Konten tersedia di bawah lisensi CC BY-SA 3.0. Kami tidak bertanggung jawab atas ketidakakuratan data yang bersumber dari kontribusi publik tersebut.

  1. The information displayed on this website is sourced in part or in whole from Wikipedia and has been adapted for the purpose of restating it. We strive to provide accurate and relevant information, however:
  2. There is no guarantee of absolute accuracy. Wikipedia is an open, collaborative project that can be edited by anyone, so information is subject to change.
  3. It is not intended to constitute professional advice. The content displayed is for informational and educational purposes only. For important decisions (e.g., medical, legal, or financial), please consult a professional.
  4. Content copyright. Wikipedia is licensed under the Creative Commons Attribution-ShareAlike License (CC BY-SA). This means that content may be reused with appropriate attribution and shared under a similar license.
  5. Responsible use. Any risk arising from the use of information from this website is entirely the responsibility of the user.