Cloud database

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A cloud database is a database that typically runs on a cloud computing platform and access to the database is provided as-a-service. There are two common deployment models: users can run databases on the cloud independently, using a virtual machine image, or they can purchase access to a database service, maintained by a cloud database provider. Of the databases available on the cloud, some are SQL-based and some use a NoSQL data model.

Database services take care of scalability and high availability of the database. Database services make the underlying software-stack transparent to the user.[1]

Deployment models

There are two primary methods to run a database in a cloud:

Virtual machine image
Cloud platforms allow users to purchase virtual-machine instances for a limited time, and one can run a database on such virtual machines. Users can either upload their own machine image with a database installed on it, or use ready-made machine images that already include an optimized installation of a database.
Database-as-a-service (DBaaS)
With a database as a service model, application owners do not have to install and maintain the database themselves. Instead, the database service provider takes responsibility for installing and maintaining the database, and application owners are charged according to their usage of the service. This is a type of software as a service (SaaS).

Architecture and common characteristics

  • Most database services offer web-based consoles, which the end user can use to provision and configure database instances.
  • Database services consist of a database-manager component, which controls the underlying database instances using a service API. The service API is exposed to the end user, and permits users to perform maintenance and scaling operations on their database instances.
  • Underlying software-stack stack typically includes the operating system, the database and third-party software used to manage the database. The service provider is responsible for installing, patching and updating the underlying software stack and ensuring the overall health and performance of the database.
  • Scalability features differ between vendors – some offer auto-scaling, others enable the user to scale up using an API, but do not scale automatically.
  • There is typically a commitment for a certain level of high availability (e.g. 99.9% or 99.99%). This is achieved by replicating data and failing instances over to other database instances.

Data model

The design and development of typical systems utilize data management and relational databases as their key building blocks. Advanced queries expressed in SQL work well with the strict relationships that are imposed on information by relational databases. However, relational database technology was not initially designed or developed for use over distributed systems. This issue has been addressed with the addition of clustering enhancements to the relational databases, although some basic tasks require complex and expensive protocols, such as with data synchronization.[2]

Modern relational databases have shown poor performance on data-intensive systems, therefore, the idea of NoSQL has been utilized within database management systems for cloud based systems.[3] Within NoSQL implemented storage, there are no requirements for fixed table schemas, and the use of join operations is avoided. "The NoSQL databases have proven to provide efficient horizontal scalability, good performance, and ease of assembly into cloud applications."[4] Data models relying on simplified relay algorithms have also been employed in data-intensive cloud mapping applications unique to virtual frameworks.[5]

It is also important to differentiate between cloud databases which are relational as opposed to non-relational or NoSQL:[6]

SQL databases
are one type of database which can run in the cloud, either in a virtual machine or as a service, depending on the vendor. While SQL databases are easily vertically scalable, horizontal scalability poses a challenge, that cloud database services based on SQL have started to address.[7][need quotation to verify]
NoSQL databases
are another type of database which can run in the cloud. NoSQL databases are built to service heavy read/write loads and can scale up and down easily,[8] and therefore they are more natively suited to running in the cloud. However, most contemporary applications are built around an SQL data model, so working with NoSQL databases often requires a complete rewrite of application code.[9]
Some SQL databases have developed NoSQL capabilities including JSON, binary JSON (e.g. BSON or similar variants), and key-value store data types.
A multi-model database with relational and non-relational capabilities provides a standard SQL interface to users and applications and thus facilitates the usage of such databases for contemporary applications built around an SQL data model. Native multi-model databases support multiple data models with one core and a unified query language to access all data models.

Vendors

The following table lists notable database vendors with a cloud database offering, classified by their deployment model – machine image vs. database as a service – and data model, SQL vs. NoSQL.

Cloud database vendors by deployment and data model
Virtual Machine Deployment Database as a Service
SQL Data Model
  • Amazon Aurora, MySQL based service
  • Amazon Relational Database Service
  • Clustrix Database as a Service[22]
  • Crunchy Bridge, PostgreSQL as a Service.[23]
  • EnterpriseDB Postgres Plus Cloud Database[24]
  • Google Cloud SQL[25]
  • Heroku PostgreSQL as a Service (shared and dedicated database options)[26]
  • MariaDB SkySQL[27]
  • Microsoft Azure SQL Database (MS SQL)[28]
  • Oracle Database Cloud Service[29]
  • Snowflake Cloud Data Warehouse
  • Xeround Cloud Database* – MySQL front-end (*service no longer available)[30]
NoSQL Data Model
  • Apache Cassandra on Amazon EC2[31] or Google Compute Engine[32]
  • ArangoDB on Amazon EC2, Google Compute or Microsoft Azure [33]
  • Clusterpoint Database Virtual Box VM[34]
  • CouchDB on Amazon EC2[35] or Google Cloud Platform[36]
  • EDB Postgres Advanced Server
  • Hadoop on Amazon EC2,[37] Google Cloud Platform,[38] or Rackspace[39]
  • MarkLogic on Amazon EC2[40] or Google Cloud Platform[41]
  • MongoDB on Amazon EC2,[42] Google Compute Engine,[43] Microsoft Azure,[44] or Rackspace[45]
  • Neo4J on Amazon EC2[46] or Microsoft Azure[47]

See also

References

  1. ^ Hwang, G.; Fu, S. (May 2016). "Proof of Violation for Trust and Accountability of Cloud Database Systems". 2016 16th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid): 425–433. doi:10.1109/CCGrid.2016.27.
  2. ^ A. Anjomshoaa and A. Tjoa, "How the cloud computing paradigm could shape the future of enterprise information processing", Proceedings of the 13th International Conference on Information Integration and Web-based Applications and Services - iiWAS'11, pp. 7-10, 2011.
  3. ^ S. Cass, "Designing for the Cloud", MIT Technology Review, 2009. [Online]. Available: https://www.technologyreview.com/s/414090/designing-for-the-cloud/. Retrieved 2016-10-04.
  4. ^ "NoSQL", Wikipedia, 2016. Retrieved 2016-10-04.
  5. ^ Modi, A (2017). "Live migration of virtual machines with their local persistent storage in a data intensive cloud". International Journal of High Performance Computing and Networking. 10 (1): 134. doi:10.1504/IJHPCN.2017.083213.
  6. ^ https://docs.microsoft.com/en-us/azure/architecture/data-guide/big-data/non-relational-data Article in 'Microsoft Azure'
  7. ^ Dave Rosenberg, Are databases in the cloud really all that different?, CNET, Retrieved 2011-11-6
  8. ^ Agrawal, Rakesh; et al. (2008). "The Claremont report on database research" (PDF). SIGMOD Record. 37 (3): 9–19. CiteSeerX . doi:10.1145/1462571.1462573. ISSN 0163-5808. S2CID 666280.
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  15. ^ Swoyer, Stephen. "NuoDB: A Database for the Cloud." TDWI. Nov. 13, 2012. Retrieved Nov. 26, 2012
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  22. ^ "Archived copy". Archived from the original on 2016-04-14. Retrieved 2017-01-15.CS1 maint: archived copy as title (link)
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  24. ^ a b EnterpriseDB#cite note-10
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  26. ^ "Announcing Heroku PostgreSQL Database Add-on", Heroku Blog, Retrieved 2011-11-9.
  27. ^ Yegulalp, Serdar (2020-03-31). "SkySQL, MariaDB-as-a-service, launches on Google Cloud". InfoWorld. Retrieved 2021-02-05.
  28. ^ Noel Yuhanna, SQL Azure Raises The Bar On Cloud Databases, Forrester, Retrieved 2011-11-9.
  29. ^ Pethuru, Raj (2014-03-31). Handbook of Research on Cloud Infrastructures for Big Data Analytics. IGI Global. ISBN 9781466658653.
  30. ^ Klint Finley, "7 Cloud-Based Database Services" Archived 2011-11-09 at the Wayback Machine, ReadWriteWeb, Retrieved 2011-11-9.
  31. ^ "Setting up Cassandra in the Cloud Archived 2015-11-13 at the Wayback Machine", Cassandra Wiki, Retrieved 2011-11-10.
  32. ^ "Google Cloud Platform Blog: Click to Deploy Apache Cassandra on Google Compute Engine". Retrieved 2016-11-28.
  33. ^ "[1]
  34. ^ "Clusterpoint Database Virtual Box VM Installation Guide Archived 2015-03-10 at archive.today", Clusterpoint, Retrieved 2015-03-08.
  35. ^ "Amazon Machine Images, CouchDB 0.10.x 32 bit Ubuntu[permanent dead link]", Amazon Web Services, Retrieved 2011-11-10.
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  37. ^ "Amazon Machine Image, Hadoop AMI[permanent dead link]", Amazon Web Services, Retrieved 2011-11-10.
  38. ^ "Cloud Dataproc - Managed Spark & Managed Hadoop Service". Retrieved 2016-11-28.
  39. ^ "Hadoop at Rackspace Archived 2014-03-02 at the Wayback Machine", Rackspace Big Data Platforms, Retrieved 2014-02-24.
  40. ^ "MarkLogic Developer 8 (HVM) on AWS Marketplace". aws.amazon.com. Retrieved 2016-03-31.
  41. ^ marklogic.com. "Flexible Deployment" (PDF). Retrieved 2016-11-28.
  42. ^ "MongoDB on Amazon EC2, MongoDB.org, Retrieved 2011-11-10.
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  45. ^ "Easily Scale MongoDB at Rackspace Archived 2014-03-02 at the Wayback Machine", Managed MongoDB ObjectRocket by Rackspace, Retrieved 2014-02-24.
  46. ^ "Neo4J in the Cloud Archived 2011-09-25 at the Wayback Machine", Neo4J Wiki, Retrieved 2011-11-10.
  47. ^ "Announcing Neo4J on Windows Azure", Neo4J Blog, Retrieved 2011-11-10.
  48. ^ Andrew Brust, "Cloudant Makes NoSQL as a Service Bigger", ZDNet, Retrieved 2012-5-22.
  49. ^ "Bigtable - Scalable NoSQL Database Service". Retrieved 2016-11-28.
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By: Wikipedia.org
Edited: 2021-06-19 17:55:06
Source: Wikipedia.org

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