\n| Number of servers available\u00a0<\/span><\/td>\n | Americas \u2013 8<\/span><\/p>\n Europe \u2013 5<\/span><\/p>\nAsia Pacific \u2013 9<\/span><\/td>\n | Americas \u2013 4<\/span><\/p>\n Europe \u2013 3<\/span><\/p>\nAsia Pacific \u2013 7<\/span><\/td>\n<\/tr>\n\n| Limit columns in a table<\/span><\/td>\n | 1,600 columns<\/span><\/td>\n | 10,000 columns<\/span><\/td>\n<\/tr>\n\n| Online data entry<\/span><\/td>\n | Must use <\/span>Amazon Kinesis Firehose<\/span><\/td>\n | Support\u00a0<\/span><\/td>\n<\/tr>\n\n| Manageability \/ usability<\/span><\/td>\n | Users need to configure the infrastructure, requiring periodic management<\/span><\/td>\n | No configuration required<\/span><\/td>\n<\/tr>\n\n| Security<\/span><\/td>\n | Inherit the security features of Amazon Web Services\u00a0<\/span><\/p>\n Data encryption must be enabled\u00a0<\/span><\/p>\nD\u1ecbch v\u1ee5 ng\u0103n ng\u1eeba m\u1ea5t d\u1eef li\u1ec7u (DLP) c\u1ee7a AWS l\u00e0 Macie, kh\u00f4ng \u0111\u01b0\u1ee3c h\u1ed7 tr\u1ee3 cho Redshift<\/span><\/td>\n | Inheriting security features of Google Cloud Platform\u00a0<\/span><\/p>\n Encrypt data by default<\/span><\/p>\nGoogle Cloud DLP Service supports BigQuery<\/span><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/span>Performance: RedShift vs BigQuery\u00a0<\/b><\/span><\/h2>\nThe performance of these 2 data warehouse solutions is relative. Usually, performance depends on data complexity, user data table size, number of online queries, among other factors. However, users can manually configure it to use the advanced features available in BigQuery. In terms of speed, BigQuery can outperform RedShift, especially if you are using dc2 service. large nodes.<\/span><\/p>\n<\/span>Structure<\/b><\/span><\/h3>\nAmazon and Google have different approaches to providing their services. Amazon's approach is either infrastructure as a service (IaaS) or platform as a service (PaaS). Customers are responsible for capacity planning and must provide compute and storage nodes on the platform. Google's approach is more like software as a service (SaaS). BigQuery is serverless, no resource allocation required. You can sign up for a service, access the web UI or REST API, and initiate a query.<\/span><\/p>\n<\/span>Update table<\/b><\/span><\/h3>\nColumnar databases are architected to support fast analytical processing. However, that architecture makes them slow and inefficient when updating and modifying. However, both Redshift and BigQuery can handle data modification, although they do it in different ways.\u00a0<\/span><\/p>\nRedshift can do all of the above, but only through a complex process. Redshift does not provide the UPSERT command to update the table. The user has to load the data into the staging table and then join the staging table to the destination table for the UPDATE statement and the SELECT statement.\u00a0<\/span><\/p>\nBigQuery is designed as an optimal system for this operation. In 2017, Google released Data Manipulation Language (DML) to allow users to update, insert, and delete data.<\/span><\/p>\n<\/span>Support development<\/b>\u00a0<\/span><\/span><\/h3>\nAWS provides SDKs for C#, Go, Java, Node.js, PHP, Python, Ruby, .NET, and JavaScript. There is also the Redshift API.\u00a0<\/span><\/p>\nGoogle provides a Cloud SDK that supports C#, Go, Java, Node.js, PHP, Python, and Ruby. It includes many services on top of GCP, including BigQuery. Google also supports REST APIs for creating, managing, sharing, and querying data, as well as APIs for BigQuery Data Transfer Service and BigQuery Storage.<\/span><\/p>\n<\/span>RedShift & Big Query \u2013 Which option is right?<\/b><\/span><\/h2>\nChoosing between Amazon Redshift and Google BigQuery will depend entirely on the needs of each business, as the winning data warehouse should be the one that works best in your environment to meet your specific business needs. organization. Redshift and BigQuery have many similarities, but also important differences that can scale. If you are not heavily invested in AWS, Redshift might be a good choice for you. If your database administrator resources are limited then BigQuery is a better choice. Or you have a data table with 1,600+ columns like Gimasys \u2014 use BigQuery.<\/span><\/p>\nAbove is all you need to know about s<\/span>compare Amazon Redshift vs Google Bigquery<\/b>. If your business is interested in Google Bigquey or platform <\/span>Google Cloud<\/span> Then you can connect with Gimasys - a senior partner of Google in Vietnam to get advice on solutions to build applications according to your own needs. Contact now:<\/span><\/p>\n\n- Gimasys \u2013 Google Cloud Premier Partner<\/b><\/li>\n
- Hotline: <\/b>Hanoi: 0987 682 505 \u2013 Ho Chi Minh: 0974 417 099<\/span><\/li>\n
- Email: <\/b>gcp@gimasys.com<\/span><\/li>\n<\/ul>\n
Source: Gimasys<\/b><\/p>","protected":false},"excerpt":{"rendered":" So s\u00e1nh hai n\u1ec1n t\u1ea3ng d\u1eef li\u1ec7u ph\u1ed5 bi\u1ebfn Amazon Redshift v\u00e0 Google BigQuery l\u00e0 m\u1ed9t kh\u00eda c\u1ea1nh quan tr\u1ecdng \u0111\u1ec3 c\u00e1c doanh nghi\u1ec7p \u0111\u01b0a ra quy\u1ebft \u0111\u1ecbnh th\u00f4ng minh v\u1ec1 vi\u1ec7c l\u1ef1a ch\u1ecdn c\u00f4ng c\u1ee5 ph\u00f9 h\u1ee3p v\u1edbi nhu…<\/p>","protected":false},"author":2,"featured_media":14658,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"inline_featured_image":false,"footnotes":""},"categories":[1,135],"tags":[],"class_list":["post-14655","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-kienthuc","category-google-cloud-platform","entry","has-media"],"_links":{"self":[{"href":"https:\/\/gcloudvn.com\/en\/wp-json\/wp\/v2\/posts\/14655","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/gcloudvn.com\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/gcloudvn.com\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/gcloudvn.com\/en\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/gcloudvn.com\/en\/wp-json\/wp\/v2\/comments?post=14655"}],"version-history":[{"count":0,"href":"https:\/\/gcloudvn.com\/en\/wp-json\/wp\/v2\/posts\/14655\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/gcloudvn.com\/en\/wp-json\/wp\/v2\/media\/14658"}],"wp:attachment":[{"href":"https:\/\/gcloudvn.com\/en\/wp-json\/wp\/v2\/media?parent=14655"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/gcloudvn.com\/en\/wp-json\/wp\/v2\/categories?post=14655"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/gcloudvn.com\/en\/wp-json\/wp\/v2\/tags?post=14655"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}} | | | | |
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