The traditional relational database has good performance and stability, at the same time, the historical test, many excellent database precipitation, such as MySQL. However, with the explosive growth of data volume and the increasing number of data types, many traditional relational database extensions have erupted. NoSQL database has emerged. However, different from the previous use of many NoSQL have their own limitations, which also led to the difficult entry. Here we share with you Shanghai Yan Technology and Technology Director Yan Lan Bowen - how to build efficient MongoDB cluster ...
Replica sets+http://www.aliyun.com/zixun/aggregation/14273.html ">sharding architecture is as follows: 1,shard server: Using Replica Sets ensures that each data node has the ability to backup, automatic fault-tolerant transfer, and automatic recovery. 2, configure the server: Use 3 configuration servers to ensure metadata integrity 3, routing process: Use 3 routing processes to achieve balance, improve client access ...
In recent days, database start-ups citus data to implement fast SQL queries on Hadoop, which is not a big deal, because for them, the bigger goal is in the back. Citus data has gone beyond postgres to extend its high-speed, analytical database Citusdb to Hadoop, and then it should be expanding to MongoDB and other database products you already think of. Gigaom's correspondent Derrick Harris thinks Citus data is ...
"Editor's note" Shopify is a provider of online shop solutions company, the number of shops currently serving more than 100,000 (Tesla is also its users). The main frame of the website is Ruby on rails,1700 kernel and 6TB RAM, which can respond to 8,000 user requests per second. In order to expand and manage the business more easily, Shopify began to use Docker and CoreOS technology, Shopify software engineer Graeme Johnson will write a series of articles to share their experience, this article is the department ...
The REST service can help developers to provide services to end users with a simple and unified interface. However, in the application scenario of data analysis, some mature data analysis tools (such as Tableau, Excel, etc.) require the user to provide an ODBC data source, in which case the REST service does not meet the user's need for data usage. This article provides a detailed overview of how to develop a custom ODBC driver based on the existing rest service from an implementation perspective. The article focuses on the introduction of ODBC ...
Recently, China Minsheng Bank Big Data Project officially launched. The project, with IBM and the giant FIR Database Company (SEQUOIADB), sequoiadb to build Low-cost, high-performance, highly reliable and horizontally expanding data platforms for CMBC through IBM biginsights large data solutions and enterprise-class NoSQL databases. To help Minsheng bank through large data analysis to meet the financial industry's big data challenges, to achieve profound industry insights. The platform uses the full set of IBM Biginsights and partner SEQUOIADB ...
Now Apache Hadoop has become the driving force behind the development of the big data industry. Techniques such as hive and pig are often mentioned, but they all have functions and why they need strange names (such as Oozie,zookeeper, Flume). Hadoop has brought in cheap processing of large data (large data volumes are usually 10-100GB or more, with a variety of data types, including structured, unstructured, etc.) capabilities. But what's the difference? Today's enterprise data warehouses and relational databases are good at dealing with ...
Now Apache Hadoop has become the driving force behind the development of the big data industry. Techniques such as hive and pig are often mentioned, but they all have functions and why they need strange names (such as Oozie,zookeeper, Flume). Hadoop has brought in cheap processing of large data (large data volumes are usually 10-100GB or more, with a variety of data types, including structured, unstructured, etc.) capabilities. But what's the difference? Enterprise Data Warehouse and relational number today ...
Now Apache Hadoop has become the driving force behind the development of the big data industry. Techniques such as hive and pig are often mentioned, but they all have functions and why they need strange names (such as Oozie,zookeeper, Flume). Hadoop has brought in cheap processing of large data (large data volumes are usually 10-100GB or more, with a variety of data types, including structured, unstructured, etc.) capabilities. But what's the difference? Today's enterprise Data Warehouse ...
Docker is undoubtedly the most popular open-source technology this year, and Docker is now the darling of entrepreneurs and innovators in the IT world. Regardless of Google, Microsoft, Amazon, IBM and other technology manufacturers are actively supporting Docker technology, Docker although the introduction and use is very simple, but the whole ecosystem is quite large, and its underlying technology is also very complex, the current based on Docker technology projects springing up, today, The author summarizes the rapid evolution of the Docker related technology, to share with you. Kubernet ...
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