What Are Some Databases

Hamsterdb Embedded Storage is an embedded database engine written in ANSI language. It has variable-length keys and record b+trees. It supports in-memory databases and Mantissa-independent files, database cursors, multiple databases in a file, record number databases, and duplicate keys. Hamsterdb is a very fast and highly configurable embedded database engine. The engine can be compiled and run on UNIX, Linux, Windows and Windows CE platforms ...

The coming 2013 is considered to be a "year of big Data" with a trans-era significance. In this year, the data is more precious than ever, and even become a new energy source comparable to the oil resources, the big data is considered as the information and the Internet after the whole revolution of the message again peak. However, large data is not a slogan, and more enterprises need to be put into practice to dig out the potential value from the monotonous data. A survey earlier this year pointed out that 28% of global companies and 25% of Chinese companies have started to practice big data. In order to further understand the real situation of large data application of Chinese enterprises ...

Google created a mapreduce,mapreduce cluster in 2004 that could include thousands of parallel-operation computers. At the same time, MapReduce allows programmers to quickly transform data and execute data in such a large cluster. From MapReduce to Hadoop, this has undergone an interesting shift. MapReduce was originally a huge amount of data that helped search engine companies respond to the creation of indexes created by the World Wide Web. Google initially recruited some Silicon Valley elites and hired a large number of engineers to ...

Large data is one of the most active topics in the IT field today. There is no better place to learn about the latest developments in big data than the Hadoop Summit 2013 held in San Jose recently. More than 60 big data companies are involved, including well-known vendors like Intel and Salesforce.com, and startups like SQRRL and Platfora. Here are 13 new or enhanced large data products presented at the summit. Continuuity Development Company Now ...

Nifty has been operating the site for a long time, and after the launch of the WYSIWYG web platform based on HTML5, users have built more than 54 million sites in the company, and most of them have less than 100 solar PV. Since the PV of each page is low, the traditional caching strategy does not apply. Even so, however, the company has done so with only 4 Web servers. Recently, Wix chief back-end engineer Aviran Mordo in "Wix architecture ...

"IT168 Technical Documentation" Since Oracle and HP launched Exadata, I have been very concerned about this product, and previously wrote an Oracle database machine introduced it. 　　Last year, Oracle and Sun merged to launch Oracle Exadata V2, which has several changes compared to previous generations: first, using sun hardware; second, it claims to support OLTP applications; third, Oracle 11g R2 offers more new features. Exadata S ...

So far, it's time to stop hype about the lack of big data talent and start training and recruiting programs. Experts are trained and not born. One question you need to answer is whether you need technical expertise or data expertise. Expertise allows SQL databases or Hadoop clusters to be used. Data expertise allows us to leverage data mining, text mining, forecasting and machine learning techniques. Either way, we should first of all assume that cultivating talent from existing staff is the most important ...

Star Ring Technology's core development team participated in the deployment of the country's earliest Hadoop cluster, team leader Sun Yuanhao in the world's leading software development field has many years of experience, during Intel's work has been promoted to the Data Center Software Division Asia Pacific CTO. In recent years, the team has studied large data and Hadoop enterprise-class products, and in telecommunications, finance, transportation, government and other areas of the landing applications have extensive experience, is China's large data core technology enterprise application pioneers and practitioners. Transwarp Data Hub (referred to as TDH) is the most cases of domestic landing ...

Big data is fashionable and promises a lot of things, but when organizations try to consolidate their data into large databases in the public cloud, they ignore some technical realities. These days, big figures seem fashionable. It's really big, it's new, it's about Hadoop, and it's generally in the public cloud. Now every week new businesses and new cloud products appear, promising to eventually control the company's data. They are all peddling the same idea: companies can migrate to almost "no capacity limit" PB-level databases through the resilience of the public cloud. ...

The rapidly growing structure and http://www.aliyun.com/zixun/aggregation/13739.html of enterprises "> The management requirements of unstructured data is an important factor in driving enterprises to use Apache Hadoop software. But Hadoop does not replace all existing technologies, according to a study published late last month by Ventana that Hadoop is now working with traditional relational databases (RDBMS). ...

The enterprise database market is huge, with the expertise of Oracle in this area, as well as the Cross-border giants of IBM (DB2) and Microsoft (SQL Server). They are similar to the open source database MySQL commonly used by small and medium-sized enterprises, belong to traditional relational database. It seems that the database market has developed very mature, the basic structure has been determined, so entrepreneurs have no chance? In fact, the emergence and development of new technologies always bring new opportunities. Just as the development and maturity of object-oriented programming technology, DB4O has spawned such pure object-oriented data ...

The big figures, which emerged in 2011 and soar in 2012, may change many aspects of data management in a dramatic way. Large data systems have brought about changes in the management and manipulation of computer data, continuous extraction, transformation and loading functions, operational business intelligence, dynamic large data, and cloud-based data warehouses. However, with large data entering the 2013, there is no system technology more active than the NoSQL database and Hadoop framework, it seems that these two products have more room for development. According to the marketanalysis ....

Cloud computing and virtualization allow you to create virtual machines and use cloud-based services for project management, problem management, and software construction with automated testing. This has encouraged agile software development in six ways. Australian Federal Bank (Commonwealth Bank), one of Australia's leading providers of integrated financial services, has built a private cloud to run internal applications as a service. These applications use more than 300 Oracle databases that are merged into an on-demand Oracle instance, which can be applied in the browser interface ...

Are your businesses getting ready to take big data programs? Either invest in the Hadoop platform or use cloud services to tap into social media streaming? Whatever your goal, we should make it easier to use large data rather than showing great ambition at the outset. This is the experience of GCE's http://www.aliyun.com/zixun/aggregation/35685.html "> chief Marketing Officer and Big Data propagator Marina Lucas, whose company is a cloud service provider ...

Social media, E-commerce, mobile communications, and machine-machine data exchange make terabytes or even petabytes of data that the enterprise IT department must store and process.   Mastering fragmentation best practices is a very important step in the cloud planning process when users process data for cloud computing databases. Fragmentation is the process of splitting a table into a manageable size disk file. Some highly resilient key-value data stores, such as Amazon simple DB, Google App engine ...

Recently, we've heard too much about "big data", lots of new apps, about Hadoop, NoSQL and a variety of new analytics software. 　　I recently spent a lot of time talking to people and thinking about these trends, and finally convinced that the huge changes we've seen, including the data we've collected, and how we're going to deal with that data for individuals, companies and societies. What the organization should do with the data, how to translate the raw data into the information used to make decisions, we are only in the early stages of full reflection. However, I also believe that the term "big data" ...

Over the past three years, the Hadoop ecosystem has expanded to a large extent, with many major IT vendors introducing Hadoop connectors to enhance the top tier of Hadoop or the Hadoop release that the vendor uses. 　　Given the exponential growth in the deployment rate of Hadoop and the growing depth and breadth of its ecosystems, we wonder whether the rise of Hadoop will lead to the end of traditional data warehousing solutions. We can also put this issue in a larger context to discuss: to what extent, large data will change ...

When Hadoop enters the enterprise, it must face the problem of how to address and respond to the traditional and mature it information architecture. 　　In the industry, how to deal with the original structured data is a difficult problem for enterprises to enter large data field. When Hadoop enters the enterprise, it must face the problem of how to address and respond to the traditional and mature it information architecture. In the past, MapReduce was mainly used to solve unstructured data such as log file analysis, Internet click Stream, Internet index, machine learning, financial analysis, scientific simulation, image storage and matrix calculation. But ...

"51CTO classic" I like MongoDB mainly because it is so simple and natural to use it in dynamic languages. So far, I've used it in two projects (Encode and SPARRW), although I'm very happy with the choice, but there are some problems I haven't noticed, and these problems have kept me scratching my scalp for hours. If you have more than one machine, and then allocate a few more machines for the database, then some problems can be solved, but my project is running on a single (virtual) server on the low flow w ...

In practical applications, "big data" seems to be often misunderstood. Large data does store and process a large number of data sets, but its characteristics are much more than that. Large data architectures and platforms are new things, and they are evolving at an extraordinary rate. 　　The business and open source http://www.aliyun.com/zixun/aggregation/7434.html "> Development team is publishing its platform's new features almost every month. Today's big data clusters will be with the data clusters we see in the future ...