从关系数据库迁移到NoSQL云数据库

显示全部楼层 · 2014-2-19 11:55:14

Takeaway: Matt Asay describes the approach one needs to take in migrating a standard relational database to an open source NoSQL cloud database.

－－－－－－By Matt Asay

The industry is on the cusp of tectonic changes in how and where data are stored and processed. For over 30 years, the venerable relational database management system (RDBMS), running in corporate data centers, has held the bulk of the world’s data. This cannot continue. RDBMS technology can no longer keep pace with the velocity, volume, and variety of data being created and consumed. For this new world of Big Data, NoSQL databases are required.
Migrating to these open-source cloud databases, however, requires some preparation for enterprise IT that grew up with RDBMS.
How Big Data is changing everything
There’s nothing wrong with the traditional RDBMS. It simply doesn’t fit the world we live in anymore. Mobile, social, cloud: these and other trends complicate the variety of data and dramatically increase the volume of data being stored in the enterprise.
As RedMonk analyst James Governor argues:
The database market is back in play after a 30-year old freeze in which Oracle dominated the high end, and Microsoft the midmarket. Then along came open source, the cloud, NoSQL, in memory and everything changed….The idea that everything is relational? Those days are gone.

千问 · 2014-2-19 11:55:14

This isn’t something that only concerns so-called web companies like Google and Foursquare. It’s equally relevant for “old school” organizations in the Finance, Healthcare, Government, Retail, and other vertical industries, and projected by Gartner to drive $28 billion in IT spending in 2012.
As organizations grapple with their Big Data problems, when data grow beyond one server or start in a distributed fashion, they generally find themselves on the same road as the web companies: open-source, NoSQL databases.
While Big Data often gets associated with data analytics technologies like Hadoop and Storm, it’s actually much broader than this, and far more concerned with data storage than analytics.
After all, if an enterprise can’t scale storage effectively, it will never have a “Big Data” problem to analyze. Hence, of the $30 billion global database market, only 25 percent is analytics, with the rest being OLTP or operational databases.
Ironically, the recent rise of data analytics innovations like Hadoop stems from RDBMS failure to cope with Gartner’s three V’s of Big Data: high-volume, high-velocity, and high-variety of data.

千问 · 2014-2-19 11:55:14

Migrating from RDBMS to NoSQL
It’s clear that the database is critical to successfully managing the explosion of data. What’s less clear is how to transition from legacy RDBMS to modern NoSQL databases. Successfully migrating from a relational world to a NoSQL world requires careful planning.
In fact, one of the biggest dings against NoSQL databases like MongoDB or Neo4j is that they’re so easy to work with that developers end up jumping in headfirst, without bothering to properly construct their data model, thereby causing problems later. While NoSQL databases do provide significantly more developer agility and flexibility, they stillshouldn’t be used willy-nilly.
This is particularly true for those starting from an RDBMS background, as NoSQL differs markedly from relational. In the RDBMS world, an engineer designs the data schema from the outset, and SQL queries are then run against the database. If business/application changes then require changes to the database, a DBA must get involved. It’s not an easy process, as the DBA must navigate complex joins (i.e., inter-table relationships).
NoSQL databases better fit modern application development, and provide significant database performance and developer agility benefits, albeit at the expense of some functionality.

千问 · 2014-2-19 11:55:14

Training
NoSQL databases are new enough that many database engineers will be RDBMS experts, but NoSQL neophytes. This shouldn’t deter developers hoping to use NoSQL in a new project. After all, most NoSQL databases are open source and come with built-in communities, happy to help new users get up to speed.
Part of this shift is one of nomenclature. For example, as relational database expert Chris Bird points out, the syntax in NoSQL Land differs greatly from SQL, and may require some mental gymnastics for new users.
According to Daniel Doubrovkine, Art.sy’s head of engineering, both NoSQL and RDBMS databases impose a learning curve on new users. The difference, he argues, is that NoSQL databases like MongoDB are simple to start with and get more complex over time, which works because a developer’s expertise with the database matures over time, too.
With SQL, Doubrovkine says, it’s hard from the start and only becomes more complex at scale, if the requisite scale is even possible with RDBMS.
Of course, getting everything “perfect” from the start is difficult no matter what database technology you’re using. As noted, Mozilla and XEmacs developer Jamie Zawinski opines,
The design process is definitely an ongoing thing; you never know what the design is until the program is done.

千问 · 2014-2-19 11:55:14

One of the great things about NoSQL, in fact, is the ability to iterate on one’s data model as one’s business requires it.
That’s not to say that developers should go in blind. For some, checking forums and online documentation is enough. No matter the NoSQL database a developer may prefer, there is plenty of online documentation for each of them.
For others, hands-on training is preferred. In addition to standard, classroom-based training offered by DataStax, Basho, and other vendors that sponsor open-source NoSQL databases, there is also free online training. As just one indication of how strong demand is for NoSQL training, 10gen registered over 30,000 people for its inaugural online training.