By Guy Harrison
For a quarter of a century, the relational
database (RDBMS) has been the dominant model for database management.
But, today, non-relational, “cloud,” or “NoSQL” databases are gaining
mindshare as an alternative model for database management. In this
article, we’ll look at the 10 key aspects of these non-relational NoSQL
databases: the top five advantages and the top five challenges.
RDBMS might not scale out easily on commodity clusters, but the new breed of NoSQL databases are designed to expand transparently to take advantage of new nodes, and they’re usually designed with low-cost commodity hardware in mind.
NoSQL databases are generally designed from the ground up to require less management: automatic repair, data distribution, and simpler data models lead to lower administration and tuning requirements — in theory. In practice, it’s likely that rumors of the DBA’s death have been slightly exaggerated. Someone will always be accountable for the performance and availability of any mission-critical data store.
NoSQL databases have far more relaxed — or even nonexistent — data model restrictions. NoSQL Key Value stores and document databases allow the application to store virtually any structure it wants in a data element. Even the more rigidly defined BigTable-based NoSQL databases (Cassandra, HBase) typically allow new columns to be created without too much fuss.
The result is that application changes and database schema changes do not have to be managed as one complicated change unit. In theory, this will allow applications to iterate faster, though,clearly, there can be undesirable side effects if the application fails to manage data integrity.
Living on the technological leading edge is an exciting prospect for many developers, but enterprises should approach it with extreme caution.
In contrast, most NoSQL systems are open source projects, and although there are usually one or more firms offering support for each NoSQL database, these companies often are small start-ups without the global reach, support resources, or credibility of an Oracle, Microsoft, or IBM.
NoSQL databases offer few facilities for ad-hoc query and analysis. Even a simple query requires significant programming expertise, and commonly used BI tools do not provide connectivity to NoSQL.
Some relief is provided by the emergence of solutions such as HIVE or PIG, which can provide easier access to data held in Hadoop clusters and perhaps eventually, other NoSQL databases. Quest Software has developed a product — Toad for Cloud Databases — that can provide ad-hoc query capabilities to a variety of NoSQL databases.
Takeaway: The
relational database model has prevailed for decades, but a new type of
database — known as NoSQL — is gaining attention in the enterprise.
Here’s an overview of its pros and cons.
Five advantages of NoSQL
1: Elastic scaling
For years, database administrators have relied on scale up — buying bigger servers as database load increases — rather than scale out — distributing the database across multiple hosts as load increases. However, as transaction rates and availability requirements increase, and as databases move into the cloud or onto virtualized environments, the economic advantages of scaling out on commodity hardware become irresistible.RDBMS might not scale out easily on commodity clusters, but the new breed of NoSQL databases are designed to expand transparently to take advantage of new nodes, and they’re usually designed with low-cost commodity hardware in mind.
2: Big data
Just as transaction rates have grown out of recognition over the last decade, the volumes of data that are being stored also have increased massively. O’Reilly has cleverly called this the “industrial revolution of data.” RDBMS capacity has been growing to match these increases, but as with transaction rates, the constraints of data volumes that can be practically managed by a single RDBMS are becoming intolerable for some enterprises. Today, the volumes of “big data” that can be handled by NoSQL systems, such as Hadoop, outstrip what can be handled by the biggest RDBMS.3: Goodbye DBAs (see you later?)
Despite the many manageability improvements claimed by RDBMS vendors over the years, high-end RDBMS systems can be maintained only with the assistance of expensive, highly trained DBAs. DBAs are intimately involved in the design, installation, and ongoing tuning of high-end RDBMS systems.NoSQL databases are generally designed from the ground up to require less management: automatic repair, data distribution, and simpler data models lead to lower administration and tuning requirements — in theory. In practice, it’s likely that rumors of the DBA’s death have been slightly exaggerated. Someone will always be accountable for the performance and availability of any mission-critical data store.
4: Economics
NoSQL databases typically use clusters of cheap commodity servers to manage the exploding data and transaction volumes, while RDBMS tends to rely on expensive proprietary servers and storage systems. The result is that the cost per gigabyte or transaction/second for NoSQL can be many times less than the cost for RDBMS, allowing you to store and process more data at a much lower price point.5: Flexible data models
Change management is a big headache for large production RDBMS. Even minor changes to the data model of an RDBMS have to be carefully managed and may necessitate downtime or reduced service levels.NoSQL databases have far more relaxed — or even nonexistent — data model restrictions. NoSQL Key Value stores and document databases allow the application to store virtually any structure it wants in a data element. Even the more rigidly defined BigTable-based NoSQL databases (Cassandra, HBase) typically allow new columns to be created without too much fuss.
The result is that application changes and database schema changes do not have to be managed as one complicated change unit. In theory, this will allow applications to iterate faster, though,clearly, there can be undesirable side effects if the application fails to manage data integrity.
Five challenges of NoSQL
The promise of the NoSQL database has generated a lot of enthusiasm, but there are many obstacles to overcome before they can appeal to mainstream enterprises. Here are a few of the top challenges.1: Maturity
RDBMS systems have been around for a long time. NoSQL advocates will argue that their advancing age is a sign of their obsolescence, but for most CIOs, the maturity of the RDBMS is reassuring. For the most part, RDBMS systems are stable and richly functional. In comparison, most NoSQL alternatives are in pre-production versions with many key features yet to be implemented.Living on the technological leading edge is an exciting prospect for many developers, but enterprises should approach it with extreme caution.
2: Support
Enterprises want the reassurance that if a key system fails, they will be able to get timely and competent support. All RDBMS vendors go to great lengths to provide a high level of enterprise support.In contrast, most NoSQL systems are open source projects, and although there are usually one or more firms offering support for each NoSQL database, these companies often are small start-ups without the global reach, support resources, or credibility of an Oracle, Microsoft, or IBM.
3: Analytics and business intelligence
NoSQL databases have evolved to meet the scaling demands of modern Web 2.0 applications. Consequently, most of their feature set is oriented toward the demands of these applications. However, data in an application has value to the business that goes beyond the insert-read-update-delete cycle of a typical Web application. Businesses mine information in corporate databases to improve their efficiency and competitiveness, and business intelligence (BI) is a key IT issue for all medium to large companies.NoSQL databases offer few facilities for ad-hoc query and analysis. Even a simple query requires significant programming expertise, and commonly used BI tools do not provide connectivity to NoSQL.
Some relief is provided by the emergence of solutions such as HIVE or PIG, which can provide easier access to data held in Hadoop clusters and perhaps eventually, other NoSQL databases. Quest Software has developed a product — Toad for Cloud Databases — that can provide ad-hoc query capabilities to a variety of NoSQL databases.
