The database market is in a state of upheaval. Keeping informed about database trends will help you successfully navigate the changing landscape.
Databases are proliferating like, well, cockroaches. The overall database market is expected to reach $50 billion by 2017, according to IDC, with the landscape changing quickly among many new players.
Deep, impactful forces are underneath these changes,said Tarun Thakur, co-founder and CEO of cloud data recovery startup Datos IO, who mentions economics, open source databases, new applications and the cloud among them.
Here are some of the most significant database trends:
The majority of next-gen applications have a high volume of real-time data coming in.
“Today’s application includes many, many different endpoints; they might be browsers, mobile devices or sensors on machines. It’s what I call a ‘follow you everywhere’ system,” explained Robin Schumacher, vice president of products for DataStax, the commercial company building upon Apache Cassandra.
“It tends to be geographically distributed; they’re all around the globe. They’re intensely transactional; there’s information being passed back and forth constantly. The system can never go down. And they tend to be very responsive. It’s fast and it’s intelligent: what to do next, where to click next, what to buy next.”
Traditional databases are ill-equipped to handle applications that run everywhere at once, have data synchronized everywhere and provide the same levels of data access and performance to all those end points, he said.
Kurt Mackey, CEO of Compose, a database-as-a-service vendor acquired by IBM, points to the sophistication of the features developers want to deliver to users.
Using Facebook as an example, he said, “Facebook will happily tell you, ‘Hey, there’s a friend of yours nearby’ and these new features spawn all this imagination [about the possibilities among other companies], so developers are getting a lot of requests for features that use a lot of different types of data, like geodata.”
DataStax is among the companies pursuing a multi-model strategy, in which one database handles multiple types of data and different data models.
An e-commerce vendor’s application might include a product catalog, user-profile management, a shopping cart, a recommendation engine, a fraud-detection component and analysis, for instance. All these components likely will have different data management and storage requirements, Schumacher said.
Gartner has predicted that by 2017, all leading operational database management systems will offer multiple data models, including relational and NoSQL, in a single platform.
However, Mackey warned that multi-model can get database vendors in trouble. “[Especially when they raise a lot of money,] they expand the scope of what they’re trying to solve and lose sight of why they’re really good at things,” he said.
Rapid growth remains an ongoing problem for database users, and scale has been a particular weakness for relational databases. High-scale heavyweights including Facebook, Google, LinkedIn and Twitter have teamed up to solve this problem in MySQL with a project called WebScaleSQL.
It’s a problem new entrants to the market are trying to solve, such as Crate which offers distributed SQL-supporting Docker containers and microservices.
NoSQL databases, meanwhile, boast of their scalability, such as the “push button” scalability of Riak KV through its integration with Mesos orchestration.