Virtualization Technology News and Information
Article
RSS
VMblog's Expert Interviews: Datos IO Talks about Next-Generation Databases and Recent Survey Findings

DatosIO Interview 

San Jose-based Datos IO, which emerged from stealth mode last year and has so far raised about $15 million in equity funding, recently surveyed 204 IT professionals responsible for application and database deployment, operation, management, and architecture, resulting in a new study that reports on how organizations are deploying "next-generation databases."

As companies consider analytics in an era of big data, they're also considering a range of new database types to accommodate the challenges that come with it.  To find out more, I recently spoke with Tarun Thakur, co-founder and CEO at Datos IO. 

VMblog:  To kick things off, what was your primary goal when conducting this survey?

The enterprise data center is rapidly transforming to accommodate the demands of next generation applications like IoT, on-demand commerce, digital advertising and media, analytics and more. With this in mind, we wanted to know how these high-volume, high-ingestion, real-time applications were impacting the enterprise IT, so we polled 204 IT professionals responsible for application and database deployment, operation, management and architecture, to capture their perspective on adoption and use of next-generation databases. We also set out to investigate and document the challenges, barriers and benefits of next-generation databases, and to forecast future database de-facto standards.

VMblog:  What were the survey's core findings?

We polled IT professionals responsible for next-generation applications and next-generation database deployment, operation, management and architecture across companies ranging in size from less than 500 to more than 10,000 employees worldwide, and found across-the-board rising demand for distributed applications and adoption of scale-out databases, especially MongoDB, Cassandra (Apache and DataStax) and Amazon cloud databases. Also, the majority of apps deployed on next-gen databases sit in the analytics category, with enterprise ERP/CRM, IoT and security applications close behind.

These numbers make a lot of sense, because further into the survey we found that 75%+ of respondents predicted that next-generation databases will influence organizational growth in coming 24 months, and a whopping 80%+ of IT and database professionals believe deployment of next-generation databases will grow by 2x or more by 2018.

VMblog:  What are the challenges facing next-generation database adoption?

This report made it apparent that there are two main barriers to next-gen database adoption: lack of experience and knowledge of next-generation databases, and an obvious lack of robust backup and recovery solutions.

In regards to the non-technical barriers of adoption, there is a significant gap in knowledge and experience at companies of all sizes. Over 60% of respondents stated this lack of experience as the main challenge to adoption, while 44% cite that their company's slow adoption of new technology is what's holding them back.

The report highlights that while there is immediate and increasing interest in evolving infrastructure to support distributed, scale-out databases and cloud databases, a lack of robust backup and recovery technologies hinders adoption, with 61% of respondents citing this issue as potentially (or probably) preventing their organization's adoption of next-generation database technology.

VMblog:  What's to be done?  What industry innovation will assist the adoption of next-gen databases?

The survey revealed that almost 90% of our polled enterprise IT database professionals consider backup and recovery critical for production applications. The trouble is, because these next-generation, distributed databases fundamentally differ from traditional databases, we can't apply the same backup and recovery logic as we do with traditional databases. If you dig into the differences, next-generation databases are the only viable (de-facto) standard for cloud, social, and mobile-based applications because:
  • They are scale-out (eventual consistency) vs. scale-up (strong consistency) in nature
  • They offer flexible data models (schema), for ease of application development
  • They provide cross-data-center replication for application availability
  • And allow "elastic" infrastructures that grow or shrink per application or user growth

All factors that render traditional database recovery solutions ineffectual and inadequate.

Another consideration is that while new scale-out databases permit rapid development of next-generation applications-they lack robust data management tools and that may come at a cost: the cost of application downtime due to potential risk of data loss, the cost of additional operational expenses required to create and manage "hand-scripted" backup and recovery solutions, the cost of unreliable, non-scalable and sub-optimal "hand-scripted" backup and recovery solutions, and the cost of additional infrastructure that is needed to maintain and manage multiple of copies of data over the lifecycle of the data.

It's important to understand that next-generation databases require next-generation data management tooling around them, which includes next-generation data protection. The only way the industry will break down the barriers to adoption is to solve the data protection challenges borne by the innovations in cloud and big data. This way, enterprises will be able to confidently deploy and scale their mission critical applications without worrying about data loss, data corruptions, disasters, or even human errors.

VMblog:  Based on the report, what do you predict is in store for next-gen databases over the coming years?

As I mentioned earlier, more than 80% of enterprise IT and database professionals believe deployment of next-generation databases will more than double by 2018 and more than 75% of respondents predicted that next-gen DBs will influence their organizational growth in the coming 24 months. While there are still hurdles to jump in terms of adoption, the use of next-gen databases will inevitably continue to grow and become more prominent in the near future.

VMblog:  How do next-gen databases, such as MongoDB and Cassandra, fit into the picture?  What other databases made the grade (or didn't) and why?

When polling respondents, we found that scalability, performance and low cost of ownership are seen as the top benefits of using a next-generation database such as MongoDB or Cassandra. In addition to MongoDB and Cassandra, we found that a significant number of enterprises are considering cloud-native databases from Amazon and Microsoft to deploy their next-generation applications. This trend is driven by the goal of enterprises to convert their capital expenditure into operational expenses and leverage database-as-a-service for rapid application development.

VMblog:  What can our readers take away from the report in terms of critical considerations if they're thinking about migrating to a next-gen database?

This survey shows IT application and database professionals clearly understand that for organizations to ride this unprecedented tide of data agility, they also need to innovate other next-generation database elements like data storage, specifically for distributed backup and recovery. To deploy and scale next-generation applications, enterprises must be sure that data can be managed and recovered over its lifecycle at scale. To unlock the full potential of data, it is imperative that businesses fill the data protection gaps that exist before forging ahead.

##

Once again, a special thank you to Tarun Thakur, co-founder and CEO at Datos IO, for taking time out to speak with VMblog and participate in our Expert Interview Series.

Published Wednesday, April 06, 2016 6:34 AM by David Marshall
Filed under: ,
Comments
There are no comments for this post.
To post a comment, you must be a registered user. Registration is free and easy! Sign up now!
top25
Calendar
<April 2016>
SuMoTuWeThFrSa
272829303112
3456789
10111213141516
17181920212223
24252627282930
1234567