All Analyst Perspectives
Posted by Matt Aslett on Jan 19, 2022 3:00:00 AM
Few trends have had a bigger impact on the data platforms landscape than the emergence of cloud computing. The adoption of cloud computing infrastructure as an alternative to on-premises datacenters has resulted in significant workloads being migrated to the cloud, displacing traditional server and storage vendors. Almost one-half (49%) of respondents to Ventana Research’s Analytics and Data Benchmark Research currently use cloud computing products for analytics and data, and a further one-quarter plan to do so. In addition to deploying data workloads on cloud infrastructure, many organizations have also adopted cloud data and analytics services offered by the same cloud providers, displacing traditional data platform vendors. Organizations now have greater choice in relation to potential products and providers for data and analytics workloads, but also need to think about integrating services offered by cloud providers with established technology and processes. Having pioneered the concept, Amazon Web Services has arguably benefitted more than most from adoption of cloud computing, and is also in the process of expanding and adjusting its portfolio to alleviate challenges and encourage even greater adoption.
Posted by Matt Aslett on Jan 5, 2022 3:00:00 AM
The need for data-driven decision-making requires organizations to transform not only the approach to business intelligence and data science but also accelerate the development of new operational applications that support greater business agility, enable cloud- and mobile-based consumption, and deliver more interactive and personalized experiences. To stay competitive, organizations need to prioritize the development of new, data-driven applications. As a result, many have been encouraged to invest in new data platforms designed to support agile development and cloud-based delivery. This is one of the factors driving the growth of MongoDB, and continues to drive the evolution of its document database into what is now described as a cloud-based application data platform.
Posted by Matt Aslett on Dec 30, 2021 3:00:00 AM
The term NoSQL has been a misnomer ever since it appeared in 2009 to describe a group of emerging databases. It was true that a lack of support for Structured Query Language (SQL) was common to the various databases referred to as NoSQL. However, it was always one of a number of common characteristics, including flexible schema, distributed data processing, open source licensing, and the use of non-relational data models (key value, document, graph) rather than relational tables. As the various NoSQL databases have matured and evolved, many of them have added support for SQL terms and concepts, as well as the ability to support SQL format queries. Couchbase has been at the forefront of this effort, recognizing that to drive greater adoption of NoSQL databases in general (and its distributed document database in particular) it was wise to increase compatibility with the concepts, tools and skills that have dominated the database market for the past 50 years.
Posted by Matt Aslett on Dec 23, 2021 3:00:00 AM
Data lakes have enormous potential as a source of business intelligence. However, many early adopters of data lakes have found that simply storing large amounts of data in a data lake environment is not enough to generate business intelligence from that data. Similarly, lakes and reservoirs have enormous potential as sources of energy. However, simply storing large amounts of water in a lake is not enough to generate energy from that water. A hydroelectric power station is required to harness and unleash the power-generating potential of a lake or reservoir, utilizing a combination of turbines, generators and transformers to convert the energy of the flowing water into electricity. A hydroanalytic data platform, the data equivalent of a hydroelectric power station, is required to harness and unleash the intelligence-generating potential of a data lake.
Posted by Matt Aslett on Dec 14, 2021 3:00:00 AM
As I noted when joining Ventana Research, the range of options faced by organizations in relation to data processing and analytics can be bewildering. When it comes to data platforms, however, there is one fundamental consideration that comes before all others: Is the workload primarily operational or analytic? Although most database products can be used for operational or analytic workloads, the market has been segmented between products targeting operational workloads, and those targeting analytic workloads for almost as long as there has been a database market.
Posted by Matt Aslett on Dec 2, 2021 3:00:00 AM
Breaking into the database market as a new vendor is easier said than done given the dominance of the sector by established database and data management giants, as well as the cloud computing providers. We recently described the emergence of a new breed of distributed SQL database providers with products designed to address hybrid and multi-cloud data processing. These databases are architecturally and functionally differentiated from both the traditional relational incumbents (in terms of global scalability) and the NoSQL providers (in terms of the relational model and transactional consistency). Having differentiated functionality is the bare minimum a new database vendor needs to make itself known in a such a crowded market, however.
Posted by Matt Aslett on Nov 24, 2021 3:00:00 AM
It has been clear for some time that future enterprise IT architecture will span multiple cloud providers as well as on-premises data centers. As Ventana Research noted in the market perspective on data architectures, the rapid adoption of cloud computing has fragmented where data is accessed or consolidated. We are already seeing that almost one-half (49%) of respondents to Ventana Research’s Analytics and Data Benchmark Research are using cloud computing for analytics and data, of which 42% are currently using more than one cloud provider.
Posted by Matt Aslett on Nov 11, 2021 3:00:00 AM
Enterprises looking to adopt cloud-based data processing and analytics face a disorienting array of data storage, data processing, data management and analytics offerings. Departmental autonomy, shadow IT, mergers and acquisitions, and strategic choices mean that most enterprises now have the need to manage data across multiple locations, while each of the major cloud providers and data and analytics vendors has a portfolio of offerings that may or may not be available in any given location. As such, the ability to manage and process data across multiple clouds and data centers is a growing concern for large and small enterprises alike. Almost one-half (49%) of respondents to Ventana Research’s Analytics and Data Benchmark Research study are using cloud computing for analytics and data, of which 42% are currently using more than one cloud provider.
Posted by Matt Aslett on Oct 30, 2021 3:00:00 AM
I am very happy to announce that I have joined Ventana Research to help lead the expertise area of Digital Technology, including Analytics and Data, Cloud Computing, Artificial Intelligence and Machine Learning, the Internet of Things, Robotic Automation, and Collaborative and Conversational Computing. While the breadth of applications and technology covered by our Digital Technology practice is broad, I will naturally make use of my decades of experience covering data platforms and analytics to help organizations improve the readiness and resilience of business and IT operations.