The News: Cloudera, (NYSE: CLDR), the enterprise data cloud company, recently announced new and upcoming enterprise data cloud services on Cloudera Data Platform (CDP): CDP Data Engineering; CDP Operational Database; and CDP Data Visualization. The new services are analytic experiences designed specifically for data specialists and, unlike general purpose services that require add-ons for critical capabilities like workflow automation, job prioritization, and performance tuning, include these key capabilities to help data engineers, data analysts, and data scientists work smarter and faster. CDP enterprise data cloud services are purpose-built to enable data specialists to confidently navigate the storm of exponential data growth and siloed data analytics operating across multiple public and private clouds. Read the full release on Cloudera.
Analyst Take: Last week, Cloudera hosted its large annual event, virtually, Cloudera Now. Amidst 3 days of in depth discussion on the company and its strategic direction, the company also included the announcement of wave of new enterprise data cloud services on its data platform-Cloudera Data Platform (CDP).
These new announcements are important to point out due to the specialized nature of what is being built and how these capabilities will help Cloudera’s users with a greater degree of data skills (which is most) to leverage important capabilities like workflow automation and job queuing–this will help accelerate data projects and reduce time to insight, which is what companies are seeking to accomplish these days as data volumes grow exponentially adding complexity but also opportunity for companies to do more with their data.
Three New Services for CDP: Data Engineering, Operational Database and Data Visualization (highlights via Cloudera release)
CDP Data Engineering
CDP Data Engineering is a powerful Apache Spark service on Kubernetes and includes key productivity enhancing capabilities typically not available with basic data engineering services:
- Visual GUI-based monitoring, troubleshooting and performance tuning for faster debugging and problem resolution
- Native Apache Airflow and robust APIs for orchestrating and automating job scheduling and delivering complex data pipelines anywhere
- Resource isolation and centralized GUI-based job management
- CDP data lifecycle integration and SDX security and governance
Take: I believe CDP Data Engineering is an important service to provide a catalyst for the development of enterprise data pipelines. This includes the collection, enrichment, visualization and insights, all being built and delivered at scale.
CDP Operational Database
CDP Operational Database is a high-performance NoSQL database service that provides unparalleled scale and performance for business critical operational applications, offering:
- Evolutionary schema support to leverage the power of data while preserving flexibility in application design by allowing changes to underlying data models without having to make changes to the application
- Auto-scaling based on the workload utilization of the cluster to optimize infrastructure utilization and cost
- Multi-modal client access with NoSQL key-value using HBase APIs and relational SQL with JDBC, making CDP Operational Database accessible to developers who are used to building applications that use MySQL, Postgres, etc.
- CDP data lifecycle integration and SDX security and governance
Take: The continued exponential growth in the volumes of structured and unstructured data, are pushing developers to their limits tasking them with rapidly building applications that democratize data access, enable actions in real-time and are integral to business operations and revenue generation. CDP Operational Database is designed to support the scale and performance requirements for these developers to be able to more fluidly accomplish these ambitious app development objectives.
CDP Data Visualization
CDP Data Visualization simplifies the curation of rich, visual dashboards, reports and charts to provide agile analytical insight in the language of business, democratizing access to data and analytics across the organization at scale:
- Technical teams can rapidly share analysis and machine learning models using drag and drop custom interactive applications.
- Business teams and decision makers can consume data insights and make trusted, well informed business decisions.
- All teams benefit from fast data exploration using AI-powered natural language search and visual recommendations.
Take: There are often disconnects between data tools and the business. This has been a catalyst for BI and data visualization tools, but often these are additional software or applications that mean more data migration and management. Cloudera is looking with this tool to help analysts and data science teams to be able to share and explain analytical results in a way that business stakeholders can more rapidly understand and act upon. I also see the potential for this to have some additional self-service capabilities for less tech/data fluent users to be able to self-service for certain analytics needs.
Estimated Release Timeline
According to the release, CDP Data Engineering is generally available on AWS. CDP Operational Database and CDP Data Visualization are in technical preview and are expected to be generally available later this year.
Overall Impressions of New Cloudera Enterprise Data Cloud Services
Cloudera continues to push its ambitions in the open source data space. CDP is being purpose built with the intention of supporting the enterprise IT architecture wave that is largely settling on hybrid. This means tools need to work fluidly with big clouds like AWS and Azure while also being robust to continue to support on-prem requirements. All of this while being on top of compliance, regulatory and governance needs–with security and experience top of mind.
Futurum Research provides industry research and analysis. These columns are for educational purposes only and should not be considered in any way investment advice.
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The original version of this article was first published on Futurum Research.
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