According to the company the next-generation QDS platform, which was unveiled in May this year, self-manages and self-optimizes, allowing data teams to focus on business outcomes rather than managing the platform. The new architecture analyzes metadata (queries, clusters, users, data, etc.) generated by platform usage and applies machine learning and artificial intelligence to create alerts, insights, and recommendations, and offers autonomous agents that perform actions automatically.
The company states that its Data Service provides a single platform for ETL, reporting, ad-hoc analysis, stream processing and machine learning, helping data teams at companies such as Lyft, Pinterest and Under Amour be more productive and reduce the costs of their data initiatives. QDS runs on AWS, Microsoft Azure and Oracle Bare Metal Cloud, leveraging its cloud capabilities. It also supports the leading open-source engines, including Apache Spark, Hadoop, Presto, Hive among others.
“Even though big data technologies have greatly advanced, most organizations have trouble operationalizing their big data efforts because data teams simply cannot scale to meet demands for data across the organization,” said Ashish Thusoo, Co-Founder and CEO, Qubole.
“What’s needed is to remove the manual effort that comes with maintaining a big data infrastructure so that data teams are empowered to focus on high-value, strategic work. The automation we’ve built into the Qubole platform delivers true self-service while minimizing costs, optimizing performance and reliability.”
QDS Enterprise Edition includes the new Alerts, Insights and Recommendations (AIR) features that deliver intelligent, actionable information to data professionals. Powered by Qubole’s new machine learning infrastructure, AIR can be rule-based, workload-aware and predictive, and becomes increasingly accurate by learning from user behavior over time.
QDS Business Edition provides companies with free access to the QDS platform – the customer only pays the regular fees to their cloud provider of choice. QDS Business Edition offers all the functionality of QDS Enterprise Edition and is only limited to a specified amount of compute hours per month. It’s ideal for smaller scale deployments and companies developing big data applications.
QDS Cloud Agents, is an optional add-on to QDS Enterprise Edition, autonomously executes a range of data management tasks that are typically time-consuming, manual tasks. The initial release of QDS Cloud Agents includes the following three agents:
- Workload-Aware Auto-Scaling Agent – optimizes cluster sizes for workload requirements to reduce over-provisioning and automates management of heterogeneous clusters.
- Spot Shopper Agent (AWS Only) – intelligently shops across AWS cloud to assemble the compute instances in the optimal combination of performance and cost.
- Data Caching Agent – optimizes the locality of your data for fast, interactive access speeds.
The company has also stated that it will also offer QDS Community Edition as an educational tool for students and others looking to explore big data, later this year. The community will be free for up to four nodes and five clusters.