By Harry Darell Brown
KX and Microsoft have announced the release of kdb Insights Enterprise on Azure, the high-performance time series analytics engine for MLOps and Cloud data pipelines enabling business users, application developers and data scientists to collaborate in building massively scalable, enterprise-impacting, insights-rich, data-driven applications quickly and easily
KX is the provider of kdb+, the fastest and most efficient data analytics engine in the cloud, which is used to capture and process high-volume, high-velocity data across a range of industries including finance, manufacturing, automotive and healthcare. kdb Insights Enterprise on Azure extends kdb+ with the expansive catalog of Azure services overlaying a low code and pro code programming approach. Deploy Azure blob storage, containerization, security, microservices, cloud-native resilience and high availability to enable quick, flexible deployment of lightning-fast query speeds and advanced vector math into Azure data architectures and MLOps and DevOps pipelines for 100x faster, more configurable and massively scalable analytics.
kdb Insights Enterprise on Azure benefits forward-thinking data science and machine learning workflows in particular. It provides teams with an intuitive drag-and-drop interface to manage data pipelines and include Python and SQL to incorporate rich queries and analytics. Together, data application developers, data scientists and data engineers can collaborate to build data-driven cloud native analytics rapidly, and leverage the simplicity, resilience, high availability and autoscaling capacity of the Azure ecosystem. Machine Learning or Model Ops (MLOps) workflows of cloud-centric historical queries, model training, feature store populations, streaming analytics and real-time model inference is merely a few clicks and minutes away. See how quickly in the video below!
Watch now to learn how easy to use kdb Insights Enterprise is as the world’s first data timehouse on Microsoft Azure.
Available on Azure Marketplace, giving instant access to Azure services under existing agreements and supported by their SLAs, kdb Insights Enterprise on Azure helps organizations achieve up to 100x time-series performance at 1/10th of the cost of lake, warehouse and other solutions.
kdb Insights Enterprise on Azure includes:
The system enables the storage and sharing of data pipelines, schemas, and assemblies that describe the structure of a dataset, its life cycle, and the services that operate upon it. Define and run SQL and Python functions, and apply transformations within data pipelines like windowing, filtering, and machine learning.
kdb Insights Enterprise on Azure is deployed with just a small number of clicks that provisions the system, freeing the user from architecture, hardware or infrastructure set-up concerns.
Use cases built upon kdb Insights Enterprise on Azure range from algorithmic trading and automated risk management in finance to anomaly detection, predictive analytics observability across high-volume time series data manufacturing, healthcare and telecommunications.
It leverages key Azure services such as:
Other general-purpose features that make development easier and more configurable include:
Embrace the Cloud with Simplicity. Simply leverage Azure
kdb Insights Enterprise on Azure allows data engineers, DevOps and CloudOps teams to modernize their data applications as they embrace the cloud and take advantage of Azure’s proven capability for innovative data science and MLOps pipelines. Given kdb Insights Enterprise on Azure’s capacity to store and process vast amounts of both streaming and historical data – wherever it resides across the pipeline – while ensuring high resilience, seamless failover and high availability, kdb Insights Enterprise is a particularly powerful medium for machine learning. Data scientists can concentrate on building powerful collaborative notebooks that analyse more data, leverage machine learning research code sets, and reduce time to deployment. In the words of one client:
Pre-KX, more than 80 percent of our time was taken to get the data into a form that permitted good data science from the test result. KX means our engineers can spend time on science and not data transformation.
With kdb Insights Enterprise on the Azure Marketplace, deploy pipelines in minutes, hours and days, not in weeks or months. Populate them with data, and make valuable decisions in instantaneous 100x faster and, when required, in real-time.