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Built for The Modern Data Ecosystem |
Kdb Insights works everywhere with a single environment and unified logins to enable quick results no matter how complex your infrastructure is. By tapping the power of open standards, kdb Insights empowers developers and data scientists to focus on business functionality for rich querying and graphical representation of results rather than grappling with hardware infrastructure and deployment challenges.
Kdb Insights runs natively on leading cloud providers, such as Azure, AWS, and GCP, and private clouds using trusted technologies like Docker, Terraform, Kubernetes, and Helm for ease of deployment, portability, and resilience.
It can similarly run on-prem and, uniquely, because of its small footprint, on edge devices for those embracing hybrid architectures or circumstances where processing must remain local. In addition to the same software and analytics running seamlessly and identically across multiple environments, KX operates best practices single sign-on and security protocols like Keycloak to manage user credentials making access across all environments similarly easy.
For example, Python developers can embed KX directly within Python using PyKX, enabling the reuse of existing Python code, libraries, and machine learning workflows. Similarly, ANSI SQL connectivity allows users to continue working with their existing ETL, data management functionality, and BI tools.
Each case makes adoption easier, avoids retraining, and retains the value of previous investments. That, in turn, accelerates time to business value by reducing development overhead, testing cycles, and deployment risk.
Database connectivity based on widely used open standards enables the reuse of existing queries and simplifies migration to KX. Examples include:
Interfaces to third-party languages enable developers to accelerate delivery by reusing existing libraries and functionality. APIs include:
KX integrates with middleware like Solace and Kafka for message delivery and connecting to machine learning platforms like Keras and TensorFlow.
REST APIs provide for easy, open connectivity and integration with supporting microservices that make it easy to connect and combine the functionality of KX and other technologies via discovery services and OpenAPI protocols.
This openness enables organizations to retain the value of existing investments and technical skills in other areas, thereby reducing risk and accelerating solution development through code reuse and industry-standard interconnectivity.
This openness enables organizations to retain the value of existing investments and technical skills in other areas, thereby reducing risk and accelerating solution development through code reuse and industry-standard interconnectivity.
Database connectivity based on widely used open standards enables the reuse of existing queries and simplifies migration to KX. Examples include:
Interfaces to third-party languages enable developers to accelerate delivery by reusing existing libraries and functionality. APIs include:
KX integrates with middleware like Solace and Kafka for message delivery and connecting to machine learning platforms like Keras and TensorFlow.
REST APIs provide for easy, open connectivity and integration with supporting microservices that make it easy to connect and combine the functionality of KX and other technologies via discovery services and OpenAPI protocols.