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By joining forces, KX and AWS are together redefining technology that optimizes analytic workflows of streaming, vector, and matrix data into a unified, low latency and low complexity stack that supports modern business requirements in the cloud.
kdb Insights on AWS enables fast, efficient time-series analytics in the cloud. For developers, data scientists, and data engineers, kdb Insights on AWS delivers high-performance time-series data analytics – with time-series applications deployed directly to AWS to make the most of the agility, security, and scalable storage. Seamless integration with AWS services, like Lambda, S3, and Redshift, empowers you to create a highly performant data analytics solution built for today’s cloud and hybrid ecosystems.
kdb Insights on AWS offers high-performance time-series data processing that can handle large volumes of data quickly and efficiently, resulting in faster data analytics and quicker time-to-insight, making informed decisions faster, and gaining a competitive advantage.
With the elastic infrastructure of AWS, kdb Insights can easily scale up or down depending on changing data needs and demands, letting you quickly adapt to changing conditions and efficiently manage growth, without worrying about the underlying infrastructure.
Running kdb Insights on AWS lets users take advantage of pay-as-you-go pricing models which ensures users only pay for the resources they use. The additional ability to scale up or down provides greater cost efficiency and helps maximize the value of their data while minimizing costs.
kdb Insights on AWS offers high-performance time-series data processing that can handle large volumes of data quickly and efficiently, resulting in faster data analytics and quicker time-to-insight, making informed decisions faster, and gaining a competitive advantage.
With the elastic infrastructure of AWS, kdb Insights can easily scale up or down depending on changing data needs and demands, letting you quickly adapt to changing conditions and efficiently manage growth, without worrying about the underlying infrastructure.
Running kdb Insights on AWS lets users take advantage of pay-as-you-go pricing models which ensures users only pay for the resources they use. The additional ability to scale up or down provides greater cost efficiency and helps maximize the value of their data while minimizing costs.
kdb Insights on AWS delivers high-performance time-series data processing, allowing data scientists and engineers to handle large volumes of data quickly and efficiently, accelerating time-to-insight.
With the elastic infrastructure of AWS, data scientists can scale up or down to meet changing data needs, without worrying about underlying infrastructure or resources.
Seize the power of the cloud to build a powerful and performant data analytics solution, seamlessly integrating with other AWS services, such as Lambda, S3, and Redshift.
kdb Insights provides a range of APIs and tools that make it easy for developers, data scientists and engineers to build and deploy custom data analytics applications, using the tools and languages they are already familiar with.
kdb Insights on AWS can provide cost savings compared to on-premises solutions or other cloud providers, with a pay-as-you-go pricing model that allows you to pay only for the resources they use, with the ability to scale up or down as needed.
Enjoy a high-performance time series data analytics engine with a range of APIs and tools that make it easy for developers, including those who use q and Python, to build and deploy custom data analytics applications in the cloud, with seamless integration with other AWS products and services.
kdb Insights on AWS offers a robust and scalable data processing platform that enables data engineers to build and manage data pipelines across their entire ecosystem – on-prem, at the edge and in the cloud – with built-in security features and the ability to scale up or down as needed.
Analyze large volumes of time-series data quickly and efficiently, unlocking the full potential of your data analytics – in real-time. With its high-performance analytics engine and developer-friendly APIs and tools, data scientists can test and deploy algorithms faster, finding value from more data to deliver context rich insights.
With Amazon FinSpace Managed kdb Insights, financial institutions can support their most advanced kdb applications using Python and SQL. Offering an improved user experience and a seamless integration with other AWS services, Amazon FinSpace Managed kdb Insights significantly reduces the operational costs of running kdb Insights by eliminating manual configuration, operations, and maintenance. Firms no longer have to worry about managing the underlying infrastructure that powers their analytics workloads. With kdb Insights running on the AWS cloud, banks and hedge funds can avoid large upfront infrastructure purchases with pay-as-you-go kdb compute and storage. The automatic scaling and built-in high availability ensure that kdb applications keep up with volatile market conditions, and meet requests for new analytics capabilities from business teams in hours instead of months.
Offering new levels of cloud modernization, value, and innovation for infrastructure, market data, and front office teams, kdb Insights on Amazon FinSpace, delivers up to 100X the performance at 1/10th of the cost of alternative solutions. Test drive Amazon FinSpace with Managed kdb Insights free for 30 days.
Easily store kdb database files, encrypted with a KMS key you provide. Use of cloud object store technology seamlessly scales the kdb database as data volumes grow. Integrated, and configurable, high-performance caching accelerate important queries, while managing the cost of what data is cached. The built-in database versioning allows you to restore back in time to query your data as it existed at any point in time.
Using simple APIs, customers can easily launch and configure kdb clusters in an instant. Managed kdb Insights eliminates most of the operational overhead and provides pay as you go compute for kdb Insights applications. Managed kdb Insights is integrated with Terraform, to enable integration with CI/CD workflows, and AWS services, such as CloudWatch, CloudTrail, and IAM Permissions.
Managed kdb Insights includes configurable autoscaling to ensure that kdb applications can keep up with the most volatile market conditions. You can also configure Multi-AZ to ensure kdb applications are highly available during the more important business hours giving you added peace of mind.
Easily configure kdb ticker plants, real time clusters, historical clusters, and gateways to match existing environment to easily migrate existing kdb workloads and Q code. In addition to configuration as code through programmatic AWS APIs, customers can setup, access and managed the kdb environment (database and clusters) via the familiar interface of the FinSpace console for added simplicity.
This eBook explores how quantitative analysts can find insights – and Alpha – faster, by leveraging the Right Data at the Right Time, incorporating streaming and historical data onto a single data platform, and supercharging Python and SQL models.
KX and BestX join forces to discuss the many tech, regulatory, and market factors that are driving change within Best Execution Analytics. Topics covered include the adoption of the cloud, regulatory changes such as MIFID2 and RG97, and process automation.
In this simple architecture diagram, data from the data sources is collected and stored in S3. kdb Insights Enterprise would be used to read data from S3, and to perform analytical queries on this data. For example, for a healthcare use-case, the system could track patient outcomes, monitor patient health trends, and identify potential health risks. The results of these queries can be stored in S3 or processed further using EMR. Finally, the analysis results can be visualized and explored using analytics and visualization tools. Note, this is a simplified architecture diagram with many possible variations depending on the specific use case and requirements.
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