Optimize performance without compromising on availability. Analyze structured data, transactional data, and other “hot” data as they happen – even before they are stored.
Extensible architecture leverages Best-of-Breed Engines and supports Near-App, Big Data, Operational Data, and Advanced Analytics.
Simplifying access to your data for high speed analytics bridging the performance gap between BI and Big Data with Seamless Integration for your existing infrastructure.
Ampool’s lightning-fast data store makes it suitable for any application, enabling quicker insights and faster query response. Some common use cases include:
Collect data from multiple and disparate sources and store them in a centralized data platform that supports faster data analytics and processing
Utilize a single interface for better collaboration and interaction
Transform data into consistent and readable formats compatible with enterprise applications and integration tools
Ingest data directly coming from connected devices and industry standard sensors
Process and analyze millions of real-time data with an active and powerful data platform to deliver real-time insights
Utilize Apache Spark (or other ML framework) to process sensor data and meet wide-ranging application requirements
Collect, process, and analyze customer data stored in CRM applications, databases, and other channels
Measure customer interaction, engagement, and loyalty
Gain 360-degree view into customer behavior and increase support agility
Capture, analyze, and process customer activity to create a personalized user experience
Create upsell and cross-sell opportunities by providing customized recommendations
Enable customer segmentation and targeting in real-time through a powerful data platform
Quantify risks in aggregated portfolios across the organization and perform scenario analyses for better risk planning
Detect and identify fraud, intrusions, and security breaches by analyzing millions of data and events in real-time
Gain better visibility into high-risk areas
From a nascent Apache project in 2006 to being commercially supported data platform by two public companies, Apache Hadoop has…Learn More
Ampool supports integrations at various levels: low-level language bindings, interfaces with compute and storage frameworks, and full-stack data platforms.