Rapids Data One-Stop High-Performance Real-Time Big Data Analytics Platform
— Built for the future —
RapidsDB - ISO standard-based, in-memory big data analytics platform
- Distributed, MPP, shared-nothing in-memory database
- Unified ANSI SQL query support for multiple data sources
- Adaptive query pushdown and dynamic query optimization
- Supports multiple table joins across nodes
- Supports TPC-H and TPC-DS levels of complicated query analysis
Based on open source Apache Hadoop technology, Rapids Hadoop is dedicated to helping enterprises build data lakes in a short period of time through strictly size-controlled installation packages. The pre-loaded Hadoop with optimized configurations ensures fast deployment of large-scale clusters.
Through the federated HDFS Connector, CSV (delimited) Parquet and ORC format data can be extracted from Hadoop and consolidated with other federated data sources including streaming data for real-time big data analysis in RapidsDB.
- Open source-based Hadoop technology that supports batch processing and real-time analysis of heterogeneous big data
- Provides various SQL-on-Hadoop analytical application tools
- Preset optimized Hadoop configuration that promotes high-speed deployment of large-scale clusters
- Supports cloud computing configurations including IaaS, YARN, and Mesos
- Integrates and authenticates various open source ETL and BI applications
- Provides a rich collection of APIs
Rapids StreamDB - ISO standard-based, in-memory streaming data processing engine
StreamDB is an in-memory and distributed stream database that can continuously analyze streaming data within milliseconds. High-velocity data streams (real-time big data) can be distributed to high-speed memory processing clusters to achieve real-time analysis and processing, breaking through the performance bottleneck of the traditional framework of storing data first before getting it processed.
- Millisecond-level real-time data processing and computing
- Fully compatible with ANSI SQL and a variety of window functions
- Incremental data refresh
- Supports multiple data source integration
Rapids ParallelAI- AI-enabled big data analytics
ParallelAI is an AI-enabled analytics platform with an in-memory, distributed, parallel implementation of the R language and the R operating environment integrated within a RapidsDB cluster. It enables users to apply machine learning against data being managed by RapidsDB.
Rapids ParallelAI currently supports 20 popular algorithms in 4 categories for complex modeling.
- Statistical analysis
- Deep neural networks
- Dimension reduction
Rapids DBaaS Cloud
Rapids DBaas Cloud is composed of a series of physical hosts in a cloud-based architecture to form an operational resource pool that is centrally managed and regulated by the Rapids Management Server. Once a request is approved by the Rapids Management Server, it is sent to a member server in the computing resource pool to create a cluster for the user to use.
- Fast and standardized deployment of large-scale clusters
- Flexible and convenient expansion
- Maximized hardware resource utilization
- Timely recovery of idled resources based on the life cycle management
x86-based All-in-One Machine – low development and operating costs
Teaming up with industry-leading server manufacturers to deliver industry-standard and cost-efficient x86 servers that have the Rapids Data Platform pre-installed to provide high-performance, all-in-one big data storage and analytics solutions.
- Cost-efficient all-in-one machine
- Guaranteed high-performance