Modern AI/ML models must run at the edge while being updated constantly
AI/ML systems have insatiable appetites for data. Machine learning models run better with more data, and the more iterations and the more training, tuning and validation you can do, the better your results.
The challenges lie in data preparation (which is painful) and model creation and tuning as models are constantly evolving.
Plus, you need an online system with streaming data and the need to make an inference in milliseconds. The problem is wanting to pull disparate signal data from sources from different countries and data centers in real-time. Sometimes the hardest part of AI/ML isn’t the AI/ML, “it’s the plumbing.”
Benefits of AI/ML data platforms
The Aerospike data platform is designed to ingest large amounts of data in real-time for parallel processing while connecting to compute platforms as well as notebooks and ML packages.
Execute Spark jobs faster with massive parallelism
Reduce training time, increase frequency of retraining, and maximize ROI.
Create low latency inference and training pipelines online
Connect the Aerospike NoSQL database with pre-built integrations for Spark, Kafka and Presto.
Conduct in-place data exploration
Eliminate compliance headaches by removing the need to copy data into multiple systems.
What our partners are saying
"Aerospike is second to none for ingesting and persisting millions of events per second…(Aerospike) allows me to do near-instantaneous machine learning on the data as it lands.”
Theresa Melvin, Chief Architect of AI-Driven Big Data Solutions, HPE