2 posts tagged with "feature"

The intersection of AI and real-time data is important. PyTorch, TensorFlow, Sci-Kit-Learn, and NLTK are ubiquitous libraries for data science workflows. To service real-time use cases, they pair well with Deephaven, a query engine that brings Python to "streaming dataframes" -- essentially "tables that update".

Uniting these two powerhouses should be easy. The deephaven.learn library was released in December, providing a gather-compute-scatter paradigm to Deephaven's streaming tables, in support of AI integrations.

Today, the team released an upgrade to the deployment options available to AI-motivated users. With a simple curl script, you can now download a Docker image that combines Python, Deephaven, and the AI library of your choice.

Copy, paste... done.

It's natural to frame new information in the context of what you already know and understand. The same is true when determining where new vendors and technology/solution providers fit into established marketplaces. Deephaven enters an arena defined by Kafka, Spark, Influx, Redshift, BigQuery, Snowflake, Postgres, and dozens of other players.