Category: Computing & data (Page 49 of 90)

DataStax announced Astra Streaming, a scalable, multi-cloud messaging and event streaming platform built on Apache Pulsar. Astra Streaming is integrated with DataStax’s marquee serverless database, Astra DB, to deliver a multi-cloud solution for managing both data in motion and data at rest. With the introduction of Astra Streaming, DataStax aims to deliver on its vision of an open data stack for today’s multi-cloud applications that require massive scale, zero-downtime availability, and high performance. Astra Streaming Features:

• Global scale, cloud-native streaming, powered by Apache Pulsar without the complexity of self-managed solutions
• Compatible with Apache Kafka and Java Messaging Service
• Multi-cloud
• Simple developer APIs for streaming
• Handles high-volume queuing and pub-sub messaging and more complex messaging patterns
• Pay-as-you-go pricing

Astra Streaming is available today in a beta version. To get started with Astra Streaming, create a free account.

https://www.datastax.com

In its second major release of the year, DataRobot announced several product upgrades to its Augmented Intelligence platform designed to further democratize AI. The 7.1 release introduces:

• MLOps Management Agents – DataRobot’s MLOps Management Agents provide advanced lifecycle management for an organization’s remote models. Management Agents understand the state of any remote model regardless of how they were created or where they are running, and can automate various tasks.
• Feature Discovery Push-Down Integration for Snowflake – Joint DataRobot and Snowflake customers can benefit from the automatic discovery and computation of new features for their models directly in the Snowflake Data Cloud.
• Time Series Eureqa Model Enhancements – DataRobot Automated Time Series now runs its unique Eureqa forecasting models as part of the regular Autopilot process. Eureqa models are based on the idea that a genetic algorithm can fit different analytic expressions to trained data and return a mathematical formula as a machine learning model.
• No-Code AI App Builder – the No-Code AI App Builder allows customers to quickly turn any deployed model into a rich AI application without a single line of code.

Additional product upgrades: Data Prep for Time Series, Nowcasting for Time-Aware Models, Automated AI Reports, and Prediction Jobs and Scheduling UI.

https://www.datarobot.com

Dataiku, an Enterprise AI platform, announced the launch of Dataiku Online, which makes their AI and machine learning platform available as an online service for smaller, more agile organizations. Dataiku Online provides everything a company needs to build analytics projects, with data preparation, data visualization, AutoML, reporting, and dashboards all in one place. It has all of the key capabilities as Dataiku’s flagship product, with a few configuration and design tweaks to match its managed usage, and without the IT resources required to manage an enterprise-scale deployment. The interface enables collaboration across a broad range of business and data team users, and teams can start within minutes, connect to their data sources, and start deploying projects in days, at a price point that makes sense for their current stage of growth.

With Dataiku Online, businesses can take advantage of cloud data stack and data storage tools from Snowflake, Google Big Query, Amazon Redshift. There is a pre-integrated version of Dataiku Online available through the Snowflake Marketplace.

Dataiku is also launching an offering for specifically for startups. Seed-stage companies, and startups founded less than five years ago or with less than $10M in funding can be eligible for discounted pricing specific to their current stage of growth. 

https://www.dataiku.com/product/dataiku-as-a-managed-service

Snowflake unveiled new product innovations for the Data Cloud, including data programmability, global data governance, and platform optimizations.

Data programmability:

• Snowpark. With initial support for Java and Scala, Snowflake’s developer experience, Snowpark, allows data engineers, data scientists, and developers to build using their preferred language and execute these within Snowflake.
• Java UDFs. With Java user-defined-functions (UDFs), customers can bring their custom code and business logic to Snowflake.
• Unstructured data. Snowflake’s unstructured data support enables customers to store, govern, process, and share file data alongside their structured and semi-structured data.
• SQL API. The Snowflake SQL API enables applications to call Snowflake directly through a REST API.

Global governance:

• Classification. Snowflake’s classification capability automatically detects personally identifiable information (PII) in a given table and leverages the tagging framework to annotate the data.
• Anonymized views. This can be used to protect privacy and identity in a dataset.

Platform:

• Improved Storage Economics. Better compression, and reduced storage costs.
• Improved Support for Interactive Experiences. Updates released for high volume and low latency workload requirements improve query throughput on a single compute cluster.
• Usage Dashboard. New usage dashboard helps customers better understand usage and costs across the platform.

https://www.snowflake.com