watsonx.data

Imagine a world where querying complex data feels seamless, where exploring datasets becomes intuitive, and where operational bottlenecks are no longer part of the equation. That’s the vision behind the latest tech preview features of watsonx.data. While data lakes and lakehouses are transformative, they often bring challenges like slow query performance, difficult data discovery, and inefficiencies in processing workflows. These are precisely the challenges watsonx.data aims to address with its latest features in preview: Materialized Views, Spark C++ (Gluten), JDBC Pushdown, and Semantic Search.

The Challenges of Modern Data Workflows

In a lakehouse environment, users frequently encounter hurdles:

• Complex Queries Take Time: Joins, aggregations, and other advanced operations can strain resources and lead to delays.
• Data Discovery is Laborious: Finding the right dataset often requires navigating layers of schemas and tables.
• Performance Bottlenecks: Processing inefficiencies result in higher costs and slower insights.

These issues can slow down decision-making, increase operational costs, and hinder innovation.

Watsonx.data’s Solutions: Making Data Simpler and Faster

watsonx.data has introduced four powerful features designed to address these common data processing challenges.

1. Materialized Views

To speed up complex queries, watsonx.data now offers materialized views in public preview. These are pre-computed query results stored for reuse, eliminating the need to repeatedly process the same data.

Solution Benefits:

• Faster Query Execution: Avoid re-running complex joins and aggregations.
• Optimized Resource Use: Reduces computational demands, saving time and costs.
• Seamless Integration: Minimal user intervention required for implementation.

Example: Instead of recalculating sales data every time a report is generated, materialized views provide pre-computed results that can be retrieved quickly, streamlining the process and freeing up resources.

2. Spark C++ (Gluten)

Currently in private preview for on-premises environments, this feature leverages Velox and Gluten to optimize Spark’s performance. It accelerates workloads by offloading tasks to high-performance C++ libraries.

Solution Benefits:

• Enhanced Speed: Processes data in formats like Parquet and CSV faster than traditional Spark engines.
• Workflow Compatibility: Maintains existing Spark workflows while boosting efficiency.

Example: If you are working with large-scale data analysis, Spark C++ accelerates processing, enabling faster results without the need for a full infrastructure overhaul.

3. JDBC Pushdown

JDBC Pushdown, available in public preview, empowers Presto to offload join operations to the data source itself. By reducing data movement and leveraging native processing capabilities, it significantly improves query performance.

Solution Benefits:

• Reduced Network Latency: Minimizes data transfer.
• Better Resource Utilization: Delegates tasks to the data source for faster execution.
• Lower Costs: Cuts down on infrastructure strain and resource consumption.

Example: When accessing data across multiple systems, JDBC Pushdown ensures that only the necessary data is transferred, improving efficiency and reducing strain on infrastructure.

4. Semantic Search

Semantic Search, available in public preview, enhances how users explore and retrieve data within watsonx.data. By enabling natural language queries, it simplifies data discovery across complex datasets. Non-technical users can easily find what they need without requiring SQL knowledge, making data exploration more intuitive and accessible.

Solution Benefits:

• User-Friendly Experience: Eliminates the need for precise SQL queries.
• Accelerated Workflows: Enables quicker access to relevant data.
• Improved Accessibility: Offers a unified search experience across schemas.

Example: Instead of writing SQL queries to filter product sales data, users can simply ask, “Show me sales data for the North region,” and Semantic Search will return the relevant results.

Impact: What These Features Mean for You

The introduction of these features into watsonx.data streamlines data workflows, making it easier for teams to address common data challenges. These updates are designed to improve performance, reduce resource consumption, and enhance data discovery, offering a smoother and more intuitive experience.

• Faster Decision-Making: With reduced query times and quicker data access, teams can make decisions based on real-time insights.
• Optimized Operations: By enhancing performance and resource utilization, watsonx.data helps reduce operational costs and improve efficiency.
• Enhanced User Experience: Features like Semantic Search and Materialized Views empower both technical and non-technical users to work more efficiently, with less time spent on troubleshooting or data management.

Influence the development of watsonx.data

Don’t miss the chance to experience these new features firsthand! Whether you’re looking to speed up query performance or fasten your data ingestion tasks, these tech previews offer a compelling opportunity to advance your analytics strategy.

By participating in the preview programs, you get an exclusive opportunity to explore these features before they are generally available, providing valuable feedback that will directly influence their development.

How to Get Started?

All the above features are free to use! If you’re eager to try out these tech previews, simply fill out this form. If your primary interest lies in the public preview features you can find a detailed guide on how to get started here.

For new users interested in the public preview features, signing up for the Lite Plan is essential. This plan provides access for 30 days or up to 2000 Resource Units (RUs) to explore the watsonx.data.

Sign up today to explore the future of data with watsonx.data!