LDW 2.1.7 released: DV Web, Sync Tool, Modular Connectors

As you might have already read before on our newsletter or social media posts, we released the Data Virtuality Logical Data Warehouse version 2.1 already late last year. Version 2.1 consists of three main features that have been introduced in detail in our blog:

• Data Virtuality Web: Next-level self-service BI
• Data Virtuality Sync Tool: Simplified data model changes
• Modular Connectors: Fast & easy data querying without manual SQL coding

After a gradual rollout of version 2.1, it now becomes generally available and new releases will be announced here in the community as well. At the same time, we are also retiring version 2.0, which will not see any new releases from today on. It will, however, remain supported for a transition period until version 2.1 has been rolled out completely.

Besides the three main features, version 2.1.7 contains minor improvements as usual:

Studio

• DVCORE-5895 (Improvement): Introduce a way to specify either Start Date or End Date in Queries tab

Connectors

• DVCORE-5447 (Improvement): Enable configuring JVM proxy settings for Amazon S3
• DVCORE-5109 (Improvement): Enhance the name generation mechanism for temporary S3 buckets
• DVCORE-4834 (Improvement): Allow to define bucket prefix for Snowflake and Redshift with Amazon S3 upload
• DVCORE-3850 (Improvement): Enable configuring JVM proxy settings for Amazon S3 upload for Redshift and Snowflake
• DVCORE-3761 (Improvement): Implement multi-part upload to Amazon S3
• DVCORE-4954: Add exception handling and retries when requests hit Amazon rate limit for Redshift with S3 upload

Backend

• DVCORE-6103 (Improvement): Data Virtuality REST API: allow bulk-calling a procedure
• DVCORE-5906 (Improvement): Provide a way for SSH tunnel to auto-recover after failures
• DVCORE-6100: CHAIN_NOT_TRIGGERED status is not stored to SYSADMIN.ScheduleJobs system table
• DVCORE-5890: Clean stale replicator tables task fails when analytical storage is not configured
• DVCORE-5856: Allow direct streaming from archives without caching the data in RAM or HDD