3 posts tagged with "snowflake"

Hi everyone!

We're excited to share with you the release of Atlas v0.38, filled with many new features and enhancements for you to try.

• Oracle Triggers and Views - We've expanded the support for Oracle schemas to include triggers and views.
• Snowflake Additions - Our library of supported resources for Snowflake has also expanded with the additions of stages, external tables, hybrid tables, and dynamic tables.
• Google Spanner Additions - Spanner users can now manage geo-partitioning placements, locality groups, sequences, and change streams with Atlas.
• Expanded Analyzer Detection - Our linting analyzers now detect SQL injections in SQL schema and migration files, and incorrect usage of transactions in migration files.
• HTTP Data Source - Users can now use HTTP endpoints as data sources in the Atlas configuration file.
• PII Detection - Objects containing potentially sensitive or PII data can now be automatically or manually tagged in the Atlas Registry.
• Pre/Post-migration Hooks - Pre- and post-migration hooks enable teams to run custom logic before and after applying migrations.
• Atlas Monitoring - The Atlas Agent can now automatically discover and monitor RDS instances across multiple AWS accounts using IAM role assumption.
• Azure DevOps Repos CI/CD Integration - Atlas now provides native integration with Azure DevOps Pipelines and Azure Repos, including a dedicated Azure DevOps extension for seamless database schema CI/CD workflows.

Snowflake's cloud data platform has transformed data warehousing, yet many teams still manage schema changes using manually-composed SQL scripts and verification processes. As data teams grow and pipelines become more complex, these approaches often become more challenging to maintain and much riskier to use.

Schema changes in production environments can quickly lead to unexpected behavior and inconsistent data, and having more contributors increases the risk of human error leading to costly downtime or data integrity issues. These cases are familiar to many data teams because the traditional manual database deployment methods come with implicit risks.

To address these challenges, Snowflake teams have begun adopting tools to automate schema changes, enforce safety checks, and ensure consistent deployments across environments.

In this post, we will compare three popular Snowflake schema management tools – Atlas, schemachange, and SnowDDL – and guide you in building reliable CI/CD pipelines to deploy schema changes with more confidence and control.

Hey everyone!

We're excited to announce the release of Atlas v0.36 with a comprehensive set of new features and improvements that further strengthen Atlas as your go-to database schema management tool:

• Snowflake Driver Beta - Atlas now supports Snowflake databases in beta, expanding our data warehouse schema management capabilities.
• PostgreSQL Partitions - Declarative management of PostgreSQL partitions has long been a top community request, and we are excited to say it's now available!
• Azure DevOps Integration - Seamless CI/CD integration with Azure DevOps pipelines for database schema management.
• Google Spanner Beta - Beta support for Google Cloud Spanner, bringing Atlas to Google's horizontally scalable and globally distributed database.
• Datadog SIEM Support - Enhanced security monitoring with Datadog integration for audit logs and schema monitoring.
• ORM Schema Linting - Advanced schema validation and policy enforcement for all supported ORM integrations.
• Explain Pipelines Errors - New AI-powered error explanations to help you quickly understand and resolve deployment errors with Atlas Pipelines.