Database Technology

PlanetScale has launched Neki, a new database engine designed to provide sharded PostgreSQL capabilities. This release aims to address scalability challenges for large-scale applications by distributing data across multiple nodes while maintaining a familiar Postgres interface. The introduction marks a significant step in expanding PlanetScale's infrastructure offerings beyond their existing Vitess-based MySQL services.

• Neki enables horizontal scaling for Postgres workloads via sharding.
• Maintains Postgres compatibility for easier migration and development.
• Expands PlanetScale's portfolio into the Postgres ecosystem.
• Targets high-throughput applications requiring distributed data storage.

Christophe Pettus argues that max_connections functions primarily as a memory budget and circuit breaker rather than a hard limit on concurrent query execution. Actual concurrency is constrained by CPU cores and storage capacity, which are determined by the underlying hardware. This setting controls how many client backends the server can spawn, not how many queries run simultaneously.

• max_connections is a memory budget and circuit breaker, not a query concurrency limiter.
• Real concurrency limits are defined by CPU cores and storage I/O capacity.
• Hardware selection, not GUC tuning, determines maximum simultaneous query load.
• Adjust max_connections to manage backend memory overhead, not query throughput.

Microsoft has halted new customer onboarding for Azure SQL Data Sync, with a full service termination scheduled before 2027. While existing deployments remain operational, the vendor has not announced a direct replacement product. This leaves current users with limited visibility into the migration path for ongoing synchronization needs.

• New onboarding for Azure SQL Data Sync is closed immediately.
• Service termination is set before 2027, forcing eventual migration.
• No like-for-like successor has been provided by Microsoft.
• Existing customers can continue operations until the cutoff date.

Observing repeated schema proposals with excessive index drops, the author investigated whether coding agents over-index. A test harness loaded 30 model-generated schemas into PostgreSQL, auditing 838 indexes across twelve samples. The results showed that most generated indexes were competent, with only ten serving no discernible requirement.

• Coding agents tend to propose excessive indexes, even when the logic is sound.
• Auditing 838 indexes revealed most were necessary, not just AI slop.
• Review processes must account for high competence in AI-generated SQL.
• Expect repetitive index-related questions to shift toward optimization.

AWS details how to build high-concurrency async Python applications using Tortoise ORM alongside Amazon Aurora DSQL. The guide covers specific adaptations such as UUID primary keys, IAM-authenticated asyncpg connections, and individual DDL execution. It also outlines implementing optimistic concurrency control with retry logic to handle contention.

• Use UUIDs for primary keys to support distributed async workloads effectively.
• Patch asyncpg to handle IAM authentication for secure database connections.
• Execute DDL statements individually to ensure compatibility with async patterns.
• Implement OCC retry logic to manage concurrency conflicts in high-load scenarios.