YSQL与YCQL是否兼容？性能差异及项目选型咨询

Great question! Let's break down the key points about Yugabyte's two APIs clearly—this is a common point of confusion for teams getting started with the database.

Compatibility: Are YSQL and YCQL Interoperable? #

Short answer: No, they are not compatible with each other.

Even though both APIs sit on top of Yugabyte's underlying DocDB storage engine, they maintain completely separate metadata catalogs and enforce distinct query semantics. This means:

• A table created via YSQL (using PostgreSQL-compatible syntax like CREATE TABLE users (id INT PRIMARY KEY, name TEXT);) will not be visible or queryable via YCQL.
• Conversely, a table created with YCQL (e.g., CREATE TABLE users (id INT PRIMARY KEY, name TEXT) WITH CLUSTERING ORDER BY (id ASC);) can't be accessed through YSQL.

Any attempt to cross-query between the two APIs will result in a "table not found" error, as the metadata systems don't share information.

Performance Differences #

While both APIs leverage DocDB's distributed storage capabilities, their design optimizations target different workloads:

• YSQL: Built for PostgreSQL compatibility, it supports full ACID transactions, complex joins, window functions, and advanced SQL features. This makes it ideal for mixed OLTP/OLAP workloads, but the overhead of maintaining PostgreSQL-compliant semantics can lead to slightly lower throughput in high-concurrency write-heavy scenarios compared to YCQL.
• YCQL: Modeled after Cassandra's CQL, it's optimized for high-throughput writes, linear scalability, and low-latency reads for wide-column datasets. It excels in use cases like time-series data, IoT telemetry, or any scenario where write throughput and horizontal scaling are top priorities. However, it has limited support for complex relational operations like multi-table joins.

That said, performance is highly workload-dependent—always benchmark with your specific data patterns to get accurate comparisons.

Should You Prioritize API Selection? #

Absolutely. Your choice of YSQL or YCQL will have long-term implications for your application architecture:

• Choose YSQL if:
  • Your team is already familiar with PostgreSQL
  • You need relational data modeling, complex SQL queries, or strict ACID compliance
  • Your workload involves mixed read/write operations with relational dependencies
• Choose YCQL if:
  • You need Cassandra-like scalability and write performance
  • Your data fits a wide-column, denormalized model (e.g., time-series, event logs)
  • Horizontal scaling and high write throughput are critical

If you have mixed workloads that require both APIs, you can run both in the same Yugabyte cluster—but remember, data between the two APIs is completely isolated. You'll need to implement application-level data syncing or ETL processes if you need to share data between them.

内容的提问来源于stack exchange，提问作者Ali Zeinali