Pros of CockroachDB

• Better support for global, multi-region deployments with advanced geo-partitioning features
• More mature and battle-tested in production environments
• Stronger consistency guarantees with serializable isolation level by default

Cons of CockroachDB

• Higher resource consumption, especially for smaller deployments
• Steeper learning curve due to more complex architecture and configuration options
• Less flexible in terms of storage engine options (only RocksDB)

Code Comparison

CockroachDB (SQL syntax):

CREATE TABLE users (
  id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
  name STRING,
  created_at TIMESTAMP DEFAULT current_timestamp()
);

YugabyteDB (SQL syntax):

CREATE TABLE users (
  id UUID PRIMARY KEY DEFAULT uuid_generate_v4(),
  name TEXT,
  created_at TIMESTAMP DEFAULT now()
);

Both databases use similar SQL syntax, with minor differences in function names and data types. CockroachDB uses STRING for text data, while YugabyteDB uses TEXT. The UUID generation functions also have slightly different names.

Overall, CockroachDB and YugabyteDB are both distributed SQL databases with similar goals, but CockroachDB has a slight edge in maturity and global deployment features, while YugabyteDB offers more flexibility in terms of storage engines and potentially lower resource usage for smaller deployments.

Pros of TiDB

• More mature project with a larger community and ecosystem
• Better support for distributed OLAP workloads
• More advanced query optimizer for complex SQL queries

Cons of TiDB

• Steeper learning curve and more complex architecture
• Less compatibility with PostgreSQL ecosystem
• Higher resource requirements for small-scale deployments

Code Comparison

TiDB (Go):

func (s *tikvStore) Begin() (kv.Transaction, error) {
    txn, err := newTiKVTxn(s)
    if err != nil {
        return nil, errors.Trace(err)
    }
    return txn, nil
}

YugabyteDB (C++):

Status YBClient::OpenTable(const string& table_name,
                           shared_ptr<YBTable>* table) {
  return OpenTable(table_name, {}, table);
}

Both projects implement distributed SQL databases, but TiDB focuses on scalability and HTAP workloads, while YugabyteDB emphasizes PostgreSQL compatibility and ease of use. TiDB uses a more complex architecture with separate storage and computation layers, while YugabyteDB has a more integrated approach. TiDB is written primarily in Go, whereas YugabyteDB uses C++ for its core components.

Pros of Cassandra

• Mature and battle-tested with a large community and extensive ecosystem
• Highly scalable and designed for massive distributed deployments
• Strong support for multi-datacenter replication and tunable consistency levels

Cons of Cassandra

• Limited support for ACID transactions and complex queries
• Steep learning curve and complex configuration process
• Lacks built-in SQL support, requiring the use of CQL or additional tools

Code Comparison

Cassandra query (CQL):

SELECT * FROM users
WHERE user_id = 123
AND timestamp > '2023-01-01'
LIMIT 10;

YugabyteDB query (YSQL):

SELECT * FROM users
WHERE user_id = 123
AND timestamp > '2023-01-01'
LIMIT 10;

Key Differences

• YugabyteDB offers PostgreSQL-compatible SQL support (YSQL) in addition to Cassandra-compatible APIs
• YugabyteDB provides stronger consistency guarantees and ACID transactions out of the box
• Cassandra has a longer track record and more extensive production deployments
• YugabyteDB aims to combine the scalability of Cassandra with the ease of use and features of traditional RDBMSs

Both databases excel in distributed environments, but YugabyteDB offers a more familiar SQL experience and stronger consistency, while Cassandra provides unparalleled scalability and a proven track record in large-scale deployments.

Pros of Vitess

• Designed for horizontal scaling of MySQL databases, making it ideal for large-scale deployments
• Provides advanced sharding capabilities, allowing for efficient data distribution
• Offers seamless integration with Kubernetes for orchestration and management

Cons of Vitess

• Steeper learning curve due to its complex architecture and components
• Limited support for non-MySQL databases, focusing primarily on MySQL compatibility
• May introduce additional latency in some scenarios due to its proxy-based architecture

Code Comparison

Vitess (VTGate query execution):

func (e *Executor) Execute(ctx context.Context, session *vtgatepb.Session, sql string, bindVariables map[string]*querypb.BindVariable) (*sqltypes.Result, error) {
    // Query execution logic
}

YugabyteDB (SQL execution):

Status PgSession::ExecuteStatements(const string& query_string,
                                    StatementExecutedCallback cb) {
  // SQL execution logic
}

Both projects implement query execution, but Vitess focuses on routing and proxying MySQL queries, while YugabyteDB directly executes SQL statements in its distributed database engine.

Pros of ScyllaDB

• Higher performance and lower latency due to its C++ implementation and shared-nothing architecture
• Better resource utilization and scalability, especially for large datasets and high-throughput workloads
• More mature and battle-tested in production environments

Cons of ScyllaDB

• Less flexible in terms of consistency models compared to YugabyteDB's tunable consistency
• Limited support for distributed ACID transactions across multiple partitions
• Narrower ecosystem integration and fewer enterprise features than YugabyteDB

Code Comparison

ScyllaDB (CQL):

CREATE TABLE users (
  user_id UUID PRIMARY KEY,
  name TEXT,
  email TEXT
);

YugabyteDB (YSQL):

CREATE TABLE users (
  user_id UUID PRIMARY KEY,
  name TEXT,
  email TEXT
);

Both databases support SQL-like syntax, with ScyllaDB using Cassandra Query Language (CQL) and YugabyteDB offering PostgreSQL-compatible YSQL. The example above shows a simple table creation, which is nearly identical in both systems. However, YugabyteDB's YSQL provides more advanced SQL features and better compatibility with existing PostgreSQL applications.