Compaction Conundrums: Which Apache Cassandra Compaction Strategy Fits Your Use Case?

We will delve into the three compaction strategies for Apache Cassandra: SizeTieredCompactionStrategy (STCS), LeveledCompactionStrategy (LCS), and TimeWindowCompactionStrategy (TWCS).

SizeTieredCompactionStrategy (STCS)

STCS is the default compaction strategy in Cassandra, designed for workloads with high write and low read volumes. Its primary objective is to merge SSTables (sorted string tables) approximately the same size. Here's a closer look at STCS:

• Write-Heavy Workloads: STCS excels in write-heavy workloads by minimizing the need for frequent compactions reducing write amplification. It is a suitable choice when your application prioritizes write performance.
• Space Amplification: STCS can lead to space amplification issues, necessitating more disk space than the perfectly-compacted data representation. To mitigate space amplification, it's recommended to maintain a buffer space of around 50% of the disk size.
• Read-Heavy Workloads: STCS may not be the best choice in read-heavy environments due to potentially increased read latency from larger SSTables.

LeveledCompactionStrategy (LCS)

LCS takes a different approach by organizing SSTables into levels, making it more suitable for workloads with high read volumes and low write volumes. Key characteristics of LCS include:

• Read-Intensive Workloads: LCS optimizes for read performance by compacting all SSTables older than a specified age into one large SSTable. This approach provides predictable read latency and improved space utilization.
• Write Performance: On the flip side, LCS is more write-intensive than STCS because writes involves more frequent compactions. This can lead to increased write latency and higher I/O operations.

TimeWindowCompactionStrategy (TWCS)

TWCS is tailor-made for handling time-series data, common in applications like IoT sensor data and user activity logs. Here's what you need to know about TWCS:

• Time-Series Data: TWCS groups SSTables into distinct time windows based on data timestamps and compacts only those within the same time window. This approach significantly enhances read performance and effectively manages disk space.
• TTL Consideration: TWCS is particularly effective when dealing with expired data that can be deleted after a certain period, known as Time to Live (TTL). It minimizes the impact on overall performance while optimizing data retention.
• Compaction Approach: It's important to note that TWCS uses STCS for compaction within time windows and does not perform further compactions within TWCS after the STCS compaction is complete.

Choosing the Best Compaction Strategy

Selecting the right compaction strategy is a critical decision that depends on your application's specific requirements. Key factors include balancing read and write operations, data growth patterns, and disk space considerations. Continuous monitoring and adjustment are essential to ensure optimal database performance.

In conclusion, Apache Cassandra offers three main compaction strategies, each suited to different workload characteristics. STCS is ideal for write-heavy workloads, LCS excels in read-intensive environments, and TWCS is tailored for time-series data. Carefully evaluate your application's needs and choose the strategy that best aligns with your goals for performance, space utilization, and data retention.