Apache Cassandra is a highly scalable, high-performance distributed NoSQL database designed to handle large amounts of data across many commodity servers, without any single point of failure. Initially developed by Facebook to power their Inbox Search feature, it was open-sourced in 2008 and has since become one of the most popular NoSQL databases.

Key Features of Cassandra:

  1. Decentralized System: Every node in the cluster has the same role. There’s no single point of failure, and data is distributed across the cluster (even across multiple data centers).
  2. Elastic Scalability: You can easily add more nodes to the system to accommodate more data. As you add more nodes, the system linearly scales its performance.
  3. Fault Tolerant: Data is replicated across multiple nodes. If one node fails, data can be retrieved from other nodes. This ensures high availability and resilience to node failures.
  4. Tunable Consistency: While most databases offer a fixed level of consistency, with Cassandra, you can tune it according to your needs. You can choose between strong consistency to eventual consistency.
  5. CQL (Cassandra Query Language): Similar in syntax to SQL, CQL allows for easier interfacing with the database.
  6. Schema-Free: Cassandra allows for flexibility with data. Columns can be added to rows without having to modify the schema.
  7. Support for Multi-Data Center Replication: Built-in support for replicating data across multiple data centers ensures higher availability and resilience to failures.

Benefits of Cassandra:

  1. Performance at Scale: Built from the ground up to scale out, Cassandra offers high write and read throughput.
  2. Resilience: With no single point of failure and data replication, Cassandra offers robust fault-tolerance.
  3. Flexible Data Storage: Store structured, semi-structured, and unstructured data.
  4. Integrated Caching: Row-level caching boosts read performance.

Limitations:

  1. Learning Curve: Cassandra has its own set of terminologies and configurations that can be challenging for newcomers.
  2. Data Modeling: Proper data modeling is crucial for achieving optimal performance, and this can be quite different from relational databases.
  3. Lack of Joins and Subqueries: Cassandra doesn’t support joins or subqueries, which can require adjustments in how you design and query your data.
  4. Write Amplification: Due to its log-structured storage engine, Cassandra can have high write amplification which can wear out SSDs faster.

In summary, Apache Cassandra is a robust and scalable NoSQL database, particularly suited for applications where scalability and high availability are crucial. Common use cases include online applications that require large scale and fast growth such as e-commerce platforms, streaming services, and online banking. As with any technology choice, the appropriateness of Cassandra depends on the specific requirements of the project in question.