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Cassandra vs Galera Cluster: What are the differences?
1. Scalability: Cassandra is designed for high scalability by distributing data across multiple nodes in a cluster, allowing linear scalability for both read and write operations. Galera Cluster, on the other hand, is a synchronous replication solution that can have limitations in scaling due to the need for all nodes to commit transactions in a multi-master setup.
2. Consistency: Cassandra offers tunable consistency levels, enabling users to choose between strong consistency and high availability. Galera Cluster enforces strict synchronous replication, ensuring strong consistency across all nodes but potentially impacting performance in certain scenarios.
3. Data Replication: In Cassandra, data replication is achieved through the replication factor and consistency level settings, allowing for control over data durability and availability. Galera Cluster replicates data synchronously across all nodes, ensuring that each node holds a copy of the same data at all times.
4. Partitioning: Cassandra uses consistent hashing to partition data across nodes, providing efficient distribution and retrieval of data. Galera Cluster does not support automatic data partitioning and relies on traditional sharding methods for horizontal scaling.
5. Conflict Resolution: In Cassandra, conflict resolution is handled through timestamps and client-provided timestamps, resolving conflicts based on the latest timestamp. Galera Cluster resolves conflicts at the network level, requiring strict consistency to avoid conflicts among nodes.
6. High Availability: Cassandra provides built-in fault tolerance through data replication and automatic data repair mechanisms. Galera Cluster relies on synchronous replication for high availability, which can introduce latency and performance trade-offs in certain scenarios.
In Summary, Cassandra focuses on scalability and flexibility in data distribution, while Galera Cluster prioritizes strong consistency and data integrity in a multi-master setup.
The problem I have is - we need to process & change(update/insert) 55M Data every 2 min and this updated data to be available for Rest API for Filtering / Selection. Response time for Rest API should be less than 1 sec.
The most important factors for me are processing and storing time of 2 min. There need to be 2 views of Data One is for Selection & 2. Changed data.
Scylla can handle 1M/s events with a simple data model quite easily. The api to query is CQL, we have REST api but that's for control/monitoring
i love syclla for pet projects however it's license which is based on server model is an issue. thus i recommend cassandra
Cassandra is quite capable of the task, in a highly available way, given appropriate scaling of the system. Remember that updates are only inserts, and that efficient retrieval is only by key (which can be a complex key). Talking of keys, make sure that the keys are well distributed.
By 55M do you mean 55 million entity changes per 2 minutes? It is relatively high, means almost 460k per second. If I had to choose between Scylla or Cassandra, I would opt for Scylla as it is promising better performance for simple operations. However, maybe it would be worth to consider yet another alternative technology. Take into consideration required consistency, reliability and high availability and you may realize that there are more suitable once. Rest API should not be the main driver, because you can always develop the API yourself, if not supported by given technology.
Pros of Cassandra
- Distributed119
- High performance98
- High availability81
- Easy scalability74
- Replication53
- Reliable26
- Multi datacenter deployments26
- Schema optional10
- OLTP9
- Open source8
- Workload separation (via MDC)2
- Fast1
Pros of Galera Cluster
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Cons of Cassandra
- Reliability of replication3
- Size1
- Updates1
Cons of Galera Cluster
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