PumpkinDB vs Scylla: What are the differences?
Introduction
Here are key differences between PumpkinDB and Scylla:
- Data Model: PumpkinDB is a log-structured database that stores data as a sequence of immutable events, while Scylla is a highly available and partition-tolerant NoSQL database that uses a shared-nothing architecture.
- Consistency Model: Scylla supports tunable consistency levels for reads and writes, allowing users to choose between strong and eventual consistency, whereas PumpkinDB provides strong eventual consistency by design.
- Programming Language: PumpkinDB uses a custom programming language called PumpkiScript for interacting with the database, which is a functional language specifically designed for data manipulation, whereas Scylla supports various programming languages through its drivers such as C++, Java, and Python.
- Deployment: Scylla is designed to be deployed on distributed systems and can scale horizontally by adding more nodes to the cluster, whereas PumpkinDB is typically deployed on a single node due to its log-structured nature.
- Use Cases: Scylla is mainly suited for real-time big data applications that require low latency and high throughput, while PumpkinDB is more suitable for event sourcing, event logging, and audit trail use cases.
- Community Support: Scylla has an active community with regular updates and contributions from various organizations, while PumpkinDB has a smaller community and may have limited resources for support and development.
In Summary, PumpkinDB and Scylla differ in their data models, consistency models, programming languages, deployment options, use cases, and community support.