thoth

Simple Key-Value Database written in Go.

POC Releases

Base - POC Release 1

• DONE!
• Table
  • Create
  • List
• Commands
  • SET
  • GET
• Server
• Makefile:
  • run
  • test

Event Sourcing - POC Release 2

• In Development
• Event Sourcing (from Thoth to Pegasus)

Backlog

• InMemory DB Key Features (asked ChatGPT for it)

1. Memory Storage:

   • Data Storage in RAM: All data is stored in the system's main memory (RAM), enabling fast read and write operations.

2. Data Structures:

   • Support for Complex Data Structures: Provides a variety of data structures like strings, lists, sets, hashes, etc.

3. Caching:

   • Caching Mechanisms: Used as caching systems to store frequently accessed or computed data, reducing the load on backend databases.

4. Key-Value Storage:

   • Key-Value Store: Organized as a key-value store, associating each piece of data with a unique key for quick retrieval.

5. Atomic Operations:

   • Atomic Operations: Supports atomic operations, ensuring certain operations are executed as a single, indivisible unit.

6. Persistence Options:

   • Persistence Mechanisms: While primarily in-memory, some systems offer persistence options to store data on disk for recovery after system restarts.

7. Pub/Sub Messaging:

   • Publish/Subscribe Mechanism: Enables a publish/subscribe model for real-time communication between different components.

8. Scalability:

   • Horizontal Scalability: Can be scaled horizontally by adding more nodes to the cluster, distributing data and load across multiple instances.

9. High Throughput and Low Latency:

   • High Throughput: Designed to handle a large number of transactions per second.
   • Low Latency: Provides very low response times for data retrieval and updates.

10. Partitioning/Sharding:

    • Data Partitioning: Supports partitioning or sharding of data to distribute it across multiple nodes for improved performance and scalability.

11. Data Expiry/TTL:

    • Time-To-Live (TTL): Allows setting a time limit for how long data should be retained in memory, useful for caching scenarios.

12. Cluster Management:

    • Cluster Management: Provides tools for managing and monitoring clusters of in-memory database nodes.

13. Security:

    • Access Controls: Offers access controls and authentication mechanisms to secure the data.

14. Replication:

    • Data Replication: Supports data replication across nodes for fault tolerance and high availability.

15. Multi-Threaded Architecture:

    • Multi-Threaded Processing: Utilizes a multi-threaded architecture to efficiently handle concurrent requests.

16. Integration with Other Systems:

    • Integration Capabilities: Often integrates well with other systems and databases to complement existing data storage solutions.