tiedot
A rudimentary embedded NoSQL document database written in Go that stores JSON documents and provides HTTP API access.
What is tiedot?
tiedot is a basic NoSQL document database written in Go that stores data in JSON format. It can be embedded directly into Go applications or run as a standalone server with an HTTP API, providing a simple document storage solution with advanced query capabilities.
Go developers needing a lightweight embedded document database for applications requiring JSON storage without external database dependencies.
Developers choose tiedot for its simplicity, embeddability into Go programs, and reliable performance with fault-tolerant data structures, though the project notes it's minimal and dormant since 2016.
Overview
A rudimentary implementation of a basic document (NoSQL) database in Go
Use Cases
Best For
- Embedding a document database directly into Go applications
- Storing and querying JSON documents in Go projects
- Prototyping applications needing simple NoSQL storage
- Running a lightweight HTTP API document database server
- Educational purposes to understand document database internals
- Applications prioritizing data safety with fault-tolerant structures
Not Ideal For
- Production applications requiring active maintenance and security updates
- Systems needing modern NoSQL features like transactions or replication
- Projects with extensive integration requirements outside the Go ecosystem
- Teams needing comprehensive documentation and community support
Pros & Cons
Pros
Uses JSON document format for schema-less data storage, enabling flexible data models as highlighted in the key features.
Can be embedded directly into Go programs or run as a standalone HTTP server, offering deployment versatility without external dependencies.
Supports complex set operations for data retrieval, allowing sophisticated queries without needing external tools, as per the query processor description.
Employs fault-tolerant data structures that prioritize data integrity, ensuring reliability even with large datasets.
Capable of handling over 120k records or 80k complex queries per second, providing good performance for embedded use cases.
Cons
The project has been inactive since 2016 with no updates, making it unsuitable for evolving needs or security fixes, as warned in the README.
Lacks modern database functionalities such as ACID transactions or replication, which limits its use in production-critical applications.
Sparse third-party tools, libraries, and community contributions due to its dormant state, hindering integration and support.
Performance claims are from outdated benchmarks; real-world scaling beyond tested scenarios might be unreliable or untested.
Frequently Asked Questions
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