A REST-based service that abstracts storage complexity and automates common data access patterns across multiple database systems.
Staash is a REST-based service that provides a unified interface for accessing multiple database systems like Cassandra and MySQL. It abstracts storage complexity through a metadata layer and automates common data access patterns, allowing developers to interact with different databases without dealing with their specific details.
Application developers working with multiple database technologies who want to simplify data access and avoid wrestling with storage-specific complexities.
Developers choose Staash because it provides a language-agnostic, storage-agnostic interface that hides database implementation details and automates repetitive data access patterns, reducing development complexity.
A language-agnostic as well as storage-agnostic web interface for storing data into persistent storage systems, the metadata layer abstracts a lot of storage details and the pattern automation APIs take care of automating common data access patterns.
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Models data in relational terms to simplify interaction with NoSQL stores like Cassandra, as stated in the README's aim to hide complexity behind relational concepts.
Provides high-level REST APIs for both Cassandra and MySQL, shielding developers from connection details and storage-specific quirks, as highlighted in the key features.
Enables joining datasets across different storage systems, a unique feature mentioned in the README for handling complex data landscapes.
Offers auto-sharding for temporal data in event-series, useful for time-based data handling, though some parts are still in development.
Currently only implements Cassandra and MySQL, with MySQL described as 'just for proof' in the README, restricting its utility for other databases.
Key features like the key-value store API and event-series are marked 'in progress' or 'in development' in the README, indicating instability and incomplete functionality.
As a first release used limitedly within Netflix per the README, it lacks production hardening, extensive documentation, and community resources outside that environment.