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LevelDB vs UnQLite: What are the differences?

Introduction

LevelDB and UnQLite are both widely used embedded key-value databases that offer high performance and efficient data storage. However, there are several key differences between the two.

  1. Data Model: LevelDB is a key-value store, where each key is associated with a value. It allows efficient CRUD operations on individual key-value pairs. On the other hand, UnQLite is a document store, where data is stored in self-contained documents. These documents can have a hierarchical structure and support complex queries.

  2. Query Language: LevelDB does not have a built-in query language. It primarily focuses on simple key-value operations and does not provide advanced querying capabilities. UnQLite, on the other hand, supports a query language similar to SQL, allowing users to perform complex queries on the stored documents.

  3. Secondary Indexes: LevelDB does not support secondary indexes out of the box. To achieve efficient querying on non-primary keys, developers need to maintain additional data structures or use external indexing mechanisms. UnQLite, on the other hand, provides built-in support for secondary indexes, enabling efficient querying on various fields of the stored documents.

  4. Durability: LevelDB offers a transaction log-based write-ahead logging mechanism to ensure durability. It ensures that data modifications are written to disk before acknowledging a commit. UnQLite, on the other hand, uses an append-only persistence model, where changes are continuously appended to the database file. This approach provides better write performance but may not offer the same level of durability as LevelDB.

  5. Concurrency Control: LevelDB uses a single-writer multiple-reader model, allowing concurrent reads but only sequential writes. It ensures data consistency by implementing a single-writer lock mechanism. UnQLite, on the other hand, does not support concurrent writes by default. It enforces a locking mechanism, where only one thread can write to the database at a time. However, concurrent reads are still possible.

  6. Embeddability: LevelDB is a standalone library that can be easily embedded into applications written in various programming languages. It provides a simple and lightweight API making it suitable for embedding in resource-constrained devices or applications. UnQLite, on the other hand, is a self-contained C library that includes both the database engine and a built-in document store. It offers a more comprehensive and feature-rich solution but may have a larger footprint.

In summary, LevelDB is a lightweight key-value store with no built-in query language or secondary indexes. It focuses on simplicity and performance, making it a suitable choice for simple key-value use cases. On the other hand, UnQLite is a feature-rich document store with a built-in query language and support for secondary indexes. It provides more advanced querying capabilities, at the cost of increased complexity and potentially larger resource footprint.

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    What is LevelDB?

    It is a fast key-value storage library written at Google that provides an ordered mapping from string keys to string values. It has been ported to a variety of Unix-based systems, macOS, Windows, and Android.

    What is UnQLite?

    UnQLite is a in-process software library which implements a self-contained, serverless, zero-configuration, transactional NoSQL database engine. UnQLite is a document store database similar to MongoDB, Redis, CouchDB etc. as well a standard Key/Value store similar to BerkeleyDB, LevelDB, etc.

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    What companies use LevelDB?
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      What tools integrate with LevelDB?
      What tools integrate with UnQLite?

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      What are some alternatives to LevelDB and UnQLite?
      MongoDB
      MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.
      Redis
      Redis is an open source (BSD licensed), in-memory data structure store, used as a database, cache, and message broker. Redis provides data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes, and streams.
      Symas LMDB
      It is an extraordinarily fast, memory-efficient database which is developed for the OpenLDAP Project. With memory-mapped files, it has the read performance of a pure in-memory database while retaining the persistence of standard disk-based databases.
      Badger
      Domain management you'll enjoy. Domains effectively drive the entire internet, shouldn't they be easier to manage? We thought so, and thus, Badger was born! You shouldn't have to auction off your house and sacrifice your first born to transfer domains, you should be able to press a button that says "Transfer Domain" and be done with it. That is our philosophy, and we think you will appreciate it. Stop letting domain registrars badger you, and start using... Badger!
      RocksDB
      RocksDB is an embeddable persistent key-value store for fast storage. RocksDB can also be the foundation for a client-server database but our current focus is on embedded workloads. RocksDB builds on LevelDB to be scalable to run on servers with many CPU cores, to efficiently use fast storage, to support IO-bound, in-memory and write-once workloads, and to be flexible to allow for innovation.
      See all alternatives