FaunaDB vs LevelDB

Overview

LevelDB

Stacks108

Followers111

Votes0

GitHub Stars38.3K

Forks8.1K

Fauna

Stacks112

Followers153

Votes27

FaunaDB vs LevelDB: What are the differences?

FaunaDB and LevelDB are both popular databases but have key differences in their functionality and use cases. Below are the main differences between FaunaDB and LevelDB.

Query Language Support: FaunaDB provides a query language called FQL (Fauna Query Language), which allows for complex nested multi-document queries, whereas LevelDB does not have built-in query language support, requiring developers to implement their query logic programmatically.
Consistency Mechanisms: FaunaDB offers ACID transactions, strong consistency guarantees, and global distribution capabilities, making it suitable for applications requiring high consistency and data integrity. In contrast, LevelDB is a key-value store that lacks built-in transaction support and does not provide the same level of consistency guarantees as FaunaDB.
Scalability: FaunaDB is designed for horizontal scalability and can automatically distribute data across multiple servers, making it well-suited for applications with rapidly growing data needs. LevelDB, on the other hand, is a single-server database and does not have built-in mechanisms for seamless horizontal scalability.
Data Modeling: FaunaDB allows for flexible data modeling with support for nested data structures, relationships, and indexes, making it suitable for applications with complex data requirements. LevelDB, being a key-value store, is more limited in terms of data modeling capabilities and is better suited for simple key-value data storage and retrieval.
Multi-tenancy Support: FaunaDB offers built-in support for multi-tenancy, allowing applications to securely isolate data for different tenants within the same database instance. LevelDB does not have native support for multi-tenancy and does not provide mechanisms for easily managing data isolation between different tenants.
Ecosystem and Integration: FaunaDB has a rich ecosystem with client libraries for different programming languages, built-in support for GraphQL, and integrations with popular application development frameworks. LevelDB, being a lightweight embedded database, may have limited ecosystem support compared to FaunaDB, especially in terms of integrations with modern web and cloud-based technologies.

In Summary, FaunaDB and LevelDB differ significantly in terms of query language support, consistency mechanisms, scalability, data modeling capabilities, multi-tenancy support, and ecosystem integrations.

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CLI (Node.js)

Manual

Detailed Comparison

LevelDB	Fauna
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.	Escape the boundaries imposed by legacy databases with a data API that is simple to adopt, highly productive to use, and offers the capabilities that your business needs, without the operational pain typically associated with databases.
Simple key-value stores with Go, C++, Node.js and more!	Native support for GraphQL and others. Easily access any data with any API. No middleware necessary.; Access all data via a data model that best suits your needs - relational, document, graph or composite.; A unique approach to indexing makes it simpler to write efficient queries that scale with your application.; Build SaaS apps more easily with native multi-tenancy and query-level QoS controls to prevent workload collisions.; Eliminate data anomalies with multi-region ACID transactions that don't limit number of keys or documents.; Data-driven RBAC that combines with SSL to offers reliable protection, and yet is simple to understand and codify.; Travel back in time with temporal querying. Run queries at a point-in-time or as change feeds. Track how your data evolved.; Dynamically replicates your data to global locations, so that your queries run fast no matter where your users are.; Easily deploy a FaunaDB cluster on your workstation accompanied by a powerful shell and tools to simplify your workflow.;
Statistics
GitHub Stars 38.3K	GitHub Stars -
GitHub Forks 8.1K	GitHub Forks -
Stacks 108	Stacks 112
Followers 111	Followers 153
Votes 0	Votes 27
Pros & Cons
No community feedback yet	Pros 5 100% ACID 4 Generous free tier 4 Removes server provisioning or maintenance 3 No more n+1 problems (+ GraphQL) 3 Low latency global CDN's Cons 1 Log stack traces to avoid improper exception handling 1 Must keep app secrets encrypted 1 Susceptible to DDoS (& others) use timeouts throttling
Integrations
Java Windows macOS	No integrations available

What are some alternatives to LevelDB, Fauna?

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.

MySQL

The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.

PostgreSQL

PostgreSQL is an advanced object-relational database management system that supports an extended subset of the SQL standard, including transactions, foreign keys, subqueries, triggers, user-defined types and functions.

Microsoft SQL Server

Microsoft® SQL Server is a database management and analysis system for e-commerce, line-of-business, and data warehousing solutions.

SQLite

SQLite is an embedded SQL database engine. Unlike most other SQL databases, SQLite does not have a separate server process. SQLite reads and writes directly to ordinary disk files. A complete SQL database with multiple tables, indices, triggers, and views, is contained in a single disk file.

Cassandra

Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.

Memcached

Memcached is an in-memory key-value store for small chunks of arbitrary data (strings, objects) from results of database calls, API calls, or page rendering.

MariaDB

Started by core members of the original MySQL team, MariaDB actively works with outside developers to deliver the most featureful, stable, and sanely licensed open SQL server in the industry. MariaDB is designed as a drop-in replacement of MySQL(R) with more features, new storage engines, fewer bugs, and better performance.

RethinkDB

RethinkDB is built to store JSON documents, and scale to multiple machines with very little effort. It has a pleasant query language that supports really useful queries like table joins and group by, and is easy to setup and learn.

ArangoDB

A distributed free and open-source database with a flexible data model for documents, graphs, and key-values. Build high performance applications using a convenient SQL-like query language or JavaScript extensions.

Related Comparisons

FaunaDB vs LevelDB: What are the differences?

FaunaDB and LevelDB are both popular databases but have key differences in their functionality and use cases. Below are the main differences between FaunaDB and LevelDB.

Query Language Support: FaunaDB provides a query language called FQL (Fauna Query Language), which allows for complex nested multi-document queries, whereas LevelDB does not have built-in query language support, requiring developers to implement their query logic programmatically.
Consistency Mechanisms: FaunaDB offers ACID transactions, strong consistency guarantees, and global distribution capabilities, making it suitable for applications requiring high consistency and data integrity. In contrast, LevelDB is a key-value store that lacks built-in transaction support and does not provide the same level of consistency guarantees as FaunaDB.
Scalability: FaunaDB is designed for horizontal scalability and can automatically distribute data across multiple servers, making it well-suited for applications with rapidly growing data needs. LevelDB, on the other hand, is a single-server database and does not have built-in mechanisms for seamless horizontal scalability.
Data Modeling: FaunaDB allows for flexible data modeling with support for nested data structures, relationships, and indexes, making it suitable for applications with complex data requirements. LevelDB, being a key-value store, is more limited in terms of data modeling capabilities and is better suited for simple key-value data storage and retrieval.
Multi-tenancy Support: FaunaDB offers built-in support for multi-tenancy, allowing applications to securely isolate data for different tenants within the same database instance. LevelDB does not have native support for multi-tenancy and does not provide mechanisms for easily managing data isolation between different tenants.
Ecosystem and Integration: FaunaDB has a rich ecosystem with client libraries for different programming languages, built-in support for GraphQL, and integrations with popular application development frameworks. LevelDB, being a lightweight embedded database, may have limited ecosystem support compared to FaunaDB, especially in terms of integrations with modern web and cloud-based technologies.

FaunaDB vs LevelDB

Overview