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  1. Stackups
  2. Application & Data
  3. In-Memory Databases
  4. In Memory Databases
  5. LevelDB vs Redis

LevelDB vs Redis

OverviewComparisonAlternatives

Overview

Redis
Redis
Stacks61.9K
Followers46.5K
Votes3.9K
GitHub Stars42
Forks6
LevelDB
LevelDB
Stacks108
Followers111
Votes0
GitHub Stars38.3K
Forks8.1K

LevelDB vs Redis: What are the differences?

Key Differences between LevelDB and Redis

Introduction

LevelDB and Redis are both popular key-value store database systems. While they share some similarities, they also differ in several key aspects. In this article, we will explore the main differences between LevelDB and Redis.

  1. Data Structures: LevelDB stores data in a simple key-value format, where both keys and values are arbitrary byte arrays. On the other hand, Redis supports a rich set of data structures, including strings, lists, sets, sorted sets, and hashes. This makes Redis more versatile for storing and manipulating different types of data.

  2. Persistence: LevelDB is designed for persistent storage and data durability. It maintains an on-disk log and provides options to periodically write data to disk, ensuring data integrity even in the event of a crash. In contrast, Redis primarily emphasizes speed and in-memory performance. By default, Redis stores data primarily in memory and provides optional persistence mechanisms such as periodic snapshots or append-only logs.

  3. Scalability: LevelDB is optimized for single-machine use and is not designed to scale horizontally across multiple nodes. It is suitable for scenarios where the data size is manageable for a single machine. Redis, on the other hand, is built with scalability in mind. It supports clustering, replication, and sharding, enabling the distribution of data across multiple nodes for high availability and performance.

  4. Primary Use Case: LevelDB is commonly used as an embedded database in various applications or as the underlying storage engine for other systems. It provides a lightweight and low-level storage solution. Redis, on the other hand, is often used as a caching and messaging system, allowing fast data retrieval from memory and supporting pub/sub messaging patterns.

  5. Complexity: LevelDB is relatively simple and straightforward, with fewer features and a more basic API. It provides a basic set of operations such as get, put, and delete for key-value pairs. Redis, on the other hand, offers a more feature-rich and complex set of operations, including powerful querying, manipulation, and pipeline capabilities.

  6. Language Support and Client Libraries: LevelDB is implemented primarily in C++ and has client libraries available for various programming languages. Redis, on the other hand, supports a wide range of programming languages with extensive client libraries and bindings, making it accessible from many different development environments.

In summary, LevelDB is a lightweight, single-machine focused, and simplicity-oriented embedded database system with persistent storage capabilities. Redis, on the other hand, is a feature-rich and scalable key-value store, optimized for speed and in-memory performance, with extensive data structure support and distributed clustering capabilities.

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Detailed Comparison

Redis
Redis
LevelDB
LevelDB

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.

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.

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Simple key-value stores with Go, C++, Node.js and more!
Statistics
GitHub Stars
42
GitHub Stars
38.3K
GitHub Forks
6
GitHub Forks
8.1K
Stacks
61.9K
Stacks
108
Followers
46.5K
Followers
111
Votes
3.9K
Votes
0
Pros & Cons
Pros
  • 888
    Performance
  • 542
    Super fast
  • 514
    Ease of use
  • 444
    In-memory cache
  • 324
    Advanced key-value cache
Cons
  • 15
    Cannot query objects directly
  • 3
    No secondary indexes for non-numeric data types
  • 1
    No WAL
No community feedback yet
Integrations
No integrations available
Java
Java
Windows
Windows
macOS
macOS

What are some alternatives to Redis, LevelDB?

MongoDB

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

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

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

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

SQLite

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

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

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

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

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

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.

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