StackShareStackShare
Follow on
StackShare

Discover and share technology stacks from companies around the world.

Follow on

© 2025 StackShare. All rights reserved.

Product

  • Stacks
  • Tools
  • Feed

Company

  • About
  • Contact

Legal

  • Privacy Policy
  • Terms of Service
  1. Stackups
  2. Application & Data
  3. In-Memory Databases
  4. In Memory Databases
  5. Pelikan Cache vs Redis

Pelikan Cache vs Redis

OverviewComparisonAlternatives

Overview

Redis
Redis
Stacks61.9K
Followers46.5K
Votes3.9K
GitHub Stars42
Forks6
Pelikan Cache
Pelikan Cache
Stacks2
Followers14
Votes0
GitHub Stars2.0K
Forks171

Pelikan Cache vs Redis: What are the differences?

Introduction

Pelikan Cache and Redis are both popular in-memory data storage systems used for caching and speeding up applications. While they share some similarities, there are key differences between the two.

  1. Data Structures: Pelikan Cache supports a limited set of data structures, such as strings, sets, and counters. Redis, on the other hand, offers a wide range of complex data structures including lists, sets, sorted sets, hashes, and more. This makes Redis a more versatile choice when it comes to storing and manipulating different types of data.

  2. Ease of Use: Pelikan Cache focuses on simplicity and ease of use with a minimalistic design. It provides a lightweight caching solution with a smaller codebase, making it easier to understand and maintain. In contrast, Redis is a robust and feature-rich data store with a larger codebase and extensive functionality. While Redis offers more advanced features, it may require more time to set up and manage.

  3. Performance: Pelikan Cache is designed for high-performance scenarios, optimized for low-latency and high-throughput workloads. It achieves this by minimizing memory traffic and providing a lockless architecture. Redis is also known for its excellent performance, but due to its extensive feature set, it may have slightly higher latency compared to Pelikan Cache in certain use cases.

  4. Persistence: Redis offers built-in data persistence, allowing data to be saved on disk and automatically reloaded on restart. This makes Redis suitable for scenarios where data durability is crucial. Pelikan Cache, on the other hand, is mainly focused on in-memory caching and does not provide native persistence capabilities. Data is lost if the cache restarts or crashes.

  5. Protocol Support: Pelikan Cache implements the Memcached protocol, which is widely supported by various client libraries and frameworks. Redis, on the other hand, has its own protocol, but it also supports the Memcached protocol through a compatibility layer. This makes Pelikan Cache a suitable choice if you want to leverage existing Memcached-based applications without modification.

  6. Community and Ecosystem: Redis has gained wide adoption and has a large and active community. It has a robust ecosystem with various client libraries, tools, and extensions. Pelikan Cache, being a relatively newer project, has a smaller community and ecosystem. While it is actively developed and supported, Redis offers a more mature and extensive set of resources.

In summary, Pelikan Cache provides a simpler and lightweight caching solution with high-performance characteristics, while Redis offers a more comprehensive and feature-rich data store with advanced data structures, persistence, and a larger ecosystem.

Share your Stack

Help developers discover the tools you use. Get visibility for your team's tech choices and contribute to the community's knowledge.

View Docs
CLI (Node.js)
or
Manual

Detailed Comparison

Redis
Redis
Pelikan Cache
Pelikan Cache

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.

Pelikan is a cache framework written in C. It provides an expanding collection of cache services, and a common library used to build them.

Statistics
GitHub Stars
42
GitHub Stars
2.0K
GitHub Forks
6
GitHub Forks
171
Stacks
61.9K
Stacks
2
Followers
46.5K
Followers
14
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

What are some alternatives to Redis, Pelikan Cache?

Hazelcast

Hazelcast

With its various distributed data structures, distributed caching capabilities, elastic nature, memcache support, integration with Spring and Hibernate and more importantly with so many happy users, Hazelcast is feature-rich, enterprise-ready and developer-friendly in-memory data grid solution.

Aerospike

Aerospike

Aerospike is an open-source, modern database built from the ground up to push the limits of flash storage, processors and networks. It was designed to operate with predictable low latency at high throughput with uncompromising reliability – both high availability and ACID guarantees.

MemSQL

MemSQL

MemSQL converges transactions and analytics for sub-second data processing and reporting. Real-time businesses can build robust applications on a simple and scalable infrastructure that complements and extends existing data pipelines.

Apache Ignite

Apache Ignite

It is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads delivering in-memory speeds at petabyte scale

SAP HANA

SAP HANA

It is an application that uses in-memory database technology that allows the processing of massive amounts of real-time data in a short time. The in-memory computing engine allows it to process data stored in RAM as opposed to reading it from a disk.

VoltDB

VoltDB

VoltDB is a fundamental redesign of the RDBMS that provides unparalleled performance and scalability on bare-metal, virtualized and cloud infrastructures. VoltDB is a modern in-memory architecture that supports both SQL + Java with data durability and fault tolerance.

Tarantool

Tarantool

It is designed to give you the flexibility, scalability, and performance that you want, as well as the reliability and manageability that you need in mission-critical applications

Azure Redis Cache

Azure Redis Cache

It perfectly complements Azure database services such as Cosmos DB. It provides a cost-effective solution to scale read and write throughput of your data tier. Store and share database query results, session states, static contents, and more using a common cache-aside pattern.

KeyDB

KeyDB

KeyDB is a fully open source database that aims to make use of all hardware resources. KeyDB makes it possible to breach boundaries often dictated by price and complexity.

LokiJS

LokiJS

LokiJS is a document oriented database written in javascript, published under MIT License. Its purpose is to store javascript objects as documents in a nosql fashion and retrieve them with a similar mechanism. Runs in node (including cordova/phonegap and node-webkit), nativescript and the browser.

Related Comparisons

Bootstrap
Materialize

Bootstrap vs Materialize

Laravel
Django

Django vs Laravel vs Node.js

Bootstrap
Foundation

Bootstrap vs Foundation vs Material UI

Node.js
Spring Boot

Node.js vs Spring-Boot

Liquibase
Flyway

Flyway vs Liquibase