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

Aerospike vs Redis

OverviewComparisonAlternatives

Overview

Redis
Redis
Stacks61.9K
Followers46.5K
Votes3.9K
GitHub Stars42
Forks6
Aerospike
Aerospike
Stacks200
Followers288
Votes48
GitHub Stars1.3K
Forks196

Aerospike vs Redis: What are the differences?

Introduction

In this article, we will discuss the key differences between Aerospike and Redis. Both Aerospike and Redis are highly popular databases used for different purposes. Understanding their differences will help in choosing the most suitable option for specific use cases.

  1. Data Structure: Aerospike is a key-value store that supports the storage of complex serialized data structures, such as lists and maps, within a single value. On the other hand, Redis is an in-memory data structure store that supports various data structures, including strings, hashes, sets, lists, and more.

  2. Data Persistence: Aerospike supports both in-memory and durable storage options. It can persist data on disk and provide high availability even in the event of a node failure. Redis primarily focuses on in-memory storage but provides the ability to persist data to disk asynchronously or synchronously using different persistence options.

  3. Scalability: Aerospike is designed to scale horizontally and can distribute data across multiple nodes in a cluster seamlessly. Redis, on the other hand, was initially designed to be a single-threaded, in-memory database, but can also be clustered to achieve scalability by sharding data across multiple nodes.

  4. Performance: Aerospike is built with performance and low-latency in mind and is able to handle high throughput workloads efficiently. Redis is also known for its high performance and low latency, especially for read-heavy workloads, due to keeping the data in memory.

  5. Replication: Aerospike uses a strong consistency model for replication, ensuring that data is replicated synchronously across multiple nodes. Redis supports both asynchronous and synchronous replication, allowing flexibility in choosing the replication strategy based on specific use cases.

  6. Advanced Data Types: Redis offers a rich set of advanced data types and operations on those types, such as sorted sets, hyperloglogs, and bitmap operations. Aerospike, while also supporting complex data structures, does not have as extensive support for advanced data types as Redis.

In summary, Aerospike and Redis differ in terms of their supported data structure, data persistence options, scalability, performance, replication strategy, and support for advanced data types. Understanding these differences will help in choosing the appropriate database for specific use cases.

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Detailed Comparison

Redis
Redis
Aerospike
Aerospike

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.

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.

-
99% of reads/writes complete in under 1 millisecond.;Predictable low latency at high throughput – second to none. Read the YCSB Benchmark.;The secret sauce? A thousand things done right. Server code in ‘C’ (not Java or Erlang) precisely tuned to avoid context switching and memory copies. Highly parallelized multi-threaded, multi-core, multi-cpu, multi-SSD execution.;Indexes are always stored in RAM. Pure RAM mode is backed by spinning disks. In hybrid mode, individual tables are stored in either RAM or flash.
Statistics
GitHub Stars
42
GitHub Stars
1.3K
GitHub Forks
6
GitHub Forks
196
Stacks
61.9K
Stacks
200
Followers
46.5K
Followers
288
Votes
3.9K
Votes
48
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
Pros
  • 16
    Ram and/or ssd persistence
  • 12
    Easy clustering support
  • 5
    Easy setup
  • 4
    Acid
  • 3
    Petabyte Scale

What are some alternatives to Redis, Aerospike?

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.

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.

BuntDB

BuntDB

BuntDB is a low-level, in-memory, key/value store in pure Go. It persists to disk, is ACID compliant, and uses locking for multiple readers and a single writer. It supports custom indexes and geospatial data. It's ideal for projects that need a dependable database and favor speed over data size.

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