Aerospike vs Kafka

Overview

Kafka

Stacks24.2K

Followers22.3K

Votes607

GitHub Stars31.2K

Forks14.8K

Aerospike

Stacks200

Followers288

Votes48

GitHub Stars1.3K

Forks196

Aerospike vs Kafka: What are the differences?

Introduction

Here is a comparison between Aerospike and Kafka, outlining their key differences in terms of functionality and usage.

Data Storage: Aerospike is a real-time NoSQL database that is designed for high-speed, low-latency data access. It is optimized for efficient data storage, retrieval, and processing. On the other hand, Kafka is a distributed streaming platform that is used for building real-time data pipelines and streaming applications. It provides fault-tolerant data storage and replication capabilities.
Data Processing: Aerospike provides a comprehensive set of data processing capabilities, including various data structures such as key-value, list, map, and sorted map. It also supports user-defined functions (UDFs) for complex data processing tasks. Kafka, on the other hand, focuses on data streaming and event processing. It allows for the real-time ingestion, processing, and delivery of high volumes of data streams.
Data Integration: Aerospike offers integration with various data storage systems, including Hadoop HDFS, Spark, and other databases. It provides connectors and APIs for seamless data integration and synchronization. Kafka, on the other hand, acts as a central data hub or backbone for data integration. It allows for data ingestion from various sources and enables data delivery to multiple target systems.
Data Scalability: Aerospike is designed to scale horizontally, allowing for the addition of more nodes to handle increasing data loads and user requests. It provides automatic data distribution and replication for high availability. Kafka, on the other hand, is built for horizontal scalability as well. It can handle large-scale data streaming and processing by distributing the data across multiple brokers.
Messaging Model: Aerospike focuses on persistent data storage and retrieval, providing support for various data models. It is not primarily designed for large-scale event streaming and message passing. Kafka, on the other hand, is specifically built for event-driven messaging. It provides a publish-subscribe model with high throughput and low latency, making it suitable for real-time streaming applications.
Data Durability: Aerospike ensures data durability through replication and high availability mechanisms. It provides synchronous replication and automatic failover to ensure data integrity and reliability. Kafka, on the other hand, provides fault-tolerance and durability by writing data to disk with configurable replication factors. It ensures data durability even in the event of hardware failures.

In summary, Aerospike is a real-time NoSQL database with comprehensive data processing capabilities and integrations, whereas Kafka is a distributed streaming platform designed for high-speed data streaming and processing.

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Manual

Advice on Kafka, Aerospike

viradiya

Apr 12, 2020

Needs adviceon

AngularJS

ASP.NET Core

MSSQL

We are going to develop a microservices-based application. It consists of AngularJS, ASP.NET Core, and MSSQL.

We have 3 types of microservices. Emailservice, Filemanagementservice, Filevalidationservice

I am a beginner in microservices. But I have read about RabbitMQ, but come to know that there are Redis and Kafka also in the market. So, I want to know which is best.

933k views933k

Comments

Kirill

GO/C developer at Duckling Sales

Feb 16, 2021

Decided

Maybe not an obvious comparison with Kafka, since Kafka is pretty different from rabbitmq. But for small service, Rabbit as a pubsub platform is super easy to use and pretty powerful. Kafka as an alternative was the original choice, but its really a kind of overkill for a small-medium service. Especially if you are not planning to use k8s, since pure docker deployment can be a pain because of networking setup. Google PubSub was another alternative, its actually pretty cheap, but I never tested it since Rabbit was matching really good for mailing/notification services.

266k views266k

Comments

Ishfaq

Feb 28, 2020

Needs advice

Our backend application is sending some external messages to a third party application at the end of each backend (CRUD) API call (from UI) and these external messages take too much extra time (message building, processing, then sent to the third party and log success/failure), UI application has no concern to these extra third party messages.

So currently we are sending these third party messages by creating a new child thread at end of each REST API call so UI application doesn't wait for these extra third party API calls.

I want to integrate Apache Kafka for these extra third party API calls, so I can also retry on failover third party API calls in a queue(currently third party messages are sending from multiple threads at the same time which uses too much processing and resources) and logging, etc.

Question 1: Is this a use case of a message broker?

Question 2: If it is then Kafka vs RabitMQ which is the better?

804k views804k

Comments

Detailed Comparison

Kafka	Aerospike
Kafka is a distributed, partitioned, replicated commit log service. It provides the functionality of a messaging system, but with a unique design.	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.
Written at LinkedIn in Scala;Used by LinkedIn to offload processing of all page and other views;Defaults to using persistence, uses OS disk cache for hot data (has higher throughput then any of the above having persistence enabled);Supports both on-line as off-line processing	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 31.2K	GitHub Stars 1.3K
GitHub Forks 14.8K	GitHub Forks 196
Stacks 24.2K	Stacks 200
Followers 22.3K	Followers 288
Votes 607	Votes 48
Pros & Cons
Pros 126 High-throughput 119 Distributed 92 Scalable 86 High-Performance 66 Durable Cons 32 Non-Java clients are second-class citizens 29 Needs Zookeeper 9 Operational difficulties 5 Terrible Packaging	Pros 16 Ram and/or ssd persistence 12 Easy clustering support 5 Easy setup 4 Acid 3 Performance better than Redis

What are some alternatives to Kafka, Aerospike?

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.

RabbitMQ

RabbitMQ gives your applications a common platform to send and receive messages, and your messages a safe place to live until received.

Celery

Celery is an asynchronous task queue/job queue based on distributed message passing. It is focused on real-time operation, but supports scheduling as well.

Amazon SQS

Transmit any volume of data, at any level of throughput, without losing messages or requiring other services to be always available. With SQS, you can offload the administrative burden of operating and scaling a highly available messaging cluster, while paying a low price for only what you use.

NSQ

NSQ is a realtime distributed messaging platform designed to operate at scale, handling billions of messages per day. It promotes distributed and decentralized topologies without single points of failure, enabling fault tolerance and high availability coupled with a reliable message delivery guarantee. See features & guarantees.

ActiveMQ

Apache ActiveMQ is fast, supports many Cross Language Clients and Protocols, comes with easy to use Enterprise Integration Patterns and many advanced features while fully supporting JMS 1.1 and J2EE 1.4. Apache ActiveMQ is released under the Apache 2.0 License.

ZeroMQ

The 0MQ lightweight messaging kernel is a library which extends the standard socket interfaces with features traditionally provided by specialised messaging middleware products. 0MQ sockets provide an abstraction of asynchronous message queues, multiple messaging patterns, message filtering (subscriptions), seamless access to multiple transport protocols and more.

Apache NiFi

An easy to use, powerful, and reliable system to process and distribute data. It supports powerful and scalable directed graphs of data routing, transformation, and system mediation logic.

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.

Gearman

Gearman allows you to do work in parallel, to load balance processing, and to call functions between languages. It can be used in a variety of applications, from high-availability web sites to the transport of database replication events.

Related Comparisons

Aerospike vs Kafka: What are the differences?

Introduction

Here is a comparison between Aerospike and Kafka, outlining their key differences in terms of functionality and usage.

Data Storage: Aerospike is a real-time NoSQL database that is designed for high-speed, low-latency data access. It is optimized for efficient data storage, retrieval, and processing. On the other hand, Kafka is a distributed streaming platform that is used for building real-time data pipelines and streaming applications. It provides fault-tolerant data storage and replication capabilities.
Data Processing: Aerospike provides a comprehensive set of data processing capabilities, including various data structures such as key-value, list, map, and sorted map. It also supports user-defined functions (UDFs) for complex data processing tasks. Kafka, on the other hand, focuses on data streaming and event processing. It allows for the real-time ingestion, processing, and delivery of high volumes of data streams.
Data Integration: Aerospike offers integration with various data storage systems, including Hadoop HDFS, Spark, and other databases. It provides connectors and APIs for seamless data integration and synchronization. Kafka, on the other hand, acts as a central data hub or backbone for data integration. It allows for data ingestion from various sources and enables data delivery to multiple target systems.
Data Scalability: Aerospike is designed to scale horizontally, allowing for the addition of more nodes to handle increasing data loads and user requests. It provides automatic data distribution and replication for high availability. Kafka, on the other hand, is built for horizontal scalability as well. It can handle large-scale data streaming and processing by distributing the data across multiple brokers.
Messaging Model: Aerospike focuses on persistent data storage and retrieval, providing support for various data models. It is not primarily designed for large-scale event streaming and message passing. Kafka, on the other hand, is specifically built for event-driven messaging. It provides a publish-subscribe model with high throughput and low latency, making it suitable for real-time streaming applications.
Data Durability: Aerospike ensures data durability through replication and high availability mechanisms. It provides synchronous replication and automatic failover to ensure data integrity and reliability. Kafka, on the other hand, provides fault-tolerance and durability by writing data to disk with configurable replication factors. It ensures data durability even in the event of hardware failures.

Aerospike vs Kafka

Overview

Aerospike vs Kafka: What are the differences?