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  1. Stackups
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  3. Background Jobs
  4. Message Queue
  5. DistributedLog vs Scheduler API

DistributedLog vs Scheduler API

OverviewComparisonAlternatives

Overview

DistributedLog
DistributedLog
Stacks21
Followers39
Votes0
Scheduler API
Scheduler API
Stacks5
Followers16
Votes0

DistributedLog vs Scheduler API: What are the differences?

Developers describe DistributedLog as "High-performance replicated log service, by Twitter". DistributedLog (DL) is a high-performance, replicated log service, offering durability, replication and strong consistency as essentials for building reliable distributed systems. On the other hand, Scheduler API is detailed as "An API for scheduling queue messages". It is a simple API to delay SQS messages. Call our APIs and we'll publish your messages when you need them.

DistributedLog and Scheduler API belong to "Message Queue" category of the tech stack.

Some of the features offered by DistributedLog are:

  • High Performance
  • Durable and Consistent
  • Efficient Fan-in and Fan-out

On the other hand, Scheduler API provides the following key features:

  • scheduling
  • cancelling scheduled SQS messages
  • changing the delay for already scheduled messages

DistributedLog is an open source tool with 2.27K GitHub stars and 290 GitHub forks. Here's a link to DistributedLog's open source repository on GitHub.

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Detailed Comparison

DistributedLog
DistributedLog
Scheduler API
Scheduler API

DistributedLog (DL) is a high-performance, replicated log service, offering durability, replication and strong consistency as essentials for building reliable distributed systems.

It is a simple API to delay SQS messages. Call our APIs and we'll publish your messages when you need them.

High Performance;Durable and Consistent;Efficient Fan-in and Fan-out;Various Workloads;Multi Tenant;Layered Architecture
scheduling ; cancelling scheduled SQS messages; changing the delay for already scheduled messages; checking the status of scheduled messages
Statistics
Stacks
21
Stacks
5
Followers
39
Followers
16
Votes
0
Votes
0

What are some alternatives to DistributedLog, Scheduler API?

Kafka

Kafka

Kafka is a distributed, partitioned, replicated commit log service. It provides the functionality of a messaging system, but with a unique design.

RabbitMQ

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

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

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

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

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

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

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.

Gearman

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.

Memphis

Memphis

Highly scalable and effortless data streaming platform. Made to enable developers and data teams to collaborate and build real-time and streaming apps fast.

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