Skip to content
master
Go to file
Code

Files

Permalink
Failed to load latest commit information.
Type
Name
Latest commit message
Commit time
Aug 8, 2020

readme.md

Awesome

If you appreciate the content 📖, support projects visibility, give 👍| | 👏

A curated list of awesome System Designing articles, videos and resources for distributed computing, AKA Big Data.

Whether you're preparing for an interview or you want to design a distributed/microservice oriented application, this list will definitely help you achieve that.

Attention: Stars on GitHub does not reflect usage or popularity for every item here listed.

Inspired By Awesome-BigData

Started By Gabriel Leon de Mattos

Contents

Articles

Books

Videos

Tools

Bonus

Articles

Introduction / Interviews

Advanced


Books


Videos

A collection of videos based on distributed systems.

Introduction / Interviews

Advanced

Tools

  • A collection of most commonly used tools for distributed systems

Relational Database Management System

  • MariaDB - MariaDB is a fork of MySQL server.

  • MySQL - Widely used relational database.

  • PostgresSQL - Relational database that has been gaining popularity.

  • SQLite - Another widely used database that is built into all mobile phones and most computers.

  • Sql Server - Widely used relational database.

NoSQL

Cache (Key-Value)

  • Apache Ignite - [3.3k ] - In memory caching with ACID properties.

  • Couchbase - Inspired by memcached, adding features such as replication and persistance.

  • Oracle Coherence - [126 ] - High scaling, low latency in-memory caching.

  • Memcached - [10.2k ] - One of the first in-memory caching database, high performing and multi-threaded.

  • Redis - [44k ] - Widely used in-memory caching database with many added features such as persistent storage and supporting strings, lists, sets, hashses, streams, bitmaps, etc.

Store (Key-Value)

  • Apple FoundationDB - [10k ] - Multi-model (many data types in a single database), ACID key-value store. Easily scalable and fault tolerant.

  • Cosmos DB - Microsoft's globally distributed, multi-model database service. Eastically and independently scale throughput and storage. SQL, MongoDB, Cassandra, Tables, Gremlin, and Spark APIs.

Document Store

  • CouchDB - [4.6k ] - ACID compliant NoSQL document-store DB, provides a RESTful HTTP API for reading and updating database documents.

  • MongoDB - One of the most popular 'NoSQL' database for general purpose.

  • RethinkDB - [23.8k ] - Document-store DB.

  • ElasticSearch - [49.9k ] - Widely popular 'NoSQL' database for fast and scalable search engines.

  • Cosmos DB - Microsoft's globally distributed, multi-model database service. Eastically and independently scale throughput and storage. SQL, MongoDB, Cassandra, Tables, Gremlin, and Spark APIs.

Wide Column Store

  • Amazon DynamoDB - Key-Value and Document database, highly performant, scalable and secure.

  • Google Bigtable - Scalable and performant 'NoSQL' database for large analytical and operational workload.

  • Cassandra - Facebook-born project very fast, easily scalable, with option to include consistency with each operation.

  • Scylla - [4.9k ] - 'NoSQL' data store using seastar framework, compatible with Cassandra.

  • HBase - [3.6k ] - Modeled after Google's Bigtable and written in Java. Developed as a part of Apache Hadoop project and runs on top of HDFS or Alluxio. (See Hadoop Related)

  • Cosmos DB - Microsoft's globally distributed, multi-model database service. Eastically and independently scale throughput and storage. SQL, MongoDB, Cassandra, Tables, Gremlin, and Spark APIs.

Graph

  • Amazon Neptune - Fast, reliable and fully managed graph database service.

  • ArangoDB - [10k ] - Flexible database for documents, key-value, graphs. Uses its own query language, AQL.

  • Neo4j - [7.9k ] - Good support for a graph db, ACID compliant and flexible.

  • Cosmos DB - Microsoft's globally distributed, multi-model database service. Eastically and independently scale throughput and storage. SQL, MongoDB, Cassandra, Tables, Gremlin, and Spark APIs.

Distributed File Systems

  • HDFS - Hadoop File System is a a widely popular choice among its big data competitors, providing high throughput access.

  • Lustre - File system for computer clusters.

  • CephFS - Unified, distributed storage system.

  • GlusterFS - Scale-out NAS file system.

  • MooseFS - POSIX-compliant distributed file system.

  • XtreemFS - Fault tolerant file system.

Resource Management

  • Kubernetes - Highly popular way to deploy, manage and automatically scale a cluster of containers on bare-metal or virtual servers.

Stream Processing

  • Apache Samza - Build stateful applications that process data in real time from multiple sources, including Kafka. Easy and inexpensive multi-subscriber model, can eliminate backpressure and has reliable persistency with low latency.

  • Apache Flink - Based on the concept of streams and transofrmations. Uses maven, handles batch tasks as data streams with finite boundaries. Low latency, high throughput.

  • Amazon Kinesis Streams - Durable, scalable, real-tme service. Collects gigabytes of data per second from hundreds of thousands of sources, including database event streams, website clickstreams, financial transactions, etc.

  • Azure Stream Analytics - Real-time analytics service that is designed for mission-critical workloads.

Message Broker

  • Amazon MQ - Open source message broker from Amazon.

  • Apache ActiveMQ - It's a multi-protocol, java based messaging server.

  • Apache Kafka - Widely popular message broker with low latency for data streaming.

  • RabbitMQ - Widely popular lightweight message broker written in erlang that also supports multiple messaging protocols.

  • IronMQ - Very fast and highly scalable messaging broker. (not open source)

  • Apache Pulsar - Created by yahoo, also highly scalable, low latency, geo-replication and multi-tenacy.

  • Kestrel - Written in Scala and speaks the memcached protocol. It works much like Kafka.

  • Azure Service Bus - A fully managed enterprise integration message broker.

Load Balancers

Open Source Software

  • SeeSaw - [5.1k ] - Used by Google, developed in Go, linux-based virtual load balancer server.

  • HAProxy - Widely popular option, provides high-availability, proxy, TCP/HTTP load balancing. Used by Reddit, Imgur, MaxCDN, GitHub, AirBNB.

  • Zevenet - Supports L3, L4 and L7. Easy install with a docker repo. Supports advanced health-check monitorining.

  • Neutrino - Used by eBay, built with Scala and Netty. Supports round-robin and least-connection algorithms.

  • Nginx - Wait, isn't Nginx a web server? Yes, the open source does support basic level of content switching and request routing. Plus edition supports load balancing, WAF, monitoring, etc.

Hardware

  • F5 - Robust hardware load balancer option, supporting multiple protocols (IP, TCP, FTP, UDP, HTTP).

  • TP-Link - Cheaper alternative that works as a load balancer.

  • Barracuda - One of the top choices for load balancing when it comes to in-house servers. Top security measures built in, comprehensive reports and monitoring outbound traffic for data loss prevention.

Cloud

  • Amazon Elastic Load Balancing - Popular choice for amazon customers, supports lambda functions, highly scalable.

  • Google Load Balancing - Popular choice for google customers, comes with auto-scaling feature, very fast, has intergrated CDN.

  • Cloudflare Load Balancing - Scalable load balancing by Cloudflare, feature fast failover and a dashboard.

  • DigitalOcean Load Balancing - If you're a digitalocean customer, this is a good option, very cheap, regional availability, scalable, easy to deploy among your other droplets.

  • Azure Load Balancing - Popular choice for Microsoft's Azure customers. Supports internal and external traffics, ipv6, monitorining and the standard load balancing set of features.

Hadoop Ecosystem

Dashboard

  • Ambari - Dashboard that integrates most of hadoop related technologies for easy management and executions.

Data Ingestion

  • Sqoop - Efficiently transfer data between Hadoop and structured datastores such as relational databases.

  • Flume - Distributed, highly available and efficient in collecting, aggregating and moving large amounts of log data.

  • Apache Kafka - Widely popular message broker with low latency for data streaming.

Workflow Scheduler

  • Oozie - Create workflows in xml to execute jobs (from other hadoop-ecosystem applications) in steps, allows for parallel execution as well.

Query

  • Hive - Query hadoop stored data in SQL.
  • Pig - Scriping language that looks like SQL to query hadoop data.

Processing

  • Tez - Solves a similar problem to Spark and MapReduce, it's more efficient than MapReduce because it calculates the most efficient way of doing it.
  • Map Reduce - MapReduce, as the name implies, maps data and reduce the results.
  • Spark - Powerful data processing to not only process data like Tez (and MapReduce), it can process streams of data in real time, apply regression analysis algorithms in ML and much more.
  • Apex - *Retired project, it's a YARN-native platform that unifies stream and batch processing.

DB

  • HBase - [3.6k ] - Modeled after Google's Bigtable and written in Java. Developed as a part of Apache Hadoop project.

Resource Management

  • YARN - 'Yet Another Resource Negotiator', works like a kernel to manage computer resources across the clusters.
  • MESOS - Works like a Linux Kernel by managing CPU, memory, storage and other resources across the cluster.

REST Framework

  • Gin - [40.6k ] - Blazingly fast microservice framework using Golang, high throughput capacity.

  • Phoenix - [15.5k ] - Distributed processing, easily scalable, support for channels and live chat. This framework - written in Elixir, uses BEAM and Erlang, very efficient for large scale systems and supports high throughput.

  • Express.js - [49.6k ] - Fast node.js rest api that can perform well under many scenarios.

  • Rails - [46.2k ] - Written in Ruby, Rails delivers quick apis from prototype to production in an efficient manner.

  • Play Framework - [11.6k ] - Very fast, high throughput framework written in Scala/Java that is RESTful by default.

  • Flask - [51.6k ] - A lightweight Python Microframework for fast prototyping and production.

  • Django REST - [18.4k ] - Written in Python, Django Rest is a powerful and flexible REST API. The efficiency and time to market resembles Rails.

  • ASP.NET Core MVC - A rich framework for building web apps and APIs using the Model-View-Controller design pattern in C# or F#. Number 6 on TechEmpower Composite Benchmarks for web frameworks.

You can’t perform that action at this time.