Redis is an open source (BSD licensed), in-memory data structure store, used as a database, cache and message broker. It supports data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs and geospatial indexes with radius queries.
You can run atomic operations on these types, like appending to a string; incrementing the value in a hash; pushing an element to a list; computing set intersection, union and difference; or getting the member with highest ranking in a sorted set.
Features
Transactions
Pub/Sub
Lua scripting
Keys with a limited time-to-live
LRU eviction of keys
Automatic failover
Redis is written in ANSI C and works in most POSIX systems like Linux, *BSD, OS X without external dependencies. Linux and OS X are the two operating systems where Redis is developed and more tested, and we recommend using Linux for deploying. Redis may work in Solaris-derived systems like SmartOS, but the support is best effort. There is no official support for Windows builds, but Microsoft develops and maintains a Win-64 port of Redis.
Neo4j is a graph database management system developed by Neo Technology, Inc. Described by its developers as an ACID-compliant transactional database with native graph storage and processing, Neo4j is the most popular graph database according to db-engines.com.
Neo4j is an open-source NoSQL graph database implemented in Java and Scala. With development starting in 2003, it has been publicly available since 2007
Neo4j is used today by hundreds of thousands of companies and organizations in almost all industries. Use cases include matchmaking, network management, software analytics, scientific research, routing, organizational and project management, recommendations, social networks, and more.
Neo4j implements the Property Graph Model efficiently down to the storage level. As opposed to graph processing or in-memory libraries, Neo4j provides full database characteristics including ACID transaction compliance, cluster support, and runtime failover, making it suitable to use graph data in production scenarios.
Druid is a column-oriented, open-source, distributed data store written in Java. Druid is designed to quickly ingest massive quantities of event data, and provide low-latency queries on top of the data.
Druid is a high-performance, column-oriented, distributed data store.
Benefits:
Interactive Queries
Real-time Streams
Horizontally Scalable
Deploy Anywhere
Vibrant Community
It is primarily used for business intelligence (OLAP) queries on event data. Druid provides low latency (real-time) data ingestion, flexible data exploration, and fast data aggregation. Existing Druid deployments have scaled to trillions of events and petabytes of data. Druid is most commonly used to power user-facing analytic applications.
MongoDB is an open-source database used by companies of all sizes, across all industries and for a wide variety of applications. It is an agile database that allows schemas to change quickly as applications evolve, while still providing the functionality developers expect from traditional databases, such as secondary indexes, a full query language and strict consistency.
MongoDB is a document database that provides high performance, high availability, and easy scalability.
MongoDB is the leading NoSQL database, empowering businesses to be more agile and scalable. Fortune 500 companies and startups alike are using MongoDB to create new types of applications, improve customer experience, accelerate time to market and reduce costs.
Features for MongoDB
Json style documents
Index on any attribute
Rich quries
In-place update
Auto sharding
Map reduce
GridFS to store files
Capped collections
Advantages of MongoDB over RDBMS
Schema less : MongoDB is document database in which one collection holds different different documents. Number of fields, content and size of the document can be differ from one document to another.
Structure of a single object is clear
No complex joins
Deep query-ability. MongoDB supports dynamic queries on documents using a document-based query** language that's nearly as powerful as SQL
Tuning
Ease of scale-out: MongoDB is easy to scale
Why should use MongoDB
Document Oriented Storage : Data is stored in the form of JSON style documents
Index on any attribute
ThingSpeak is an open-source Internet of Things (IoT) application and API to store and retrieve data from things using the HTTP protocol over the Internet or via a Local Area Network.ThingSpeak was originally launched by ioBridge in 2010 as a service in support of IoT applications. ThingSpeak™ is an IoT analytics platform service that allows you to aggregate, visualize and analyze live data streams in the cloud.
ThingSpeak provides instant visualizations of data posted by your devices to ThingSpeak. With the ability to execute MATLAB® code in ThingSpeak you can perform online analysis and processing of the data as it comes in. ThingSpeak is often used for prototyping and proof of concept IoT systems that require analytics.
ThingSpeak allows you to aggregate, visualize and analyze live data streams in the cloud.
Some of the key capabilities of ThingSpeak include the ability to
Easily configure devices to send data to ThingSpeak using popular IoT protocols.
Visualize your sensor data in real-time.
Aggregate data on-demand from third-party sources.
Use the power of MATLAB to make sense of your IoT data.
Run your IoT analytics automatically based on schedules or events.
Prototype and build IoT systems without setting up servers or developing web software.
Automatically act on your data and communicate using third-party services like Twilio® or Twitter®.
Minikube is a tool that makes it easy to run Kubernetes locally. Minikube runs a single-node Kubernetes cluster inside a VM on your laptop for users looking to try out Kubernetes or develop with it day-to-day.
Minikube supports Kubernetes features such as:
DNS
NodePorts
ConfigMaps and Secrets
Dashboards
Container Runtime: Docker, rkt, CRI-O and containerd
Enabling CNI (Container Network Interface)
Ingress
When using a single VM of Kubernetes, it’s really handy to reuse the Minikube’s built-in Docker daemon; as this means you don’t have to build a docker registry on your host machine and push the image into it -
We can just build inside the same docker daemon as minikube which speeds up local experiments. Just make sure you tag your Docker image with something other than ‘latest’ and use that tag while you pull the image. Otherwise, if you do not specify version of your image,
it will be assumed as :latest, with pull image policy of Always correspondingly, which may eventually result in ErrImagePull as you may not have any versions of your Docker image out there in the default docker registry (usually DockerHub) yet.
