Best NoSQL Databases 2019 - Most Popular Among Programmers

Before starting with most popular NoSQL databases. You must have to know about&nbsp;<strong>NoSQL databases</strong>. Most of the programmer doesn’t know that it stands for&nbsp;<strong>Not only SQL</strong>. After getting knowledge of NoSQL database, we will jump into&nbsp;<em>Best NoSQL databases</em>&nbsp;for the 2019&nbsp;year and we also see&nbsp;Cassandra vs MongoDB vs HBase.

Before starting with most popular NoSQL databases. You must have to know about NoSQL databases. Most of the programmer doesn’t know that it stands for Not only SQL. After getting knowledge of NoSQL database, we will jump into Best NoSQL databases for the 2019 year and we also see Cassandra vs MongoDB vs HBase.

WHAT IS NOSQL DATABASE?

NoSQL databases (additionally called Not Only SQL Databases) are non-relationaldatabase systems used for Storing and Retrieving data. These days NoSQL Databases are vigorously utilized as a part of real-time web applications. NoSQL databases can likewise be said as Big Data databases or Cloud databases. NoSQL Databases are quicker in contrast to SQL Databases and thus NoSQL Databases are utilized as a part of a Big Data application. Before utilizing any specific NoSQL Database you ought to check its component first on the grounds that each NoSQL Database has it claim set of functionalities. Now, we will go to Most popular NoSQL databases and Best NoSQL Database for 2019 and 2020 year.

NOSQL DATABASE TYPES
  • Document Databases – These Db usually pair each key with a complex data structure which is called a document. Documents can contain key-array pairs or key-value pairs or even nested documents.
  • Key-value stores – Every single item is stored as a Key-value pair. Key-value stores are the most simple among NoSQL Databases.
  • Wide-column stores – These types of Databases are optimized for queries over large datasets, and instead of rows, they store columns of data together.
  • Graph stores – These store information about graphs, networks, such as social connections.

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BEST NOSQL DATABASES 2019

MongoDB

It is an open source NoSQL database which is document-oriented. MongoDB uses JSON like documents to store any data. It is written in C++.

Cassandra

It was developed at Facebook for inbox search. Cassandra is a distributed data storage system for handling very large amounts of structured data.

Redis

Redis is the most famous key-value store. Redis is composed in C language. It is authorized under BSD.

HBase

It is a distributed and non-relational database which is designed for the BigTable database by Google.

Neo4j

Neo4j is referred to as a native graph database because it effectively implements the property graph model down to the storage level.

Oracle NoSQL

Oracle NoSQL Database implements a map from user-defined keys to opaque data items.

Amazon DynamoDB

DynamoDB uses a NoSQL database model, which is nonrelational, allowing documents, graphs and columnar among its data models.

Couchbase

Couchbase Server is a NoSQL document database for interactive web applications. It has a flexible data model, is easily scalable, provides consistent high performance.

Memcached

It is an open source, high-performance, distributed memory caching system intended to speed up dynamic web applications by reducing the database load.

CouchDB

It is an Open Source NoSQL Database which utilizes JSON to store information and JavaScript as its query language.

1. MONGODB


MongoDB is the most well known among NoSQL Databases. It is an Open-Sourcedatabase which is Document-oriented. MongoDB is a scalable and accessible database. It is in C++. MongoDB can likewise be utilized as the file system. In MongoDB, JavaScript can be utilized as the query language. By utilizing sharding MongoDB scales horizontally. It is very useful in Popular JavaScript Frameworks. People really enjoying sharding, advanced text searching, gridFS, map-reduce features for the 2019 year. Amazing performance and new features promoted this NoSQL database to 1st place in our list.

  • Developed by: MongoDB Inc. in 2007
  • Latest version: 4.0.5
  • Blog: MongoDB
  • Download: MongoDB

FEATURES

  • Provides high performance
  • Auto-sharding
  • Run over multiple servers
  • Supports Master-Slave replication
  • Data is stored in the form of JSON style documents
  • index any field in a document
  • It has an automatic load balancing configuration because of data placed in shards
  • Supports regular expression searches
  • Easy to administer in the case of failures

PROS OF MONGODB

  • Easy to setup MongoDB
  • MongoDB Inc. provides professional support to its clients
  • Support ad-hoc query
  • High-Speed Database
  • Schema-less database
  • Horizontally scalable database
  • Performance is very high

CONS OF MONGODB

  • Doesn’t support joins
  • Data Size is High
  • Nesting of documents is limited
  • Increase unnecessary usage of memory
2. CASSANDRA


Cassandra was developed at Facebook for inbox search. Cassandra is a distributed data storage system for handling very large amounts of structured data. Generally, these data are spread out across many commodity servers. You can also add storage capacity of your data keeping your service online and you can do this task easily. As all the nodes in a cluster are same, there is no complex configuration to deal with. Cassandra is written in Java. Cassandra Query Language (CQL) is a SQL-like language for querying Cassandra Database. As a result, Cassandra stands 2nd in best open source databases. Cassandra is being used by some of the biggest companies such as Facebook, Twitter, Cisco, Rackspace, eBay, Twitter, Netflix, and more.

  • Developed by: Apache Software Foundation
  • Latest version: 3.11.3
  • Blog: Cassandra
  • Download: Cassandra

FEATURES

  • Linearly scalable
  • Maintains a quick response time
  • Supports properties like Atomicity, Consistency, Isolation, and Durability (ACID)
  • Supports MapReduce with Apache Hadoop
  • Maximal flexibility to distribute the data
  • Highly scalable
  • Peer-to-peer architecture

PROS OF CASSANDRA

  • Highly scalable
  • No single point of failure
  • Multi-DC Replication
  • Integrate tightly with other JVM based applications
  • More suitable for multiple data-center deployments, redundancy, failover and disaster recovery

CONS OF CASSANDRA

  • Limited support for aggregations
  • Unpredictable Performance
  • Doesn’t Support ad-hoc query
3. REDIS

Redis is a key-value store. Furthermore, it is the most famous key-value store. Redis has support for some C++, PHP, Ruby, Python, Perl, Scala and so forth. Redis is composed in C language. Furthermore, it is authorized under BSD.

  • Developed by: Salvatore Sanfilippo
  • Latest version: 5.0.2
  • Blog: Redis
  • Download: Redis

FEATURES

  • Automatic failover
  • Holds its database entirely in the memory
  • Transactions
  • Lua scripting
  • Replicate data to any number of slaves
  • Keys with a limited time-to-live
  • LRU eviction of keys
  • Supports Publish/Subscribe

PROS OF REDIS

  • Supports a huge variety of data types
  • Easy to install
  • Very fast(perform about 110000 SETs per second, about 81000 GETs per second)
  • Operations are atomic
  • Multi-utility tool(used in a number of use cases)

CONS OF REDIS

  • Doesn’t support joins
  • Knowledge required of Lua for stored procedures
  • the dataset has to fit comfortably in memory
4. HBASE


HBase is a distributed and non-relational database which is designed for the BigTable database by Google. One of the main goals of HBase is to host Billions of rows Xmillions of columns. You can add servers anytime to increase capacity. And multiple master nodes will ensure high availability of your data. HBase is composed in Java 8. It’s authorized under Apache. Hbase accompanies simple to utilize Java API for customer access also.

  • Developed by: Apache Software Foundation
  • Blog: HBase
  • Download: HBase
  • latest version: 2.1.0

FEATURES

  • Support automatic failure
  • Linearly scalable
  • Provides data replication
  • Integrates with Hadoop, both as a source and a destination

PROS OF HBASE

  • Provides fast lookups for larger tables.
  • Provides low latency access to single rows from billions of records
  • Easy Java API for client
  • Auto-sharding
  • License-free
  • Handle large datasets on top of HDFS file storage
  • Flexible on schema design
  • High-speed

CONS OF HBASE

  • Doesn’t support transaction
  • No permissions or built-in authentication
  • Indexed and sorted only on key.
  • Single point of failure (when only one HMaster is used)
  • Doesn’t support for SQL structure
  • Memory issues on the cluster
5.NEO4J

Neo4j is referred to as a native graph database because it effectively implements the property graph model down to the storage level. This means that the data is stored exactly as you whiteboard it, and the database uses pointers to navigate and traverse the graph. Neo4j has both a Community Edition and Enterprise Edition of the database. The Enterprise Edition includes all that Community Edition has to offer, plus extra enterprise requirements such as backups, clustering, and failover abilities.

  • Developed by: Neo Technology
  • Blog: Neo4j
  • Download: Neo4j
  • Latest version: 3.4.9

FEATURES

  • Supports UNIQUE constraints
  • Supports full ACID(Atomicity, Consistency, Isolation, and Durability) rules
  • Supports both Java API: Cypher API and Native Java API
  • Supports Indexes by using Apache Lucence
  • Easy query language Neo4j CQL
  • Contains a UI to execute CQL Commands: Neo4j Data Browser

PROS OF NEO4J

  • Easy to retrieve its adjacent node or relationship details without Joins or Indexes
  • Easy to learn Neo4j CQL query language commands
  • Not require complex Joins to retrieve data
  • Represents semi-structured data very easily
  • High availability for large enterprise real-time applications
  • Simplified tuning

CONS OF NEO4J

  • Doesn’t support Sharding
6. ORACLE NOSQL

Oracle just started NoSQL database with Oracle NoSQL. It’s becoming popular in the year 2018. It less popular compare to MongoDB and Casandra databases. Oracle NoSQL Database implements a map from user-defined keys to opaque data items. Although it records internal version numbers for key/value pairs, it only maintains the single latest version in the store. The version of Oracle, 12c, is designed for the cloud and can be hosted on a single server or multiple servers, and it enables the management of databases holding billions of records. Some of the features of the latest version of Oracle include a grid framework and the use of both physical and logical structures. Oracle Database 18c now provides customers with a high-performance, reliable and secure platform to easily and cost-effectively modernize their transactional and analytical workloads either in the Cloud, or on-premises or in a Hybrid Cloud configuration.

FEATURES

  • Oracle NoSQL Database handle big data
  • Supports SQL, and it can be accessed from Oracle relational databases
  • Oracle NoSQL Database using Java/C API to read and write data
  • Distributed database
  • Provides access to the data through the node for the requested key.

PROS OF ORACLE NOSQL

  •  Based on PL/SQL Programming construct
  • Peer to peer communities help to solve all problems
  • Oracle database is secure and ensures that user data is not tampered with through prompt updates.

CONS OF ORACLE NOSQL

  • High cost for small organizations
  • Require significant resources for installation
  • Hardware upgrades may be required to even implement Oracle
  • takes up a lot of space
7.AMAZON DYNAMODB

DynamoDB uses a NoSQL database model, which is nonrelational, allowing documents, graphs and columnar among its data models. Each DynamoDB query is executed by a primary key identified by the user, which uniquely identifies each item. It also relieves the customers from the burden of operating and scaling a distributed database. Hence, hardware provisioning, setup, configuration, replication, software patching, cluster scaling, etc. is managed by Amazon.

FEATURES

  • High Scalable
  • Hash-Range for indexing a range of values
  • Stores data in partitions
  • Utilizes JSON as a transport protocol, not as a storage format

PROS OF DYNAMODB

  • Easy to set up
  • Provide a low-level AWS DynamoDB API
  • Auto-scaling
  • Reduces the complexity of managing the high availability and scaling for peak usage times.
  • Encryption at rest
  • Security for DynamoDB is governed by AWS Identity

CONS OF DYNAMODB

  • Doesn’t back up your tables for free
  • Size limit
8.COUCHBASE

The focus is on the ease of use, embracing the web. It is a NoSQL document store database. Couchbase Server is a NoSQL document database for interactive web applications. It has a flexible data model, is easily scalable, provides consistent high performance. Couchbase Server, JSON documents are used to represent application objects and the relationships between objects.

  • Developed by: Couchbase, Inc.
  • Blog: CouchDB
  • Download: CouchDB
  • Latest version:  6.0.0

FEATURES

  • Auto-FailoverDeploying and Managing Couchbase at Scale With Kubernetes
  • Index partitioning
  • Support JSON data natively via N1QL queries
  • Data Compression
  • Couchbase Eventing Service

PROS OF COUCHBASE

  • Aggregate optimization
  • reduces the cost of network, memory, and storage
  •  great admin panel that provides tons of insights into how your cluster is performing

CONS OF COUCHBASE

  • Couchbase is not open source
9.MEMCACHED

Memcached is an open source, high-performance, distributed memory caching system intended to speed up dynamic web applications by reducing the database load. It is a key-value dictionary of strings, objects, etc., stored in the memory, resulting from database calls, API calls, or page rendering. It is now being used by Netlog, Facebook, Flickr, Wikipedia, Twitter, and YouTube among others.

  • Developed by: Danga Interactive
  • Blog: Memcached
  • Download: Memcached
  • Latest version: 1.5.12

FEATURES

  • Client-server application over TCP or UDP
  • Reduces the database load
  • Memcached server is a big hash table
  • Efficient for websites with high database load
  • Distributed under Berkeley Software Distribution license
  • Combine memory caches into a logical pool

PROS OF MEMCACHED

  • Installation is fast
  • Widely documented with a huge community

CONS OF MEMCACHED

  • Only supported on Linux operating systems and systems that are similar to BSD
  • Doesn’t support data redundancy
  • Doesn’t support for locks, read-through, CAS
10.COUCHDB

CouchDB is an Open Source NoSQL Database which utilizes JSON to store information and JavaScript as its query language. CouchDB applies a type of Multi-Version Controlling system for avoiding the blockage of the DB file during writing. It is Erlang. It’s authorized under Apache. It is ranked 1st for Best NoSQL Database 2016 list for popularity.

  • Developed by: Apache Software Foundation
  • Blog: CouchDB
  • Download: CouchDB
  • Latest version: 2.3.0

FEATURES

  • Map/Reduce List and Show
  • Provide database-level security
  • Authentication opens via a session cookie like a web application
  • JSONP for Free
  • Follow document storage
  • Support ACID Properties
  • Provide the simplest form of replication
  • Browser-based GUI to handle your data, permission, and configuration

PROS OF COUCHDB

  • Map/Reduce, querying data is somewhat separated from the data itself
  • Store any JSON data

CONS OF COUCHDB

  • Arbitrary queries are expensive
  • A bit of extra space overhead with CouchDB
  • Doesn’t support XML

Before ending list for NoSQL database. I must recommend preparing for Database interview -> Most popular quires for databases. We have recently been taking a survey from different programmers who are available on google plus social media for all SQL and NoSQL databases. Here we have seen the most popular database with its features, pros, and cons. Now you can decide which one is best for your project.




Database Design Tutorial - How to Design & Plan Database for Beginners

Database Design Tutorial - How to Design & Plan Database for Beginners

Learn how to design and plan a database for beginners. This database design course will help you understand database concepts and give you a deeper grasp of database design. Database design is the organisation of data according to a database model. The designer determines what data must be stored and how the data elements interrelate. With this information, they can begin to fit the data to the database model.

Database Design Tutorial - How to Design & Plan Database for Beginners

This database design course will help you understand database concepts and give you a deeper grasp of database design.

Database design is the organisation of data according to a database model. The designer determines what data must be stored and how the data elements interrelate. With this information, they can begin to fit the data to the database model.

⭐️ Contents ⭐
⌨️ (0:00:00) Introduction
⌨️ (0:03:12) What is a Database?
⌨️ (0:11:04) What is a Relational Database?
⌨️ (0:23:42) RDBMS
⌨️ (0:37:32) Introduction to SQL
⌨️ (0:44:01) Naming Conventions
⌨️ (0:47:16) What is Database Design?
⌨️ (1:00:26) Data Integrity
⌨️ (1:13:28) Database Terms
⌨️ (1:28:28) More Database Terms
⌨️ (1:38:46) Atomic Values
⌨️ (1:44:25) Relationships
⌨️ (1:50:35) One-to-One Relationships
⌨️ (1:53:45) One-to-Many Relationships
⌨️ (1:57:50) Many-to-Many Relationships
⌨️ (2:02:24) Designing One-to-One Relationships
⌨️ (2:13:40) Designing One-to-Many Relationships
⌨️ (2:23:50) Parent Tables and Child Tables
⌨️ (2:30:42) Designing Many-to-Many Relationships
⌨️ (2:46:23) Summary of Relationships
⌨️ (2:54:42) Introduction to Keys
⌨️ (3:07:24) Primary Key Index
⌨️ (3:13:42) Look up Table
⌨️ (3:30:19) Superkey and Candidate Key
⌨️ (3:48:59) Primary Key and Alternate Key
⌨️ (3:56:34) Surrogate Key and Natural Key
⌨️ (4:03:43) Should I use Surrogate Keys or Natural Keys?
⌨️ (4:13:07) Foreign Key
⌨️ (4:25:15) NOT NULL Foreign Key
⌨️ (4:38:17) Foreign Key Constraints
⌨️ (4:49:50) Simple Key, Composite Key, Compound Key
⌨️ (5:01:54) Review and Key Points....HA GET IT? KEY points!
⌨️ (5:10:28) Introduction to Entity Relationship Modeling
⌨️ (5:17:34) Cardinality
⌨️ (5:24:41) Modality
⌨️ (5:35:14) Introduction to Database Normalization
⌨️ (5:39:48) 1NF (First Normal Form of Database Normalization)
⌨️ (5:46:34) 2NF (Second Normal Form of Database Normalization)
⌨️ (5:55:00) 3NF (Third Normal Form of Database Normalization)
⌨️ (6:01:12) Indexes (Clustered, Nonclustered, Composite Index)
⌨️ (6:14:36) Data Types
⌨️ (6:25:55) Introduction to Joins
⌨️ (6:39:23) Inner Join
⌨️ (6:54:48) Inner Join on 3 Tables
⌨️ (7:07:41) Inner Join on 3 Tables (Example)
⌨️ (7:23:53) Introduction to Outer Joins
⌨️ (7:29:46) Right Outer Join
⌨️ (7:35:33) JOIN with NOT NULL Columns
⌨️ (7:42:40) Outer Join Across 3 Tables
⌨️ (7:48:24) Alias
⌨️ (7:52:13) Self Join

Migrate Entity Framework Core to SQL Database on Startup

Migrate Entity Framework Core to SQL Database on Startup

This ASP.NET Core tutorial explains how to migrate Entity Framework Core to SQL Database on Startup. How to automatically migrate database changes from code in ASP.NET Core using Entity Framework Core from the Startup.cs file. Use the EF Core DB Context Service to automatically migrate database changes.

Example code tested with ASP.NET Core 3.1

This is a super quick example of how to automatically migrate database changes from code in ASP.NET Core using Entity Framework Core from the Startup.cs file.

Solution

Register the EF Core DB Context as an ASP.NET Core Service

The Entity Framework Core DB Context is registered as a service with the ASP.NET Core Dependency Injection (DI) system from the ConfigureServices() method of the Startup.cs file.

// This method gets called by the runtime. Use this method to add services to the container.
public void ConfigureServices(IServiceCollection services)
{
    services.AddDbContext<DataContext>(x => x.UseSqlite("Data Source=LocalDatabase.db"));

    ...
}

Use the EF Core DB Context Service to automatically migrate database changes

An instance of the EF Core DB Context service is injected as a parameter into the Configure() method of the Startup.cs file, the DB Context instance is then used to apply any pending migrations to the database by calling the Database.Migrate() method.

// This method gets called by the runtime. Use this method to configure the HTTP request pipeline.
public void Configure(IApplicationBuilder app, IWebHostEnvironment env, DataContext dataContext)
{
    // migrate any database changes on startup (includes initial db creation)
    dataContext.Database.Migrate();

    ...
}
Extra Info

While updating the tutorial from an EF Core InMemory database to SQLite I ran into some difficulties trying to automatically run database migrations from the Startup.cs. At first I was following a tutorial on the MS Docs website that called services.BuildServiceProvider().GetService<MyDatabaseContext>().Database.Migrate(); from within the ConfigureServices() method, but this resulted in the following warning in the console when I ran the application:

Startup.cs(39,13): warning ASP0000: Calling 'BuildServiceProvider' from application code results in an additional copy of singleton services being created.
Consider alternatives such as dependency injecting services as parameters to 'Configure'.
[/Users/jwatmore/Projects/aspnet-core-3-registration-login-api/WebApi.csproj]

Database Management Tutorial - Database Design and Management

Database Management Tutorial - Database Design and Management

Learn how to design and manage database with ERD, database generation and reversal with Visual Paradigm.

Learn how to design and manage database with ERD, database generation and reversal with Visual Paradigm.

Database Design and Management is tailor-made for software development teams who need to develop application or software system that require data persistence. All lectures come with clear voice-over as well as demonstrations to walk you through different tools step by step. We are sure you can master database design and management skills with ease and learn most key features in Visual Paradigm after attending the lectures.

The lectures cover a wide range of contents. Firstly, you will start by an introduction of database design, with description of ERD, entity and column. After gaining a better knowledge about ERD, you can then jump to keys, relationships, database view, triggers and stored procedures. This course also covers database management skills like the generation of database from ERD, database patching and reverse engineering of ERD. Developers may want to study the lecture about ORM for system development with database. Last but not least, the training introduces some best practices in database design and management, as well as the usage of data specification.

Once you have completed this online training, you will know how to design database productively and effectively.

What you'll learn

  • Design database with ERD
  • Maintain database productively and effectively
  • Use Visual Paradigm in database design
  • Use Visual Paradigm in database management