Answer:- MongoDB uses collections to store data rather than tables.

Answer:- The save() method is used to replace the existing document with a new document.

Answer:- MongoDB (from humongous) is a cross-platform document-oriented database. Classified as a NoSQL database, MongoDB eschews the traditional table-based relational database structure in favor of JSON-like documents with dynamic schemas (MongoDB calls the format ‘BSON’), making the integration of data in certain types of applications easier and faster. Released under a combination of the GNU Affero General Public License and the Apache License, MongoDB is open-source. MongoDB was first developed by the software company 10gen (now, MongoDB Inc.) in October 2007 as a component of a planned platform as a service product. Then, the company shifted to an open-source development model in 2009, with 10gen offering commercial support and other services. Since then, MongoDB has been adopted as backend software by a number of major websites and services, including Craigslist, eBay, Foursquare, SourceForge, Viacom, and the New York Times, among others. Currently, MongoDB is the most popular NoSQL database system.

Answer:- MongoDB is a relational database management system (RDBMS) replacement for web applications. So, when we have something close to RDBMS, MongoDB could be of good use. It gives us the additional partition tolerance, which RDMBS doesn’t offer, but it has problems with availability. Nonetheless, if we want more scalability, MongoDB would be the right choice for us. It’s suitable for real-time analytics and high-speed logging, and it’s highly scalable as well. Craigslist uses MongoDB for archived posts.

Answer:- Presently, the Internet is loaded with big data, big users, and so on that are becoming more complex day by day. NoSQL is the answer to all these problems; it is not a traditional database management system, not even a relational database management system (RDBMS). NoSQL stands for ‘Not only SQL’, and it is a type of database that can handle and sort all types of unstructured, messy, and complicated data. It is just a new way to think about databases. Yes, MongoDB is a NoSQL database.

Answer:- MongoDB is a document-oriented DBMS.

Answer:- Although both MongoDB and MySQL are free and open-source databases, there is a lot of difference between them in terms of data representation, relationships, transaction, querying data, schema design and definition, performance speed, normalization, and many more. To compare MySQL with MongoDB is like a comparison between relational and non-relational databases.

Answer:- • MongoDB is typically used as the primary data store for operational applications with real-time requirements (i.e., low latency, high availability, etc.). MongoDB is generally a good fit for 60–80 percent of the applications we build today. MongoDB is easy to operate and scale in the ways that are hard if not impossible with relational databases. • MongoDB excels in many use cases where the relational databases aren’t a good fit, like applications with unstructured, semi-structured, and polymorphic data, as well as those with large scalability requirements or multi-datacenter deployments. • MongoDB may not be a good fit for some applications. For example, applications that require complex transactions (e.g., a double-entry bookkeeping system) and scan-oriented applications that access large subsets of the data mostly may not be a good fit for MongoDB. Also, MongoDB is not a drop-in replacement for legacy applications built around the relational data model and SQL. • Some common use cases of MongoDB include mobile apps, product catalogs, real-time personalization, content management, and applications delivering a single view across multiple systems.

Answer:- MongoDB is a document-oriented DBMS. We can think of it as MySQL but with JSON-like objects comprising the data model, rather than RDBMS tables. Significantly, MongoDB supports neither joins nor transactions. However, it features secondary indexes, an expressive query language, atomic writes on a per-document level, and fully-consistent reads. Operationally, MongoDB offers the master–slave replication with automated failover and built-in horizontal scaling via automated range-based partitioning.

Answer:- MongoDB is implemented in C++. However, drivers and client libraries are typically written in their own respective languages. Although, some drivers use C extensions for better performance.

Answer:- MongoDB uses memory-mapped files. When running a 32-bit build of MongoDB, the total storage size for the server, including data and indexes, is 2 GB. For this reason, we do not deploy MongoDB to production on 32-bit machines. If we’re running a 64-bit build of MongoDB, there’s virtually no limit to the storage size. For production deployments, 64-bit builds and operating systems are strongly recommended.

Answer:- While creating a schema in MongoDB, the points need to be taken care of are as follows: • Design our schema according to the user requirements • Combine objects into one document if we want to use them together; otherwise, separate them • Do joins while on write, and not when it is on read • For most frequent use cases, optimize the schema • Do complex aggregation in the schema

Answer:- It is a column-oriented database that is used to store sparse data sets. It is run on the top of the Hadoop file distributed system. Apache HBase is a database that runs on a Hadoop cluster. Clients can access HBase data through either a native Java API or through a Thrift or REST gateway, making it accessible by any language. Some of the key properties of HBase include: • NoSQL: HBase is not a traditional relational database (RDBMS). HBase relaxes the ACID (Atomicity, Consistency, Isolation, Durability) properties of traditional RDBMS systems in order to achieve much greater scalability. Data stored in HBase also does not need to fit into a rigid schema like with an RDBMS, making it ideal for storing unstructured or semi-structured data. • Wide-Column: HBase stores data in a table-like format with the ability to store billions of rows with millions of columns. Columns can be grouped together in “column families” which allows physical distribution of row values onto different cluster nodes. • Distributed and Scalable: HBase group rows into “regions” which define how table data is split over multiple nodes in a cluster. If a region gets too large, it is automatically split to share the load across more servers. • Consistent: HBase is architected to have “strongly-consistent” reads and writes, as opposed to other NoSQL databases that are “eventually consistent”. This means that once a writer has been performed, all read requests for that data will return the same value.

Answer:- • HBase • Hadoop • Batch Jobs • REST/Thrift • Cassandra • Peer-to-peer • Data writes • Thrift