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 Source - https://www.linkedin.com/posts/rocky-bhatia-a4801010_exploring-different-types-of-databases-activity-7168574286775930881-8X9j


In today's data-driven world, the choice of database technology plays a crucial role in the success of various applications and systems. With a multitude of options available, ranging from traditional SQL databases to specialised solutions for specific data types and use cases, it's essential to understand the characteristics and functionalities of each type.

Lets explore different type of databases

1. SQL Databases: These are relational databases that use Structured Query Language (SQL) for defining and manipulating data. Examples include MySQL, PostgreSQL, and Oracle Database.

2. Document Databases: These databases store semi-structured data as documents, typically in JSON or BSON format. They are suitable for use cases where flexibility in data schema is required. Examples include MongoDB and Couch base.

3. Columnar Databases: Also known as column-oriented databases, they store data in columns rather than rows, which can provide better performance for analytics and data warehousing. Examples include Apache Cassandra and Apache HBase.

4. Key-Value Stores: These databases store data as key-value pairs, making them simple and efficient for certain types of operations such as caching and session management. Examples include Redis and Amazon DynamoDB.

5. Vector Databases: These databases are optimized for storing and querying vector data, which is common in machine learning and data analytics applications. Examples include Faiss and Milvus.

6. Object Databases: These databases are designed to store objects rather than rows or documents, making them suitable for object-oriented programming paradigms. Examples include db4o and ObjectDB.

7. Graph Databases: These databases are optimized for storing and querying graph data structures, making them suitable for applications like social networks, recommendation engines, and fraud detection. Examples include Neo4j and Amazon Neptune.

8. In-Memory Databases: These databases primarily store data in memory rather than on disk, resulting in very fast read and write operations. Examples include Redis (again) and Memcached.

9. Time Series Databases: These databases are optimized for storing and querying time-stamped data, making them suitable for IoT, monitoring, and financial applications. Examples include InfluxDB and Prometheus.

Other database like search , new sql , spatial etc are also there

Each type of database has its own strengths and weaknesses, and the choice of database depends on the specific requirements of the application and the nature of the data being stored and queried.

Referred Link - http://bigdataanalyticsnews.com/mongodb-mistakes-to-avoid-the-best-practices-to-follow/

mongodb

MongoDB is supposed to be a greatly-in-demand NoSQL database. As per experts, developers are used to making many mistakes while working on various MongoDB projects. Here are some of the mistakes to avoid.
Mistake No.1: Allowing Access from the Internet
If you allow access to your MongoDB database from the Internet, it would be a grave mistake. The default configuration of MongoDB used to leave the database fully exposed to the Internet. It implies that anyone could easily connect to your MongoDB database simply by using the server’s URL. A database must be accessible through your app only. It must actually be kept hidden in an exclusively private network which would be local and providing access to only your app’s server.
Even though MongoDB developers claim that this sort of vulnerability no longer exists and has actually been fixed in the latest versions, you must ensure that the configuration is changed after upgrading the database from the earlier version. You must focus on securing your MongoDB database. Maintaining a white-list of only those IP addresses which are having access to your MongoDB database is supposed to be a clever idea.
Mistake No.2: Having Just a Single MongoDB User
Another probable security risk would be having just one MongoDB database user instead of multiple users doing the entire job. This generally would take place when inexperienced developers or developers with lack of any interest in databases or developers without sound knowledge of the databases are there to take care of database management.
It is always a bad idea to have just one user for managing the database and then utilize the same user for accessing the database. You must understand that NoSQL would not automatically imply “secure” by default. Developers must be concerned about security breaches and overall security of the database while creating the database. Do not wait until the last moment for properly managing security issues and mitigating all possibilities of security breaches after shipping the product. You may seek assistance from professional DBA services such as RemoteDBA.com for perfect database management solutions.
Mistake No.3: Assuming Schema-Less Implies No Schema
MongoDB does not necessarily require a schema. You need to focus on your data structure. Do not be impatient and do not be in a hurry, instead think how you would be organizing your data and structure all important documents. Schemaless does not imply you have absolutely no Schema. RDBMS generally boast a pre-defined schema that is tables with columns and each comes with a data type and names. If you wish to insert an additional column, you need to include an extra column to the whole table.
But MongoDB actually does away with all this. We discover the absence of any enforced schema per document or collection. This would facilitate rapid developments and modifications could become quite easy. But do not be under the wrong impression that you could completely ignore schema design. If you have a perfectly designed schema, you could obtain the best performance and outcomes from MongoDB.
Mistake No.4: Premature Sharding
Sharding is supposed to be an optimization. Hence, you must avoid doing it way too soon as it could be a bad idea. Often just one single replica set could be adequate for operating a smooth and fast MongoDB that caters to all your specific requirements. Bad indexing and bad schema are supposed to be the real performance bottlenecks that users would be thinking of solving their issues with sharding. This process could be considered particularly when an obvious resource such as concurrency or RAM becomes a performance bottleneck on some particular machine.
Mistake No.4: Using Replicas as Backup
Remember replicas are not supposed to be backups. You would be requiring the right backup system for your database. You must not regard replicas as the actual backup mechanism. Think about what would be happening when you end up deploying the incorrect code which totally ruins the database. In such a case, replicas would be simply following the master and having the same kind of damage. You could be using a backdrop and even restoring your MongoDB in a number of effective ways, such as Mongodump, or filesystem snapshots or even MMS (Third-party service). It is crucial to have perfect fire drills. You must have the confidence that the backups made by you would be used actually in a real-life situation.
MongoDB Best Practices
If you fail to follow MongoDB best practices you could end up losing sensitive data, disrupting operations, and even dragging organizations out of business. All the MongoDB best practices discussed below are from experienced MongoDB professionals involved in creating security systems meant for databases and working closely with MongoDB users.
Enabling Access Control plus Enforcing Authentication
You should be enabling access control and specifying the authentication mechanism. You could consider using any of the existing external frameworks or the default MongoDB mechanism for authentication. Authentication necessitates that all servers and clients must provide valid credentials and only then they could be connecting to the system.
Encrypting Communication
You must necessarily configure MongoDB for using TLS/SSL meant for all the outgoing and incoming connections.
Restricting Network Exposure
Make sure that MongoDB operates in a trustworthy network environment. Consider restricting or limiting the interfaces where MongoDB instances actually are listening for incoming connections. You must only let trusted clients go ahead with accessing the ports and network interfaces where MongoDB instance could be available.
Auditing System Activity
You must be tracking access and modifications to the database configurations, as well as, data. MongoDB Enterprise actually includes an efficient system auditing facility which could be recording system events like connection events, user operations, etc. All these audit records would be permitting forensic analysis and allowing administrators to go about verifying proper controls.
Considering Security Standards Compliance
You could take note of the Security Reference Architecture of MongoDB for learning more about ways to utilize the core security capabilities for building compliant application infrastructure.
Conclusion
Many people do not like MongoDB. Actually, this is simply because they are misguided. The fact remains that many of you lack the basic understanding. If you avoid the common MongoDB mistakes and follow the MongoDB best practices discussed above, everyone would be benefitting from the simplicity and power of MongoDB. Moreover, never disregard security best practices. The most certain way of creating an insecure system would be to go on ignoring the topic altogether. Before deployment of any MongoDB instance having certain sensitive data, you must examine thoroughly the MongoDB security.
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Jayavel Chakravarthy Srinivasan
Professional:I'm a Software Techie, Specialized in Microsoft technologies. Worked in CMM Level 5 organizations like EPAM, KPMG, Bosch, Honeywell, ValueLabs, Capgemini and HCL. I have done freelancing. My interests are Software Development, Graphics design and Photography.
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