Database Management System Lab (PCCCS405P)
S. B. JAIN INSTITUTE OF TECHNOLOGY,
MANAGEMENT & RESEARCH, NAGPUR.
Post lab
Aim: Case study on Document Store Database Management Systems:
• MongoDB
• Couchbase
• CouchDB
• Amazon DocumentDB
• RavenDB
Name of Student:
Roll No.:
Semester/Year:
Academic Session:
Date of Performance:
Date of Submission:
Department of Computer Science and Engineering (CSE), S.B.J.I.T.M.R.
Database Management System Lab (PCCCS405P)
AIM: Document Store Database Management Systems:
• MongoDB
• Couchbase
• CouchDB
• Amazon DocumentDB
• RavenDB
OBJECTIVE/ EXPECTED LEARNING OUTCOME:
The objectives and expected learning outcome of this practical are:
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Gain practical experience in deploying and managing document store databases, such as
MongoDB and Couchbase, to understand their unique data storage and retrieval
mechanisms.
Explore the scalability and performance features of document store databases, including
sharding and replication, to effectively handle large datasets and high-volume workloads.
Analyze the suitability of different document store databases for various use cases and
applications, considering factors such as data modeling flexibility and integration
capabilities.
THEORY:
Document Store Database Management Systems:
Document Store Database Management Systems are NoSQL databases that store and manage data
in a document-oriented format, typically using JSON or similar data structures. Unlike traditional
relational databases, which organize data in tables with rows and columns, document store
databases store data as documents, each containing key-value pairs or nested structures. These
databases are designed to provide flexibility in data modeling, allowing developers to store and
retrieve complex and hierarchical data structures without the need for a fixed schema. Examples
of document store databases include MongoDB, Couchbase, CouchDB, Amazon DocumentDB,
and RavenDB.
1. MongoDB:

MongoDB stores data in flexible JSON-like documents, allowing for easy representation of
complex data structures without the need for a fixed schema.
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MongoDB automatically distributes data across multiple servers in a cluster, enabling
horizontal scalability to handle growing data volumes and high traffic.
Department of Computer Science and Engineering (CSE), S.B.J.I.T.M.R.
Database Management System Lab (PCCCS405P)

MongoDB supports replica sets, which provide automatic failover and data redundancy,
ensuring high availability and data durability in case of server failures.
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MongoDB offers a variety of indexing options, including single-field, compound, geospatial,
and text indexes, to optimize query performance for different types of queries.
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MongoDB includes GridFS, a specification for storing large files and binary data in the
database, allowing for efficient storage and retrieval of large assets alongside other data.
2. Couchbase:
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Couchbase stores data in flexible JSON documents, supporting agile data modeling without
rigid schemas.
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Couchbase's distributed architecture scales horizontally across nodes for high availability and
elasticity with growing data and workloads.
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Couchbase prioritizes frequently accessed data in memory for low-latency access, ensuring
performance and reliability.
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Couchbase offers built-in full-text search capabilities for advanced text searches without
external tools.
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Couchbase includes caching features within the database for improved performance and
reduced latency in read-heavy scenarios.
3. CouchDB:

CouchDB is a NoSQL database that stores data in JSON-like documents for flexible data
modeling.
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CouchDB's distributed design allows for horizontal scaling across multiple nodes to handle
large datasets and high traffic.

CouchDB offers eventual consistency, ensuring that data changes eventually propagate across
the system.

CouchDB supports built-in replication for data synchronization across distributed nodes,
providing fault tolerance and data redundancy.
Department of Computer Science and Engineering (CSE), S.B.J.I.T.M.R.
Database Management System Lab (PCCCS405P)
4. Amazon DocumentDB:

Amazon DocumentDB is a fully managed service provided by Amazon Web Services (AWS),
simplifying database administration tasks.
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It is compatible with MongoDB, allowing seamless migration of MongoDB workloads to
Amazon DocumentDB.

Amazon DocumentDB automatically scales storage and compute resources to accommodate
changing workloads and data volumes.
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It offers built-in replication across multiple availability zones for increased reliability and fault
tolerance.

Amazon DocumentDB provides robust security features and complies with industry standards
such as HIPAA and GDPR.
5. RavenDB:

RavenDB is a NoSQL database that stores data in flexible JSON-like documents, enabling agile
data modeling.
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RavenDB supports ACID transactions, ensuring data consistency, durability, and reliability
even in complex operations.

It offers support for multiple data models, including documents, graphs, and key-value pairs,
allowing diverse data types to be stored and queried.

RavenDB utilizes a distributed architecture with automatic sharding and replication for high
availability and scalability.

It includes built-in full-text search capabilities, enabling powerful text searches without the need
for external indexing or search engines.
Department of Computer Science and Engineering (CSE), S.B.J.I.T.M.R.
Database Management System Lab (PCCCS405P)
CONCLUSION: Hence, We successfully understood about the various document store database
management systems available, including MongoDB, Couchbase, CouchDB, Amazon
DocumentDB, and RavenDB. we understood the importance of selecting the right database system
based on specific requirements for scalability, reliability, and data model flexibility in different
organizational contexts.
DISCUSSION QUESTIONS:
1. What are some popular Document Store Database Management Systems?
2. What are the primary benefits of using MongoDB over traditional relational databases??
3. What are the advantages of using Amazon DocumentDB as a managed database service?
4. Can you explain the differences between CouchDB and Amazon DocumentDB ?
REFERENCE:
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www.w3schools.com/sql
http://www.nptelvideos.in/2012/11/database-management-system.html
Department of Computer Science and Engineering (CSE), S.B.J.I.T.M.R.