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  1. Stackups
  2. Application & Data
  3. NoSQL Databases
  4. NOSQL Database As A Service
  5. Cloudant vs IBM DB2

Cloudant vs IBM DB2

OverviewComparisonAlternatives

Overview

Cloudant
Cloudant
Stacks86
Followers74
Votes28
IBM DB2
IBM DB2
Stacks245
Followers254
Votes19

Cloudant vs IBM DB2: What are the differences?

Introduction:

Cloudant and IBM DB2 are both database management systems offered by IBM. While they share some similarities, they also have key differences that set them apart from each other. In this article, we will explore and discuss these differences in detail.

  1. Scalability: Cloudant is a NoSQL, distributed database designed to handle large-scale, high-velocity workloads. It offers automatic data partitioning and replication across multiple servers, enabling it to scale horizontally as the workload increases. On the other hand, IBM DB2 is a relational database management system (RDBMS) that follows the traditional ACID (Atomicity, Consistency, Isolation, Durability) properties. It can handle large-scale workloads but scaling up requires careful design and planning.

  2. Data Model: Cloudant uses a flexible schema-less data model. It allows for the storage of different types of data without predefined schemas, making it suitable for applications with evolving data structures. IBM DB2, on the other hand, follows a strict relational model that requires predefined schemas. It uses tables with columns and rows to organize and store data, making it more suitable for structured data sets.

  3. Query Language: Cloudant uses Apache Lucene-based full-text search and Cloudant Query as its primary query languages. It also supports MapReduce for complex queries and indexing. In contrast, IBM DB2 uses SQL as its primary query language. SQL is a widely adopted language for relational databases and allows for complex queries and data manipulation.

  4. Deployment Options: Cloudant is a managed database service that is offered as part of IBM Cloud. It provides a fully managed environment where IBM takes care of infrastructure, backups, and security. IBM DB2, on the other hand, can be deployed on-premises or in the cloud. It provides more flexibility but requires additional efforts for maintenance and management.

  5. Data Consistency: Cloudant guarantees eventual consistency for read and write operations. It means that changes may take some time to propagate across all replicas but are eventually consistent. IBM DB2, being a relational database, follows strong consistency. It ensures that all transactions are immediately consistent with the most up-to-date data, maintaining data integrity and accuracy.

  6. Integration with IBM Ecosystem: Cloudant is designed to integrate well with other IBM Cloud services and tools like Watson, IoT, and Analytics. It provides seamless integration for building applications on the IBM Cloud platform. IBM DB2, being an established RDBMS, has a broader integration capability with various IBM and third-party tools and platforms.

In Summary, Cloudant and IBM DB2 have key differences in terms of scalability, data model, query language, deployment options, data consistency, and integration with the IBM ecosystem. These differences make each database suitable for different use cases and requirements.

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Detailed Comparison

Cloudant
Cloudant
IBM DB2
IBM DB2

Cloudant’s distributed database as a service (DBaaS) allows developers of fast-growing web and mobile apps to focus on building and improving their products, instead of worrying about scaling and managing databases on their own.

DB2 for Linux, UNIX, and Windows is optimized to deliver industry-leading performance across multiple workloads, while lowering administration, storage, development, and server costs.

Managed- Cloudant's big data experts monitor your data 24/7 to ensure its high availability and safety.;Distributed Multi-Master Database- All read and write transactions can be synced across Cloudant's global data network without global locks, providing true high availability of your data.;Geo-load Balancing- To keep latency low, our geo-load balancing infrastructure routes requests to the copies of the data that are geographically closest to the requestor.;Mobile Sync- Cloudant not only syncs between data centers around the world, but also between data centers and mobile devices.;Incremental MapReduce- Unlike Hadoop, Cloudant’s Incremental MapReduce keeps indexes up-to-date with new transactions and updates without requiring a full reindexing of your data.;Integrated Lucene Search- High-performance full-text indexing and search, without the difficulty and cost of managing text and operational data in separate databases.
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Statistics
Stacks
86
Stacks
245
Followers
74
Followers
254
Votes
28
Votes
19
Pros & Cons
Pros
  • 13
    JSON
  • 7
    REST interface
  • 4
    Cheap
  • 3
    JavaScript support
  • 1
    Great syncing
Pros
  • 7
    Rock solid and very scalable
  • 5
    BLU Analytics is amazingly fast
  • 2
    Native XML support
  • 2
    Secure by default
  • 2
    Easy
Integrations
AppHarbor
AppHarbor
Heroku
Heroku
Microsoft Azure
Microsoft Azure
Amazon EC2
Amazon EC2
SoftLayer
SoftLayer
CloudBees
CloudBees
Joyent Cloud
Joyent Cloud
Rackspace Cloud Servers
Rackspace Cloud Servers
cloudControl
cloudControl
Node.js
Node.js
JavaScript
JavaScript
PHP
PHP
Ruby
Ruby
Java
Java
Python
Python
C#
C#
.NET
.NET
C++
C++
Perl
Perl

What are some alternatives to Cloudant, IBM DB2?

MongoDB

MongoDB

MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.

MySQL

MySQL

The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.

PostgreSQL

PostgreSQL

PostgreSQL is an advanced object-relational database management system that supports an extended subset of the SQL standard, including transactions, foreign keys, subqueries, triggers, user-defined types and functions.

Microsoft SQL Server

Microsoft SQL Server

Microsoft® SQL Server is a database management and analysis system for e-commerce, line-of-business, and data warehousing solutions.

SQLite

SQLite

SQLite is an embedded SQL database engine. Unlike most other SQL databases, SQLite does not have a separate server process. SQLite reads and writes directly to ordinary disk files. A complete SQL database with multiple tables, indices, triggers, and views, is contained in a single disk file.

Cassandra

Cassandra

Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.

Memcached

Memcached

Memcached is an in-memory key-value store for small chunks of arbitrary data (strings, objects) from results of database calls, API calls, or page rendering.

MariaDB

MariaDB

Started by core members of the original MySQL team, MariaDB actively works with outside developers to deliver the most featureful, stable, and sanely licensed open SQL server in the industry. MariaDB is designed as a drop-in replacement of MySQL(R) with more features, new storage engines, fewer bugs, and better performance.

RethinkDB

RethinkDB

RethinkDB is built to store JSON documents, and scale to multiple machines with very little effort. It has a pleasant query language that supports really useful queries like table joins and group by, and is easy to setup and learn.

Amazon DynamoDB

Amazon DynamoDB

With it , you can offload the administrative burden of operating and scaling a highly available distributed database cluster, while paying a low price for only what you use.

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