Most of you are already familiar with
SQL database, and have a good knowledge on either MySQL, Oracle, or
other SQL databases. In the last several years, NoSQL database is
getting widely adopted to solve various business problems.
It is helpful to understand the
difference between SQL and NoSQL database, and some of available
NoSQL database that you can play around with.
SQL vs NoSQL: High-Level Differences
SQL databases are primarily called
as Relational Databases (RDBMS); whereas NoSQL database are
primarily called as non-relational or distributed database.
SQL databases are table based
databases whereas NoSQL databases are document based, key-value
pairs, graph databases or wide-column stores. This means that SQL
databases represent data in form of tables which consists of n
number of rows of data whereas NoSQL databases are the collection of
key-value pair, documents, graph databases or wide-column stores
which do not have standard schema definitions which it needs to
adhered to.
SQL databases have predefined
schema whereas NoSQL databases have dynamic schema for unstructured
data.
SQL databases are vertically
scalable whereas the NoSQL databases are horizontally scalable. SQL
databases are scaled by increasing the horse-power of the hardware.
NoSQL databases are scaled by increasing the databases servers in
the pool of resources to reduce the load.
SQL databases uses SQL (
structured query language ) for defining and manipulating the data,
which is very powerful. In NoSQL database, queries are focused on
collection of documents. Sometimes it is also called as UnQL
(Unstructured Query Language). The syntax of using UnQL varies from
database to database.
SQL database examples: MySql,
Oracle, Sqlite, Postgres and MS-SQL. NoSQL database examples:
MongoDB, BigTable, Redis, RavenDb, Cassandra, Hbase, Neo4j and
CouchDb
For complex queries: SQL databases
are good fit for the complex query intensive environment whereas
NoSQL databases are not good fit for complex queries. On a
high-level, NoSQL don’t have standard interfaces to perform
complex queries, and the queries themselves in NoSQL are not as
powerful as SQL query language.
For the type of data to be stored:
SQL databases are not best fit for hierarchical data storage. But,
NoSQL database fits better for the hierarchical data storage as it
follows the key-value pair way of storing data similar to JSON data.
NoSQL database are highly preferred for large data set (i.e for big
data). Hbase is an example for this purpose.
For scalability: In most typical
situations, SQL databases are vertically scalable. You can manage
increasing load by increasing the CPU, RAM, SSD, etc, on a single
server. On the other hand, NoSQL databases are horizontally
scalable. You can just add few more servers easily in your NoSQL
database infrastructure to handle the large traffic.
For high transactional based
application: SQL databases are best fit for heavy duty transactional
type applications, as it is more stable and promises the atomicity
as well as integrity of the data. While you can use NoSQL for
transactions purpose, it is still not comparable and sable enough in
high load and for complex transactional applications.
For support: Excellent support are
available for all SQL database from their vendors. There are also
lot of independent consultations who can help you with SQL database
for a very large scale deployments. For some NoSQL database you
still have to rely on community support, and only limited outside
experts are available for you to setup and deploy your large scale
NoSQL deployments.
For properties: SQL databases
emphasizes on ACID properties ( Atomicity, Consistency, Isolation
and Durability) whereas the NoSQL database follows the Brewers CAP
theorem ( Consistency, Availability and Partition tolerance )
- For DB types: On a high-level, we can classify SQL databases
as either open-source or close-sourced from commercial vendors.
NoSQL databases can be classified on the basis of way of storing
data as graph databases, key-value store databases, document store
databases, column store database and XML databases.
SQL Database Examples
1. MySQL Community Edition
MySQL
database is very popular open-source database. It is generally
been stacked with apache and PHP, although it can be also stacked
with nginx and server side javascripting using Node js. The following
are some of MySQL benefits and strengths:
Replication: By replicating MySQL
database across multiple nodes the work load can be reduced heavily
increasing the scalability and availability of business application
Sharding: MySQL sharding os useful
when there is large no of write operations in a high traffic
website. By sharding MySQL servers, the application is partitioned
into multiple servers dividing the database into small chunks. As
low cost servers can be deployed for this purpose, this is cost
effective.
Memcached as a NoSQL API to MySQL:
Memcached can be used to increase the performance of the data
retrieval operations giving an advantage of NoSQL api to MySQL
server.
Maturity: This database has been
around for a long time and tremendous community input and testing
has gone into this database making it very stable.
Wide range of Platforms and
Languages: MySql is available for all major platforms like Linux,
Windows, Mac, BSD and Solaris. It also has connectors to languages
like Node.js, Ruby, C#, C++, C, Java, Perl, PHP and Python.
- Cost effectiveness: It is open source and free.
2. MS-SQL Server Express Edition
It is a powerful and user friendly database which has good
stability, reliability and scalability with support from Microsoft.
The following are some of MS-SQL benefits and strengths:
Integrated Development
Environment: Microsoft visual studio, Sql Server Management Studio
and Visual Developer tools provide a very helpful way for
development and increase the developers productivity.
Disaster Recovery: It has good
disaster recovery mechanism including database mirroring, fail over
clustering and RAID partitioning.
- Cloud back-up: Microsoft also provides cloud storage when you
perform a cloud-backup of your database
3. Oracle Express Edition
It is a limited edition of
Oracle
Enterprise Edition server with certain limitations. This database
is free for development and deployment. The following are some of
Oracle benefits and strengths:
Easy to Upgrade: Can be easily
upgraded to newer version, or to an enterprise edition.
Wide platform support: It supports
a wide range of platforms including Linux and Windows
- Scalability: Although the scalability of this database is not
cost effective as MySQL server, but the solution is very reliable,
secure, easily manageable and productive.
NoSQL Database Examples
1. MongoDB
Mongodb
is one of the most popular document based NoSQL database as it stores
data in JSON like documents. It is non-relational database with
dynamic schema. It has been developed by the founders of DoubleClick,
written in C++ and is currently being used by some big companies like
The New York Times, Craigslist, MTV Networks. The following are some
of MongoDB benefits and strengths:
Speed: For simple queries, it
gives good performance, as all the related data are in single
document which eliminates the join operations.
Scalability: It is horizontally
scalable i.e. you can reduce the workload by increasing the number
of servers in your resource pool instead of relying on a stand alone
resource.
Manageable: It is easy to use for
both developers and administrators. This also gives the ability to
shard database
- Dynamic Schema: Its gives you the flexibility to evolve your
data schema without modifying the existing data
2. CouchDB
CouchDB
is also a document based NoSQL database. It stores data in form of
JSON documents. The following are some of CouchDB benefits and
strengths:
Schema-less: As a member of NoSQL
family, it also have dynamic schema which makes it more flexible,
having a form of JSON documents for storing data.
3. Redis
Redis is another Open Source NoSQL
database which is mainly used because of its lightening speed. It is
written in ANSI C language. The following are some of Redis benefits
and strengths:
Data structures: Redis provides
efficient data structures to an extend that it is sometimes called
as data structure server. The keys stored in database can be hashes,
lists, strings, sorted or unsorted sets.
Redis as Cache: You can use Redis
as a cache by implementing keys with limited time to live to improve
the performance.
- Very fast: It is consider as one of the fastest NoSQL server
as it works with the in-memory dataset.
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