Posts Tagged ‘nosql’

What are some commercial and free open-source types of NoSQL databases?

January 26th, 2013 No comments

When you want to invest in the commercial databases, you need to make sure that you settle with some of the best in the market. You should have the ability to know the performance and take time to choose the best.

CouchDB – Document Store

Maps keys to data

It provides a RESTful JSON API and is written in Erlang

You can upload functions to index data and then you can call those functions

Has a very simple REST interface

Provides an innovative replication strategy – nodes can reconnect, sync, and reconcile differences after being disconnected for long periods of time

Enables new distributed types of applications and data

MongoDB – Document Store


Free-form key-value-like data store with good performance

Powerful, expansive query model

Usability rivals that of Redis

Good for complex data storage needs.

Production-quality sharding capabilities


Neo4j – GraphDB



Has a restricted, single-threaded model for graph traversal

Has optional layers to expose Neo4j as an RDF store

Can handle graphs of several billion nodes, relationships, or properties on a single machine

Released under a dual license – free for non-commercial use

Apache Hbase – Wide Column Store/Column Families

Built on top of Hadoop, which has functionality similar to Google’s GFS and MapReduce systems

Hadoop’s HDFS provides a mechanism that reliably stores and organizes large amounts of data

Random access performance is on par with MySQL

Has a high performance Thrift gateway

Cascading source and sink modules


Redis – Key Value/Tuple Store


Provides a rich API and does more operations in memory, using disk only periodically.

It’s extremely fast

Lets you append a value to the end of a list of items that’s already been stored on a key.

Has atomic operations, making it a best-of-breed tally server.


Memcached – Key Value/Tuple Store


High-performance, distributed memory object caching

Free and open source

Generic and agnostic to the objects/strings it caches

It’s all in-memory data

Simple yet elegant design enables easy development and deployment

Language neutral caching scheme.

Most of the large properties on the web are using it now, except for Microsoft



Project Voldemort – Eventually Consistent Key Value Store


Used by LinkedIn

Handles server failure transparently

Pluggable serialization supports rich keys and values including lists and tuples with named fields

Supports common serialization frameworks including Protocol Buffers, Thrift, and Java Serialization

Data items are versioned

Supports pluggable data placement strategies

Memory caching and the storage system are combined



Tokyo Cabinet and Tokyo Tyrant – Key Value/Tuple Store


Supports hashtable mode, b-tree mode, and table mode

It’s fast and straightforward

Good for small to medium-sized amounts of data that require rapid updating and can be easily modeled in terms of keys and values



Cassandra – Wide Column Store/Column Families


First developed by Facebook

SuperColumns can turn  simple key-value architecture into an architecture that handles sorted lists, based on an index specified by the user.

Can scale from one node to several thousand nodes clustered in different data centers.

Can be tuned for more consistency or availability

Smooth node replacement if one goes down

Categories: NoSQL Tags:

Top 10 most popular books on the NoSQL architecture

January 23rd, 2013 No comments

When you want to get more details about NOSQL, it is important to have a descriptive look into the books and this makes it easier for one to get the latest versions and models in the creating of this database.

The importance of getting the book is the ability for one to settle with the best descriptions and this means to nothing but the best results. You only need to settle with the best offers in the market can choose the books that have been verified to give you nothing but the best results. Some of the books include-

1] Refactoring: improving the design of existing code- this books is written by martin flower, and describes the different opportunities that the refactoring assistance and how to find it. This is suitable for people who are doing the NOSQL programing basis and gives then the refactoring steps in the developmental

2] Ubuntu unleashed 2012: covering 11.10 and 12.04 written by Matthew Helmke. This is a guide to the Ubuntu operating system covers such topics as installation and configuration, productivity applications, the command line, managing users, networking, remote access, security, kernel, and module management


3] Google APPs, the missing manual by Nancy Conner

This book shows these applications together can ease your ability to collaborate with others, and allow you access to your documents, mail and appointments from any computer at any location. Link-

4] Hadoop- the definitive guide by Tom White –

It offers illuminating case studies that illustrate how Hadoop is used to solve specific problems. Link-

5] Patterns of Enterprise Application Architecture by Martin Fowler

This book is actually two books in one. The first section is a short tutorial on developing enterprise applications, which you can read from start to finish to understand the scope of the book’s lessons. Link-

6] CouchDB: The Definitive Guide: The Definitive Guide by Chris Anderson, Jan Lehnardt, Noah Slater

This book, shows how to work with CouchDB through its RESTful web interface, and become familiar with key features such as simple document CRUD (create, read, update, delete), advanced MapReduce, deployment tuning, and more. Link-

7] Maven: The Definitive Guide


Written by Sonatype Company – 2008 – Preview

This is one of the descriptive guides that show one the effectiveness of all the NOSQL processes. To use Maven, everything you need to know is in this guide.

8] MongoDB in Action


Written by Kyle Banker –

MongoDB in Action is a comprehensive guide to MongoDB for application developers. The book begins by explaining what makes MongoDB unique and describing its ideal use cases.

9] Professional NoSQL

Written by Shashank Tiwari – 2011

They provide examples, practical solutions, and expert education in new technologies, all designed to help programmers do a better job. Programmer Forums Join our Programmer to Programmer forums to ask and answer programming …

10] Core Python Programming: Text

Written by Wesley Chun – 2001

New to Python? This is the developer’s guide to Python development!



Categories: NoSQL Tags:

What are the origins of NoSQL database? Where did it get started?

January 7th, 2013 No comments

This article focuses on the developmental stages of the NOSQL database and reasons that let to formation of it to date


MultiValue (aka PICK) databases are developed at TRW in 1965.

It is a programming language, that incorporates a hierarchical database with B+ tree storage.  IBM IMS, a hierarchical database, is developed with Rockwell and Caterpillar for the Apollo space program in 1966.


InterSystems developed the ISM product family succeeded by the Open M product, all M[umps] implementations.  In 1979 Ken Thompson creates DBM which is released by AT&T.


TDBM supporting atomic transactions

NDBM was the Berkeley version of DBM supporting having multiple databases open at the same time.

SDBM – another clone of DBM mainly for licensing reasons.

GT.M is the first version of a key-value store with focus on high performance transaction processing.

BerkeleyDB reated at Berkeley in the transition from 4.3BSD to 4.4BSD. Sleepycat software is started as a company in 1996 when Netscape needed new features for BerkeleyDB.


GDBM is the Gnu project clone of DBM

Mnesia is developed by Ericsson as a soft real-time database to be used in telecom. It is relational in nature but does not use SQL as query language but rather Erlang itself

InterSystems Caché launched in 1997 and is a hybrid so-called post-relational database. It has object interfaces, SQL, PICK/MultiValue and direct manipulation of data structures. It is a M[umps] implementation. See Scott Jones comment below for more on the history of InterSystems


Graph database Neo4j is started in 2000.

db4o an object database for java and .net is started in 2000

QDBM is a re-implementation of DBM with better performance by Mikio Hirabayashi.

Memcached is started in 2003 by Danga to power Livejournal. Memcached is not really a database since it’s memory-only but there is soon a version with file storage called memcachedb.

Infogrid graph database is started as closed source in 2005, open sourced in 2008

CouchDB is started in 2005 and provides a document database inspired by Lotus Notes. The project moves to the Apache Foundation in 2008.

Google BigTable is started in 2004 and the research paper is released in 2006.


JackRabbit is started in 2006 as an implementation of JSR 170 and 283.

Tokyo Cabinet is a successor to QDBM by (Mikio Hirabayashi) started in 2006

The research paper on Amazon Dynamo is released in 2007.

The document database MongoDB is started in 2007 as a part of a open source cloud computing stack and first standalone release in 2009.

Facebooks open sources the Cassandra project in 2008

Project Voldemort is a replicated database with no single point-of-failure. Started in 2008.

Dynomite is a Dynamo clone written in Erlang.

Terrastore is a scalable elastic document store started in 2009

Redis is persistent key-value store started in 2009

Riak Another dynamo-inspired database started in 2009.

HBase is a BigTable clone for the Hadoop project while Hypertable is another BigTable type database also from 2009.




Categories: NoSQL Tags:

Top 15 examples NoSQL database being used with PHP programming language?

January 2nd, 2013 1 comment


(UniVerse, UniData): MultiValue Databases, Data Structure: MultiValued, Supports nested entities, Virtual Metadata, API: BASIC, InterCall, Socket, .NET and Java API’s, IDE: Native, Record Oriented, Scalability: automatic table space allocation, Protocol: Client Server, SOA, Terminal Line, X-OFF/X-ON, Written in: C, Query Method: Native mvQuery, (Retrieve/UniQuery) and SQL, Replication: yes, Hot standby, Concurrency: Record and File Locking (Fine and Coarse Granularity)


API: Basic+, .Net, COM, Socket, ODBC, Protocol: TCP/IP, Named Pipes, Telnet, VT100. HTTP/S Query Method: RList, SQL & XPath Written in: Native 4GL, C, C++, Basic+, .Net, Java Replication: Hot Standby Concurrency: table &/or row locking, optionally transaction based & commit & rollback Data structure: Relational &/or MultiValue, supports nested entities Scalability: rows and tables size dynamically


(Northgate IS): The original MultiValue data set database, virtual machine, enquiry and rapid development environment. Delivers ultra efficiency, scalability and resilience while extended for the web and with built-in auto sizing, failsafe and more. Interoperability includes Web Services, Java Classes, XML, ActiveX, Sockets, C and, for those that have to interoperate with the SQL world, ODBC/JDBC and two-way transparent SQL data access.


Supports nested data. Fully automated table space allocation. Concurrency control via task locks, file locks & shareable/exclusive record locks. Case insensitivity option. Secondary key indices. Integrated data replication. QMBasic programming language for rapid development. OO programming integrated into QMBasic. QMClient connectivity from Visual Basic, PowerBasic, Delphi, PureBasic, ASP, PHP, C and more. Extended multivalue query language.


(by Microsoft) ISAM storage technology. Access using index or cursor navigation. Denormalized schemas, wide tables with sparse columns, multi-valued columns, and sparse and rich indexes. C# and Delphi drivers available. Backend for a number of MS Products as Exchange.

non-blocking ingest, Misc: Free for Qualified Startups.


API: Java, http/REST, Protocol: as API + XPRISO, OpenID, RSS, Atom, JSON, Java embedded, Query Method: Web user interface with html, RSS, Atom, JSON output, Java native, Replication: peer-to-peer, Written in: Java, Concurrency: concurrent reads, write lock within one MeshBase, Misc: Presentation »


API: Java (and Java Langs), Written in:Java, Query Method: Java or P2P, Replication: P2P, Concurrency: STM, Misc: Open-Source, Especially for AI and Semantic Web.


: API: Java, .NET, C++, Blueprints Interface Protocol: Embedded, Query Method: APIs (Java, .Net, C++) + Gremlin (via Blueprints), Written in: C++, Data Model: Labeled Directed Attributed Multigraph, Concurrency: yes, Misc: Free community edition up to 1 Mio nodes, Links: Intro », Tutorial »


Sub-graph-based API, query language, tools & transactions. Embedded Java, remote-proxy Java or REST. Distributed storage & processing. Read/write all Nodes. Permissions & Constraints frameworks. Object storage, vertex-embedded agents. Supports multiple graph models. Written in Java


API: C#, Protocol: C# Language Binding, Query Method: Graph Navigation API, Replication: P2P with Master Node, Written in: C#, Concurrency: Yes (Transactional update in online query mode, Non-blocking read in Batch Mode) Misc: distributed in-memory storage, parallel graph computation platform (Microsoft Research Project)


API: Java, Python, Ruby, C#, Perl, Clojure, Lisp Protocol: REST, Query Method: SPARQL and Prolog, Libraries: Social Networking Analytics & GeoSpatial, Written in: Common Lisp, Links: Learning Center », Videos »


A native, .NET, semantic web database with code first Entity Framework, LINQ and OData support. API: C#, Protocol: SPARQL HTTP, C#, Query Method: LINQ, SPARQL, Written in: C#


API: Java, Jini service discovery, Concurrency: very high (MVCC), Written in: Java, Misc: GPL + commercial, Data: RDF data with inference, dynamic key-range sharding of indices, Misc: Blog » (parallel database, high-availability architecture, immortal database with historical views)


RDF enterprise database management system. It is cross-platform and can be used with most programming languages. Main features: high performance, guarantee database transactions with ACID, secure with ACL’s, SPARQL & SPARUL, ODBC & JDBC drivers, RDF & RDFS. »

OpenLink Virtuoso

Hybrid DBMS covering the following models: Relational, Document, Graph

Categories: NoSQL, PHP Tags:

Top 10 Reasons why you should use Relational over NoSQL databases

December 31st, 2012 No comments

With the introduction of NOSQL database, many people find that it is easier to shift to these databases but this does not mean they will get all the solutions that they need. It is still important to settle with the relational databases due to a number of reasons and some of the developers find that it is easy to stick to the system.

  1. With the relational database, one is investing in a low-volume and less complex applications, which makes it easier for them to handle and this means they can start to develop this application in a matter of time
  2. With the chance to do normalization with relational database, you find that it is effect to have the duplicated volumes of data in the system that you want
  3. Switching to another database is not an easy process since you have already invested in this program, bought the services. This means that you have to let go, learn a new system, and in most cases, you find that it does not solve all the matters, that you want and this means you have to go back to the SQL method. You need to learn and find what other developers have to say before you switch to a new system
  4. Just because a system is popularized by the search engine and has good marketing methods done online, does not mean that you have the chance to trust it. This is the reason why one needs to go through the reviews and find the reasons why they need to stick to the system and if they have to switch to NOSQL< the benefits they get over the relational methods
  5. Before investing in a new system, many people find that it will not meet their needs, and gets trickier to start learning another language and develop it. This is why one needs to stick to the database they have since all have faults but one has managed to stay with them due to the effectiveness and ability to control them regardless of their issues
  6. Relational databases are known to have the best declarative syntax and strong mathematical basis compared to other systems in the market.
  7. Relational databases have a well-known language known as structured query language in short, SQL
  8. Relational databases have a good existing ecosystem introduced into the channel and this means the documentation, third party vendors, binding to other programming languages, and loads of tools.
  9. Relational databases have the ability to host different bonuses like geographical databases and mechanism
  10. The relational database offers different indexing solutions, trustworthy transactional details, and extensive security installations.

Before one settles with any new system, they need to find more about the qualities and start the comparison process. Many people want to stick with relational methods due to the programming language, the effectiveness in the security methods, easy procedures and the chance to have the developing structures in place and center the programming language to the method that developer wants, making it hard for other people to crack the codes installed.


Categories: General, mysql, NoSQL Tags: , , ,

Top 10 most popular video tutorials on NoSQL

December 29th, 2012 No comments

These are some of the top rates YouTube videos on the suitable tutorials that will make it easy it for you to have the opportunity to understand more about the programs since they have the photos, examples and integral look at the definition of terms used in this program.

  1. NoSQL Database Tutorial part1 | Introduction to NoSql

This tutorial offers some of the best introduction details to the people who want to learn more about the NOSQL details. It makes it easier for one to have the full understanding of the process and this becomes easier for one to understand the correct ways they will use when they want to start activating this system.





This shows the difference that one will get when they settle with the new database method and over from the other SQL method of programming



3. hadoop and NOSQL downfall parody

This shows the ability for investing in the NOSQL database, and it gives the technical stuff and this enables one to have the basic details about the database that are in use and ends up comparing them in order to find the ones that are suitable for the different users



4. Row, column, NOSQL and Hadoop- when to use and where

This video shows the relation between the database, that are in the NOSQL method and some of the ways that will make it easier for them to start investing in it. Most of the developers want to find out some of the details that make it easier for them to settle with good results but with the ability to settle with top-notch results and this video starts to showcase all different settings, and one ends up knowing when to use the different applications.



5. NOSQL- this shows the details about the database by giving a description on some of the examples that leads one to know more about the terms, and familiarize with the system. This is one of the best videos, which make to easier for one to understand this database.

6.  handlerSocket: NOSQL via MUSQL- this is one of the simplified version that make it possible for anyone who wants to know more about this database to understand more about it.



7. NOSQL database tutorial part 4/ c# and cloud based mongodb using orchestra php platform

This allows you to understand the different platforms that you can use when operating this databases



8. datastax Cassandra tutorials-datastax opscenter overview

This is a newer version that many people do not know about but it has all the key details that one needs to know in order to have the deeper understanding of this program



9. Datastax webinar-NOSQL for big data in the enterprise

This is dedicated to the people who want to have the larger platform to understand bigger operational database systems



10. NOSQLdistilled a brief guide to the emerging world of polyglot persistence

This gives an integral and detailed look to enable one get the details of NOSQL database and some of the different ways that you can use them.



Categories: NoSQL Tags:

How does NoSQL database work?

December 27th, 2012 No comments

NoSQL database is new introduction in the system but this does not mean it started the other day. In fact, it has been there for a long time but many developers were focused on the mathematical programming language and did not want to invest in other new systems. However, with time, this changed and it became easier for them developers to start using it. This started to gain momentum and with time, most of the developers started to favor it from the other programming options due to the effectiveness and the ability to encompass a large data storage and high level of monitoring tools

What is NoSQL
this is a systematic special system, that allows loading of new data and storage of backups and they do not follow the relational DB model. This means that you do not have it master the mathematical language, which becomes harder for one to invest when merging in the developing world.

How does it work?

There are more them 150 current NOSQL databases available in the market and some of them are being developed currently. This makes it easier for one to choose the one that they want, since some are suitable for small developers and some for large-scale developers. The systems are labeled with generic name and this works differently in the sense of scalability. One does not need to have enough memory space in order to support this system. You only need to keep on replicating the data and you will find that the message is stored and this saves you on the memory space. This is one of the best descriptions that make many people prefer to use the NOSQL database. Often more characteristics apply such as: schema-free, easy replication support, simple API, eventually consistent / BASE (not ACID), a huge amount of data and more.


Delivers ultra-efficiency, scalability and resilience while extended for the web and with built-in auto sizing, fail safe and more. Interoperability includes Web Services, Java Classes, XML, ActiveX, Sockets, C and, for those that have to interoperate with the SQL world, ODBC/JDBC and two-way transparent SQL data access.

Handel big data- the NOSQL database makes it easier for one to handle big data, which means that it can handle the revolution of data and this is suitable for people who have numerous data to handle, and this makes it easier for them to store, update, change, and retrieve without blocking the system from basic operations.

Handel big data- the NOSQL database makes it easier for one to handle big data, which means that it can handle the revolution of data and this is suitable for people who have numerous data to handle, and this makes it easier for them to store, update, change, and retrieve without blocking the system from basic operations.

Is it effective?

Experts’ advice developers need to keep in mind a number of different options when dealing with databases. It is not easy to choose the right NOSQL database to use due to their expansiveness but this does not mean they will get the results they want.

Categories: NoSQL Tags:

MongoDB Sharding, how to do sharding

December 21st, 2012 No comments

MongoDB Sharding systems give users the platform to partition an entire collection in a simple database form and distribute it to documents in the MongoDB instances or in simpler terms shards. This enables the writing capacity to increase and provides the ability to support the volumes of working set. This raises the limits of data size much higher beyond physical resources in a single node.

Features of sharding

Range-based data partitioning

MongoDB describes data in shards, according to the value of the shard key. Each represents a single block of documents that lie in a specific range. When the volume grows bigger, the MongoDB splits the shards into other smaller chinks known as splitting

Automatic data volume distribution

The system balances data automatically in all areas in the cluster and prevents intervention in the application layer. It does not need any additional features in modification or any developmental interventions.

Transparent Query routing

Transparency in sharding is because of connections in the cluster, which go through the MongoDB, and only requires basic configuration for the application to run smoothly.

A sharded cluster comprises of replica sets, which hold data, lightweight routing process and three configurations sever to store the data.

The process

This is the process of creating multiple shreds in order to facilitate storage of large data volumes. It is easy to multiply and backup data in several servers for easy retrieval and use.

  1. Start up the new machine in the process
  2. Install the MongoDB program, and start a new process which acts as the shard cluster for the storage of data
  3. Create another new process and this acts as the configuration which maintains and verifies the information given
  4. Start the process of sharding as directed by the program, and use mongo to find the current db,
  5. Enter the commands that enable sharding of collections and database you have.
  6. Modify all the applications to activate the MongoDB Sharding process and update the system.
  7. The configuration process is automatic and done through the IP

When to apply sharding

You do not need to apply sharding all the time and is usually applicable when you have a number numerous volumes of data. This a significant infrastructure development but you have the chance to deploy the operation when

–          Your data set exceed the limited capacity of your single node system

–          When you have volumes of writing activity in a single MongoDB and the process is slowing down and unable to meet your demands.

–          The current working set will not fit into your RAM system and you do not want to stop the process

When installing the MongoDB Sharding, you need to make sure that you follow the correct processes especially in configuration since this can delete all information in the indexes and servers when you do not use the correct handles. This is the reason why you need to customize your MongoDB and have numerous servers that will store extra memory details to prevent massive data loss. This process makes it easy to deal with massive production and you do not need to stop the working set in order to increase your memory space.


Categories: MongoDB Tags: , ,

Top 10 Reasons why you should use NoSQL over Relational databases

December 19th, 2012 No comments

The latest development currently in the market for developers is the NOSQL database but this does not mean that one should not use the other methods to access the data. You have the chance to start investing in the database that you need but some developers are finding it effective to move from the relational database and start choosing the NPSQL method. Some of the reasons include

  1. Elastic scaling- tone does not need to keep on investing in the bigger servers, when they want to increase the information, which is common with relational system. You only need to scale out, which means that you source the database, accessing several hosts, when there is increase of data. This means that you can handle volumes of data in a short memory space, and this saves on the costs of installing new hardware servers and memory space, which is hard for one to get the optimum results.
  2. Handel big data- the NOSQL database makes it easier for one to handle big data, which means that it can handle the revolution of data and this is suitable for people who have numerous data to handle, and this makes it easier for them to store, update, change, and retrieve without blocking the system from basic operations.
  3. Less repairs and monitoring- most of the companies do not want o incur extra costs when dealing with the databases. With SQL, one needs to keep on monitoring the system virtual data distribution and repairs. This also involves updating the servers and the memory space, placing it at result of losing details when not stored in the correct manner. With NOSQL, the system has automatic monitoring methods, which allows the user to apply the command settings in the best way they want to monitor and handle the system.
  4. Cost effective- NOSQL database makes it easier for one to have the economic sense of not investing in multiple servers and upgrades of the mathematical programming language. With different severs to use with the relational method, users are at risk when they do not backup data when updating and this means one should have multiple servers for the upgrading sessions to avoid losing information.
  5. Flexible data modes- it is easier for one to choose the keys they want to operate and upgrades are done on the system when one has installed the command
  6. Less input of data- one does not need to be at the system in order to access all the information or have the upgrades the system still runs automatically
  7. Easy to use commands- there are different commands making it easier for one to automatic selections, and minimizes time spend on doing routine process
  8. Expertise- one does not need to become a programming expert since this does not need one to master all the mathematical languages to develop a system
  9. High level of security- with multiple servers to operate from several locations, the database only allows authorized access making it safer to store the data
  10. Updating tools- unlike the relational method, you do not need to worry about losing data when updating since it has the automatic upgrading tools to update and save data.



Categories: NoSQL Tags:

What are 5 key differences between Relational and NoSQL databases?

December 19th, 2012 No comments

Ever since the development of NOSQL databases, many people find it hard if they should settle with them or not. It is important to have an integral look at the different reasons to choose one over the other. The relational or the SQL databases have been in the market for long but due to the recent developments in the market, you find that many people prefer to choose the ones that have the adaptability features.



  1. Relational databases or SQL databases are relational meaning that it uses the frequency of tables and relations. This works by using them to match data by use of several characteristics known as Schema. This is through the division in terms of rows and columns The NOSQL databases do not need to use the schema or the tables in order to operate but scale horizontally. This means that the database has a structured system.
  2. NOSQL database have the integrated caching method, which means they have to increase the memory, and this increases the performance. This technique makes it easier to use the cache data technique to install the system memory The SQL databases do not have the integrated caching method and this is done using a separate infrastructure.
  3. With relational, when the data does not fit into the tables and columns, one need to create another database structure and this is a complex work, which takes time and effort. With NOSQL databases, it accommodates the formation of additional features into the system even when adding new data, since the infrastructure is defined.
  4. With relational databases, the uses need to scale on powerful servers and this is an expensive cost and this means that one has to keep on investing in new ones and connect to operate multiple servers, which becomes harder to manage. The NOSQL database uses the replica method and this means automatic increases of the memory, and easy to operate different servers at the same time without limiting the current operations.
  5. NOSQL has auto elasticity and this means that one has the chance to automatically update the different servers from any location and use different commands to aid in the process. When dealing with relational databases, a simple mistake in the update on the servers, risks deleting the entire information.


Both databases have the ability to handle effective data storage and the retrieval process. They both have integrated security levels and this makes it easier for a company to store the information safer due to restricted access. Both have the chance to handle data storage and easy access especially when dealing with multiple servers.

It is important for a developer to understand the operation of both databases and this makes it easier for them to know the ones, which are suitable based on their needs. Both have positive and negative sides, making it easier for one to choose the ones that will satisfy their needs in the best way they can expound, and relate it to the work they want to do. Due to future technical enhancements, developers need to adjust to the new settings and choose the one that fits their infrastructure


Categories: NoSQL Tags: