Unit III Key-Value Based Databases in nosql.pptx

Content
• Introduction to Key-Value Databases,
• Key Value Store,
• Essential Features, Consistency, Transactions, Partitioning, Scaling, Replicating Data, Versioning
Data,
• How to construct a Key, Using Keys to Locate Values, Hash Functions,
• Store data in Values, Use Cases.
Key-Value Based Databases
2

Introduction
• A key-value database is a type of
nonrelational database that uses a
simple key-value method to store
data.
• A key-value database stores data as
a collection of key-value pairs in
which a key serves as a unique
identifier. Both keys and values can
be anything, ranging from simple
objects to complex compound
objects.
• Key-value databases are highly
partitionable and allow horizontal
scaling at scales that other types of
3

• Akey-value database also known as a key-value store and key-value store
database is a type of NoSQL database that uses a simple key/value method to
store data.
• The key-value pair is a well established concept in many programming
languages. Programming languages typically refers to a key-value as an
associative array or data structure.
• Akey-value is also commonly referred to as a dictionary or hash.
Introduction
4

• Flexible data modeling:
• key-value store does not enforce any structure on the data, it offers tremendous
flexibility for modeling data to match the requirements of the application.
• High performance:
• Key-value architecture can be more performant than relational databases in many
scenarios, because there is no need to perform lock, join, union, or other operations
when working with objects.
• Unlike traditional relational databases, a key-value store does not need to search
through columns or tables to find an object. Knowing the key will enable very fast
location of an object.
Key-value Database Benefits
5

• Massive scalability:
• Most key-value databases makes it easy to scale out on demand using commodity
hardware. They can grow to virtually any scale without significant redesign of the
database.
• High availability:
• Key-value databases may make it easier and less complex to provide high availability .
• Some key-value databases use a masterless, distributed architecture that eliminates
single points of failure to maximise resiliency.
• Operational simplicity:
• it is as easy as possible to add and remove capacity as needed and that any hardware or
network failures within the environment do not create downtime.
Benefits-
6

• popular key-value databases are Riak, Redis (often referred to as Data Structure
server), Memcached , Berkeley DB, upscale dB, Amazon DynamoDB (not open-source), Project
Voldemort and Couchbase.
• All key-value databases are not the same, there are major differences between these products, for
example: Memcached data is not persistent while in Riak it is, these features are important when
implementing certain solutions.
• Let us consider we need to implement caching of user preferences, implementing them in memcached
means, when the node goes down all the data is lost and needs to be refreshed from source system, if we store
the same data in Riak, we may not need to worry about losing data.
Benefits-
7

• Key-Value Stores are a type of data store that organise data differently from your
traditional SQL store.
• The fundamental data model of a key-value store is the associative array (a.k.a. a map, a
dictionary or
a hash). It is a collection of key-value pairs, where the key is unique in the collection.
• Akey can be an ID or a name or anything you want to use as an identifier.
• Rather than storing data into a variety of tables and columns like in SQL stores, key-value
stores split a data model into a collection of data structures such as, key-value strings,
lists, hashes, sets, etc.
• Redis focuses on high performance and a simple querying language that is just a set of
data retrieval commands.
Key Value Stores
8

• The nature of key-value stores makes them best suited to operate as caches or data structure
stores and in situations that are performance sensitive.
• We can build more advanced data structures on top of key-value pairs. You can also use the
high performance to build queues or publish-subscribe mechanisms.
• Key-value stores fall into the NoSQL family of databases, they do not use SQL and
have a flexible schema.
• Application defines the key-value pairs and can change the definition at any time. We
decide how to store your data.
Key Value Stores
9

• Delete( key ): Delete the data that was stored under the “key”.
Aquick overview of key-value stores
• Key-value stores are one of the simplest forms of database. Almost all programming languages
come with in-memory key-value stores. The map container from the C++ STL is a key-value store,
just like the HashMap of Java, and the dictionary type in Python. Key-value stores generally share
the following interface:
• Get( key ): Get some data previously saved under the identifier “key”, or fail if no data was stored
for “key”.
• Set( key, value ): Store the “value” in memory under the identifier “key”, so we can access it later
referencing the same “key”. If some data was already present under the “key”, this data will be
replaced.
Key Value Stores
14

• Most underlying implementations are using either hash tables or some kind of self-
balancing trees, like B- Trees or Red-black trees. Sometimes, the data is too big to fit
in memory, or the data must be persisted in case the system crashes for any reason. In
that case, using the file system becomes mandatory.
• Key-value stores are part of the NoSQL movement, which regroup all the database
systems that do not make use of all the concepts coined by relational databases.
• Do not use the SQL query language.
• May not provide full support of theACID paradigm (atomicity, consistency, isolation,
durability).
• May offer a distributed, fault-tolerant architecture.
Key Value Stores
11

• Unlike relational databases, key-value stores have no knowledge of the data in
the values, and do not have any schema like in MySQL or PostgreSQL.
• This also means that, it is impossible to query only part of the data by doing any
kind of filtering, as it can be done in SQL with the WHERE clause.
• If you do not know where to look for, you will have to iterate over all the keys, get
their corresponding values, apply whatever filtering that you need on those values,
and keep only the ones you need.
Key Value Stores Limitations
12

• Full performance can only be attained in the cases where the keys are
known, otherwise key-value stores turn up to be simply inadequate .
• Therefore, even if key-value stores often outperform relational database
systems, by several orders of magnitude in terms of sheer access speed, the
requirement to know the keys restricts the possible applications.
Key Value Stores Limitations
13

• Transactions:
• While it is possible to offer transaction guarantees in a key value store, those are
usually offered in the context of a single key put.
• It is possible to offer those on multiple keys, but that really does not work when
you start thinking about a distributed key value store, where different keys may
reside on different machines.
• Some data stores offer no transaction guarantees.
Essential Features
14

Scaling up
• Key-value stores scale out by implementing partitioning (storing data on more than one
node), replication and auto recovery.
• They can scale up by maintaining the database in RAM and minimise the effects of
ACID guarantees (a guarantee that committed transactions persist
somewhere) by avoiding locks, latches and low-overhead server calls.
• The simplest way for key-value stores to scale up is to shard the entire key space. This
means that keys starting inA, go to one server, while keys starting with B go to another
server.
• In this system, a key is only stored on a single server. This drastically simplify things like
transactions guarantees, but it exposes the system for data loss if a single server goes down.
Essential Features
26

• Storing multiple copies of the same data in other servers, or even racks of servers, helps to
ensure availability of data if one server fails. Server failure happens primarily in the same
cluster.
• operate replicas two main ways :
• Master-slave:
• All reads and writes happen to the master. Slaves take over and receive requests only
if the master fails. Master-slave replication is typically used on ACID-compliant
key-value stores.
• To enable maximum consistency, the primary store is written to and all replicas are
updated before the transaction completes. This mechanism is called a two-phase
commit and creates extra network and processing time on the replicas.
Replication
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• Master-master:
• Reads and writes can happen on all nodes managing a key. There’s no concept of a
“primary” partition owner.
• Master-master replicas are typically eventually consistent, with the cluster
performing an automatic operation to determine the latest value for a key and
removing older, stale values.
• In most key-value stores, this happens slowly — at read time. Riak is the exception
here because it has an anti-entropy service checking for consistency during normal
operations.
Replication
17

• To enable automatic conflict resolution, you need a mechanism to indicate the latest
version of data. Eventually consistent key-value stores achieve conflict resolution in
different ways.
• Riak uses a vector-clock mechanism to predict which copy is the most recent one.
• Other key-value stores use simple timestamps to indicate staleness.
• When conflicts cannot be resolved automatically, both copies of data are sent to the client.
• Conflicting data being sent to the client can occur in the following situation:
• 1. Client 1 writes to replica A ‘Adam: {likes: Cheese}’.
• 2. Replica A copies data to replica B.
• 3. Client 1 updates data on replica A to ‘Adam: {likes: Cheese, hates: sunlight}’.
At this point, replica A doesn’t have enough time to copy the latest data to replica B
Versioning data
18

• 4. Client 2 updates data on replica B to ‘Adam: {likes: Dogs, hates: kangaroos}’.
• At this point, replica A and replica B are in conflict and the database cluster cannot
automatically resolve the differences.
An alternative mechanism is to use time stamps and trust them to indicate the latest data
In such a situation, it’s common sense for the application to check that the time stamps read
the latest value before updating the value. They are checking for the check and set mechanism,
which basically means ‘If the latest version is still version 2, then save my version 3’.
This mechanism is sometimes referred to as read match update (RMU) or read match write
(RMW).
This mechanism is the default mechanism employed by Oracle NoSQL, Redis, Riak, and
Voldemort.
Versioning data
19

What can a Key-Value Database be used for?
Key-value databases can be applied to many scenarios. For example, key-value stores can be useful
for storing things such as the following:
General Web/Computers
• User profiles
• Session information
• Article/blog comments
• Emails
• Status messages
20

E-commerce
• Shopping cart contents
• Product categories
• Product details
• Product reviews
Networking/Data Maintenance
• Telecom directories
• Internet Protocol (IP) forwarding tables
• Data deduplication
• Key-value databases can even store whole webpages, by using the URL as the key and the web
page as the value.
21

clones which feature eventual consistency.
Use Cases
• Complex transactions because you cannot afford to lose data or if you would like a simple transaction
programming model, then look at a relational or grid database.
• Example: An inventory system that might want full acid. I was very unhappy, when I bought a
product and they said later they were out of stock. I did not want a compensated transaction. I
wanted my item!
• To scale, then nosql or sql can work. Look for systems that support scale-out, partitioning, live
addition and removal of machines, load balancing, automatic sharding and rebalancing, and fault
tolerance.
• To always be able to write to a database because, you need high availability then look at bigtable
39

• To handle lots of small continuous reads and writes, that may be volatile, then look at document or
key-value or databases offering fast in-memory access.Also consider SSD.
• To implement social network operations, then you first may want a graph database or second, a
database like riak that supports relationships.An in-memory relational database, with simple SQL
joins might suffice for small data sets. Redis' set and list operations could work too.
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1. Define Key Value and write a note on Key Based Database.
2. Explain the essential features in NoSQL.
3. Describe Partitioning and Scaleup.
4. How to construct KEY and Store Key Value.
5. Explain Hash Functions.
6. Explain the concept of Store in Data values
Assignment
General Instructions:
Please answer the below set of questions.
i. The answers should be clear, legible and well presented.
ii. Illustrate your answers with suitable examples wherever necessary.
iii. Please provide sources (if any) for data, images, facts, etc.
66

Assignment (Cont…)
7. Does NoSQL Database Interact With Oracle Database?
8. When should I use a NoSQL database instead of a relational database?
9. Could you explain the transaction support by using BASE in NoSQL systems?
10. What is the difference between NoSQL and RDBMS?
11. Tell me the challenges of using NoSQL?
12. Difference with NOSQLVS Relational
25

Unit III Key-Value Based Databases in nosql.pptx

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Unit III Key-Value Based Databases in nosql.pptx