Database Management and Administration Developer with NoSQL Salary in 2024

Where is NoSQL used?

Feeding Time at the Social Media Zoo

• These digital jungles use NoSQL to keep millions of critters—ahem, user profiles—munching through feeds without a hiccup.

Gaming Gardens Grow with NoSQL

• Gamers plant seeds of victory in online arenas where NoSQL fertilizes real-time scores and beat-the-clock data sprouts.

E-commerce Vines Twisting through NoSQL

• NoSQL is the trellis for climbing e-commerce vines, ensuring that shopping carts don't tumble when customers go grape-crazy on sales.

The Library of Babble: Cataloging with NoSQL

• In the world’s most hush-hush library, NoSQL is the silent librarian categorizing books and user queries faster than a shush!

NoSQL Alternatives

SQL Databases

Structured Query Language (SQL) databases are relational, table-based systems designed for complex queries with ACID compliance. Examples: MySQL, PostgreSQL.

-- Example SQL query
SELECT * FROM users WHERE age > 20;

• Strong consistency model

• Complex query capabilities with JOIN operations

• Mature with extensive tooling

• Can be less scalable for write-heavy applications

• Rigid schema can impede agility in rapidly evolving datasets

• May underperform in big data scenarios

In-Memory Data Stores

In-memory data stores offer rapid data access by holding data in RAM. They are used for caching and real-time analytics. Examples: Redis, Memcached.

-- Example Redis command
SET user:1000 "John Doe"

• Extremely fast read/write operations

• Flexible data structures

• Great for ephemeral data and caching

• Data may be lost on power failure if not persisted

• Limited storage capacity tied to RAM size

• Often used alongside other DBs due to volatility

NewSQL Databases

NewSQL databases aim to provide the scalability of NoSQL while maintaining the ACID guarantees of traditional SQL databases. Examples: Google Spanner, CockroachDB.

-- Example NewSQL syntax (CockroachDB)
BEGIN;
UPDATE accounts SET balance = balance - 100 WHERE id = 1;
UPDATE accounts SET balance = balance + 100 WHERE id = 2;
COMMIT;

• Scalability with consistency

• Advanced features for distributed computing

• SQL interface for relational data handling

• Might be more complex to administer

• Can be cost-prohibitive for small-scale applications

• Newer, with less established community

Quick Facts about NoSQL

NoSQL Databases: The Non-Conformists of Data Storage

Once upon a not-so-distant past in the year 1998, Johan Oskarsson flicked a switch in the world of databases when he organized an event named after Carlo Strozzi’s brainchild, the 'NoSQL' database. NoSQL cheekily stood as the antithesis to SQL's structured query language strictness, waving goodbye to rigid schemas and embracing flexibility like a hippie loves tie-dye.

Viva la Evolución: The Rise of Schema-less Storage!

Faster than a speeding query, NoSQL databases like MongoDB, released in 2009, championed the document model, yanking away the relational database’s necessity for predefined schemas. This was akin to a software whisperer gently saying to the data, "Be free, my structured friends!" and oh, how they danced. They also made friends with JSON and BSON, two formats that help them play nice with web applications.

{
  "firstName": "Zero",
  "lastName": "Schemas",
  "contact": {
    "email": "free@data.com",
    "phone": "123-456-7890"
  }
}

MongoDB and the Curious Case of Version 5.0

Leaping through time to 2021, MongoDB introduced its version 5.0 with Live Resharding, which is basically the database's way of saying, "You know what? I can change my mind whenever I feel like it." This allows admins to rejig the data’s distribution across a cluster without downtime—a feat similar to changing the tires on a moving car while blindfolded. Also, it acquired some time series collection abilities, for all those who like their databases with a side of foretelling the future.

db.runCommand( { reshards: 'user_data', key: { userId: 1 } } )

What is the difference between Junior, Middle, Senior and Expert NoSQL developer?

Top 10 NoSQL Related Tech

1. 
   

   JavaScript (of The NoSQL Persuasion)

   
   

   
   Picture this: you're frolicking in the NoSQL meadow, and there stands JavaScript, the unicorn of programming languages. Omnipresent in web development, it prances its way into NoSQL land with its trusty companions Node.js and JSON. Why? Because when you're dealing with unstructured data, you need a language that doesn't raise its eyebrow at a little chaos. JavaScript says, "Array of objects as a database? Pfft. Watch me." And indeed, we do.

   
   

   
               db.superheroes.find({ capeColor: "red" })
           

1. 
   

   Node.js (Server-side Shenanigans)

   
   

   
   Ah, Node.js, where JavaScript sheds its browser-only cape and takes on server-side quests! With this event-driven knight, you'll trot through I/O operations without ever breaking into a gallop, because who has the time for that? Plus, npm—with its treasure trove of packages—lets you arm yourself with tools like Mongoose. Getting cozy with MongoDB was never more straightforward. Mmm, the smell of asynchronous code in the morning!

   
   

   
               npm install mongoose --save
           

1. 
   

   MongoDB (The Document Store Darling)

   
   

   
   Enter MongoDB, the hipster of databases, snubbing rows and columns for documents and collections since 2009. Why stifle your data in rigid schemas when it can be as free as a JSON-like BSON document? Here, your agile data dons a leather jacket and hops onto a schema-less motorcycle, ready to zip and zoom without a care for structure. And with operators like $match and $group, aggregations are slicker than a greased handlebar mustache.

   
   

   
               db.inventory.aggregate([ { $group: { _id: "$item", total: { $sum: "$qty" } } } ])
           

1. 
   

   Redis (The Speedy Keystore Wizard)

   
   

   
   Watch out! Redis is zipping by, casting spells of sub-millisecond response times with its enchanting in-memory data structure store. Most known for its cache magic, Redis plays peekaboo with data structures like strings and hashes that virtually whisper, "Seeya SQL, hello speed!" And let's not forget about Pub/Sub, where messages are passed around like notes in magic school—fast and reliable.

   
   

   
               SET superpower "invisibility"
               GET superpower
           

1. 
   

   Cassandra (The High-availability Herald)

   
   

   
   Cassandra strides in, her head held high, boasting availability and fault-tolerance fit for battle. She crafts a tapestry of decentralized, peer-to-peer nodes that scoffs at single points of failure. With her, your data sets sail across a Viking fleet of servers, partitioned and replicated like plunder. CQL might echo SQL's song, but make no mistake, it dances to a different tune—a bolder, wider-reaching choreography.

   
   

   
               SELECT * FROM vikings WHERE name = 'Ragnar';
           

1. 
   

   Apache HBase (The Bigtable Benefactor)

   
   

   
   Oh, the grand Apache HBase, inspired by Google's Bigtable and part of the Hadoop family! Imagine a banquet hall of never-ending tables with rows stretching to the horizon. This is the realm of sparse, distributed, multidimensional maps indexed by a rowkey. Wield Column Families like a royal scepter, and partition your kingdom's data with preordained reverence. Big Data, meet your roomy abode.

   
   

   
               scan 'epicTales'
           

1. 
   

   Couchbase (The Cluster Conductor)

   
   

   
   The maestro of seamless scaling, Couchbase, conducts a symphony where every node is first chair. Here's a document database that strolls nonchalantly through both cache and store, keeping JSON-documents at the heart of a meticulously replicated and sharded cluster. Tame these wild clusters with N1QL, and dock RESTful APIs like ships at its versatile ports. The crescendo? A performance that scales elastically to rapturous applause.

   
   

   
               SELECT airportname, city, country FROM `travel-sample` WHERE type="airport" AND city="London";
           

1. 
   

   Elasticsearch (The Full-text Search Sorcerer)

   
   

   
   Need to conjure search results faster than you can say "abracadabra"? Elasticsearch enters with a twirl of his wand—the revered full-text search engine, tailored for horizontal scalability, reliability, and a real knack for real-time indexing. Juggling JSON documents with ease, this wizard enchants with RESTful spells and search queries that can pinpoint a needle in a data haystack. It's like speed dating...with your data!

   
   

   
               GET /wizards/_search?q=spell:fireball
           

1. 
   

   DynamoDB (The Serverless Charm Caster)

   
   

   
   DynamoDB, Amazon's brainchild, is the serverless treasure for those who abhor server maintenance as much as Voldemort abhors happiness. Auto-scaling, built-in redundancy, and a performance that laughs in the face of peak traffic—expect it all, as if granted by an AWS genie. Got a batch of data? Wave your provisioned throughput wand and watch it write and read in perfectly predictable performance puffs. Scaly clusters beware!

   
   

   
               Scan TableName="ForbiddenSpells";
           

1. 
   

   Neo4j (The Graph Database Guru)

   
   

   
   Neo4j, the sensei of connected data, assembles your intertwined web of nods and edges like an origami master. Grasp the deep relationships within your data, traversing paths and nodes through graph algorithms that weave tales of connections mere mortal databases can't discern. It's philosophy class meets database—where questions like "Who are you connected to?" and "How many degrees separate you?" find artful answers.

   
   

   
               MATCH (n:Person)-[r:LIKES]->(m:Technology) RETURN n, r, m