Four easy steps to Real-time Analytics with mishmash io

Step 1: Take a deep pot

Get mishmash io

The most advanced featureless database

Developers can start using our hosted version of mishmash io right away, free of charge. No hardware needed, no setup to work through.

Public releases are/will be available on all major cloud platforms and for various programming languages.

See the full list in the Road Map and Release Schedule.

$ heroku addons:create mishmashio:asdf
Adding mishmashio:asdf on myapp...done, v1 (free)
Use `heroku addons:docs mishmashio:asdf` to view documentation

Step 2: Put all your data in

Irrespective of structure

mishmash io doesn't have a schema - you can store your variables, scalars, arrays, lists, maps, objects, etc., exactly as they are.

Use them in your code as you see fit - mishmash io will automatically figure out the rest.

Behind the scenes it will uncover how the new data relates to everything else and organize it for quick parallel access.

// Init mishmash io
var mishmash = new Mishmash();

// store some data
mishmash.fibonacci = [0, 1, 1, 2, 3, 5, 8];

// add a user
mishmash.users[id++] = {
  login: "username",
  password: "password"
};

# Init mishmash io
mishmash = Mishmash()

# store some data
mishmash.fibonacci = [0, 1, 1, 2, 3, 5, 8]

# add a user
mishmash.users[uid+1] = {
  "login": "username",
  "password": "password"
}

Step 3: Stir for 200 milliseconds

'Query' with an entire algorithm

Implement an algorithm, in your choice of programming language, and mishmash io will then automatically run it in parallel on many cluster nodes to maximize processing speed and efficiency.

Exploring patterns in data is essential for any smart app, but it doesn't have to be hard. See how we use an algorithm to find structure in this smart football commentator example app.

// Initialize some local variables

teamA = 'Everton';
teamB = 'Huddersfield';

// submit an entire algorithm
res = mishmash.fixtures(function(data) {
  // executed remotely in parallel
  for (f of data) {
    if (f.homeTeam === teamA &&
        f.awayTeam === teamB) {
      // all data is in variables
      // add statements,
      // call functions
      // and more
    }
  }

  return 42;
})

# Initialize some local variables

teamA = 'Everton'
teamB = 'Huddersfield'

# submit an entire algorithm
def algorithm(data):
  # executed remotely in parallel
  if f.homeTeam == teamA and
     f.awayTeam == teamB:
    # all data is in variables
    # add statements, 
    # call functions
    # and more

  return 42

res = mishmash.fixtures(algorithm)

Step 4: Real-time analytics with mishmash io

Big Data, Disparate sets, Real-time Analytics. All in one DBMS.

This is Real-time Analytics.

Adopting algorithms is the way to extract value from patterns in data. Leave the guessing to others and let your data speak for itself.

To help you get going, mishmash io follows three guiding principles that make algorithm development easy and accessible, despite increasing data sizes and complexity.

And just as apps are here to assist us in every activity, so are algorithms here to assist every app. Read through the case studies to get a grasp on the breadth of transformation they deliver.

Ready for a deep dive?

Check out how mishmash io speeds up complex Machine Learning algorithms, by combining sophisticated code analysis and deep understanding of input data.

Consistency of results and performance is ensured by a group of components. Take a look at the architecture for an overview of how they cooperate.

A great resource for more technical details and examples is the Documentation page.