Keep it simple with SQL.

Riak TS lets you create your schema, write your data fast, and run queries. This enables you to ingest, transform, store, and analyze your time series data … all using SQL commands

With Riak TS, create tables that match your data model. Use SELECT statements with WHERE clauses to query and analyze your data. You can use the SHOW TABLES command to return a list of all tables in the schema, and use DESCRIBE to dynamically discover your schema (including quantum).

Arithmetic and aggregations in your SELECT statements make querying your time series data easier.


SQL MAKES TIME SERIES ANALYSIS EASY

Riak TS provides incredible flexibility for storing time series data. The Data Definition Language (DDL) defines tables, fields, and data types for time series structured and semi-structured data, which means that developers can define their own schema.

Your use case will determine how you create your schema. The tables define how to group data together based on a time range, called a quanta. All data belonging to the same quanta will be stored in the same partition in Riak TS.

By creating tables and typing your time series data, you can use Riak TS to efficiently write and read the data. Use the CREATE TABLE command to define your tables and fields, and use SELECT statements with WHERE clauses to read your data.

With Riak TS, you define your tables, as well as your family and series for the data points you collect across a specific time period. The example below shows creating a table using the Riak Python Client.

table = 'WEATHER'
fmt = """CREATE TABLE {table} (
city varchar not null,
location varchar not null,
time timestamp not null,
weather varchar not null,
temperature double,
PRIMARY KEY ((myfamily, myseries, quantum(time, 2, 'h')),
myfamily, myseries,, time))
"""
query = fmt.format(table=table)
ts_obj - client.ts_query(table,query)

 
Once you load your data into your table, you use SELECT statements with WHERE clauses to query your data:

Select * from WEATHER
WHERE city = 'Seattle' AND 
      location = 'Bellevue' AND
      time >= 1451606400000 AND
      time <= 1454284800000;

 
BENEFITS OF SQL COMMANDS IN RIAK TS

According to Gartner, IoT products and services will generate incremental revenue exceeding $300 billion by 2020. To compete in this race, you’ll want to develop your application quickly and ensure it scales. With Riak TS you can meet these requirements.

Get to market faster
You want to quickly build your IoT and time series applications. With Riak TS, you can leverage your existing SQL knowledge to model, store, and analyze your data, making application development easier, so you get to market faster.

Increase performance and scale
Time series data comes in at high volume and velocity. Riak TS with SQL commands lets you store and analyze your data quickly, which ensures your applications can scale.

Make better business decisions
Consumers and businesses are rapidly embracing time series applications resulting in huge amounts of data. To be valuable, this data needs to be analyzed and acted on quickly. With Riak TS, fast SQL queries enable you to make better business decisions.

According to Accenture, IoT will add $14.2 trillion to the global economy by 2030, enabling companies to capture new growth and boost revenue. As more and more enterprise applications collect IoT data—specifically time series data from sensors—they need fast, reliable, and scalable read and write performance. To best accomplish this, the data must be stored, queried, and analyzed together.

  1.  RESILIENCY
  2.  SCALABILITY
  3. OPERATIONALSIMPLICITY
  4. DATACO-LOCATION
  5. SQLCOMMANDS
  6. SQL RANGEQUERIES
  7.  AGGREGATIONS
  8. GLOBAL OBJECTEXPIRATION
  9. APACHE SPARKCONNECTOR
  10. APIS/CLIENTLIBRARIES
  11. MULTI-CLUSTERREPLICATION
  12. APACHE MESOSFRAMEWORK