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  1. Stackups
  2. Application & Data
  3. Databases
  4. Databases
  5. KairosDB vs MySQL

KairosDB vs MySQL

OverviewDecisionsComparisonAlternatives

Overview

MySQL
MySQL
Stacks129.6K
Followers108.6K
Votes3.8K
GitHub Stars11.8K
Forks4.1K
KairosDB
KairosDB
Stacks16
Followers44
Votes5
GitHub Stars1.8K
Forks345

KairosDB vs MySQL: What are the differences?

# Introduction
Key differences between KairosDB and MySQL are outlined below.

1. **Data Model**: KairosDB is a time-series database specifically designed for handling time-series data, making it efficient for storing and querying timestamped data. On the other hand, MySQL is a relational database management system, optimized for handling structured data in tables with complex relationships.

2. **Query Language**: KairosDB uses its native query language to efficiently retrieve time-series data based on timestamps and other criteria. In contrast, MySQL employs SQL (Structured Query Language) for querying relational data, offering a more extensive set of features for complex queries involving joins, unions, and subqueries.

3. **Scalability**: KairosDB is horizontally scalable, allowing users to add more servers to the cluster to handle growing amounts of time-series data. MySQL, while supporting replication and clustering for read-heavy workloads, may require more effort and expertise to scale horizontally effectively.

4. **Performance**: Due to its specialization in time-series data, KairosDB can outperform MySQL in terms of write and query performance for timestamped data. MySQL, with its broader focus on relational data, may face performance limitations when dealing with large volumes of time-series data.

5. **Data Storage**: KairosDB stores data in a schema-less format optimized for time-series data, allowing for efficient storage and retrieval of timestamped information. In contrast, MySQL requires a predefined schema for storing data in a structured format, potentially leading to additional overhead in managing and querying time-series data.

6. **Use Cases**: KairosDB is well-suited for applications that primarily deal with time-series data such as IoT (Internet of Things), monitoring systems, and sensor data analysis. In contrast, MySQL is commonly used for traditional OLTP (Online Transaction Processing) applications, where complex relational queries and transactions are the focus.

In Summary, KairosDB and MySQL differ in terms of their data model, query language, scalability, performance, data storage, and use cases, catering to distinct requirements in handling time-series and relational data. 

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Advice on MySQL, KairosDB

Kyle
Kyle

Web Application Developer at Redacted DevWorks

Dec 3, 2019

DecidedonPostGISPostGIS

While there's been some very clever techniques that has allowed non-natively supported geo querying to be performed, it is incredibly slow in the long game and error prone at best.

MySQL finally introduced it's own GEO functions and special indexing operations for GIS type data. I prototyped with this, as MySQL is the most familiar database to me. But no matter what I did with it, how much tuning i'd give it, how much I played with it, the results would come back inconsistent.

It was very disappointing.

I figured, at this point, that SQL Server, being an enterprise solution authored by one of the biggest worldwide software developers in the world, Microsoft, might contain some decent GIS in it.

I was very disappointed.

Postgres is a Database solution i'm still getting familiar with, but I noticed it had no built in support for GIS. So I hilariously didn't pay it too much attention. That was until I stumbled upon PostGIS and my world changed forever.

449k views449k
Comments
Ido
Ido

Mar 6, 2020

Decided

My data was inherently hierarchical, but there was not enough content in each level of the hierarchy to justify a relational DB (SQL) with a one-to-many approach. It was also far easier to share data between the frontend (Angular), backend (Node.js) and DB (MongoDB) as they all pass around JSON natively. This allowed me to skip the translation layer from relational to hierarchical. You do need to think about correct indexes in MongoDB, and make sure the objects have finite size. For instance, an object in your DB shouldn't have a property which is an array that grows over time, without limit. In addition, I did use MySQL for other types of data, such as a catalog of products which (a) has a lot of data, (b) flat and not hierarchical, (c) needed very fast queries.

575k views575k
Comments
Navraj
Navraj

CEO at SuPragma

Apr 16, 2020

Needs adviceonMySQLMySQLPostgreSQLPostgreSQL

I asked my last question incorrectly. Rephrasing it here.

I am looking for the most secure open source database for my project I'm starting: https://github.com/SuPragma/SuPragma/wiki

Which database is more secure? MySQL or PostgreSQL? Are there others I should be considering? Is it possible to change the encryption keys dynamically?

Thanks,

Raj

401k views401k
Comments

Detailed Comparison

MySQL
MySQL
KairosDB
KairosDB

The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.

KairosDB is a fast distributed scalable time series database written on top of Cassandra.

Statistics
GitHub Stars
11.8K
GitHub Stars
1.8K
GitHub Forks
4.1K
GitHub Forks
345
Stacks
129.6K
Stacks
16
Followers
108.6K
Followers
44
Votes
3.8K
Votes
5
Pros & Cons
Pros
  • 800
    Sql
  • 679
    Free
  • 562
    Easy
  • 528
    Widely used
  • 490
    Open source
Cons
  • 16
    Owned by a company with their own agenda
  • 3
    Can't roll back schema changes
Pros
  • 1
    Easy setup
  • 1
    Easy Rest API
  • 1
    Open source
  • 1
    Time-Series data analysis
  • 1
    As fast as your cassandra/scylla cluster go

What are some alternatives to MySQL, KairosDB?

MongoDB

MongoDB

MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.

PostgreSQL

PostgreSQL

PostgreSQL is an advanced object-relational database management system that supports an extended subset of the SQL standard, including transactions, foreign keys, subqueries, triggers, user-defined types and functions.

Microsoft SQL Server

Microsoft SQL Server

Microsoft® SQL Server is a database management and analysis system for e-commerce, line-of-business, and data warehousing solutions.

SQLite

SQLite

SQLite is an embedded SQL database engine. Unlike most other SQL databases, SQLite does not have a separate server process. SQLite reads and writes directly to ordinary disk files. A complete SQL database with multiple tables, indices, triggers, and views, is contained in a single disk file.

Cassandra

Cassandra

Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.

Memcached

Memcached

Memcached is an in-memory key-value store for small chunks of arbitrary data (strings, objects) from results of database calls, API calls, or page rendering.

MariaDB

MariaDB

Started by core members of the original MySQL team, MariaDB actively works with outside developers to deliver the most featureful, stable, and sanely licensed open SQL server in the industry. MariaDB is designed as a drop-in replacement of MySQL(R) with more features, new storage engines, fewer bugs, and better performance.

RethinkDB

RethinkDB

RethinkDB is built to store JSON documents, and scale to multiple machines with very little effort. It has a pleasant query language that supports really useful queries like table joins and group by, and is easy to setup and learn.

ArangoDB

ArangoDB

A distributed free and open-source database with a flexible data model for documents, graphs, and key-values. Build high performance applications using a convenient SQL-like query language or JavaScript extensions.

InfluxDB

InfluxDB

InfluxDB is a scalable datastore for metrics, events, and real-time analytics. It has a built-in HTTP API so you don't have to write any server side code to get up and running. InfluxDB is designed to be scalable, simple to install and manage, and fast to get data in and out.

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