DBMS > Apache Druid vs. Ingres vs. MySQL vs. Riak KV

System Properties Comparison Apache Druid vs. Ingres vs. MySQL vs. Riak KV

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Editorial information provided by DB-Engines

Name

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

Well established RDBMS

Widely used open source RDBMS

Distributed, fault tolerant key-value store

Primary database model

Relational DBMS
Time Series DBMS

Relational DBMS

Key/Value like access via memcached API

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Secondary database models

Document store
Spatial DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	2.85
Rank	#96	Overall
	#50	Relational DBMS
	#6	Time Series DBMS

Score	3.63
Rank	#79	Overall
	#43	Relational DBMS

Score	1029.49
Rank	#2	Overall
	#2	Relational DBMS

Score	3.84
Rank	#76	Overall
	#9	Key-value stores

Website

druid.apache.org

www.actian.com/databases/ingres

www.mysql.com

Technical documentation

druid.apache.org/docs/latest/design

docs.actian.com/ingres

dev.mysql.com/doc

www.tiot.jp/riak-docs/riak/kv/latest

Developer

Apache Software Foundation and contributors

Actian Corporation

Oracle

since 2010, originally MySQL AB, then Sun

OpenSource, formerly Basho Technologies

Initial release

2012

1974

originally developed at University Berkely in early 1970s

1995

2009

Current release

30.0.0, June 2024

12.0, July 2024

9.0.0, July 2024

3.2.0, December 2022

License

Commercial or Open Source

Open Source

Apache license v2

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Apache version 2, commercial enterprise edition

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C and C++

Erlang

Server operating systems

Linux
OS X
Unix

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Linux
OS X

Data scheme

yes

schema-less columns are supported

yes

schema-free

Typing

predefined data types such as float or date

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

but tools for importing/exporting data from/to XML-files available

yes

Secondary indexes

yes

restricted

SQL

Support of SQL

SQL for querying

yes

with proprietary extensions

APIs and other access methods

JDBC
RESTful HTTP/JSON API

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

ADO.NET
JDBC
ODBC
Proprietary native API

HTTP API
Native Erlang Interface

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

yes

proprietary syntax

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

horizontal partitioning

Ingres Star to access multiple databases simultaneously

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

no "single point of failure"

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

Ingres Replicator

Multi-source replication
Source-replica replication

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

links between data sets can be stored

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

MVCC

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

yes, using Riak Security

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