DBMS > Amazon Aurora vs. Apache Druid vs. KairosDB vs. Snowflake vs. Splunk

System Properties Comparison Amazon Aurora vs. Apache Druid vs. KairosDB vs. Snowflake vs. Splunk

Editorial information provided by DB-Engines

Name

Description

MySQL and PostgreSQL compatible cloud service by Amazon

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

Distributed Time Series DBMS based on Cassandra or H2

Cloud-based data warehousing service for structured and semi-structured data

Analytics Platform for Big Data

Primary database model

Relational DBMS

Relational DBMS
Time Series DBMS

Time Series DBMS

Relational DBMS

Search engine

Secondary database models

Document store

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

Score	7.57
Rank	#51	Overall
	#32	Relational DBMS

Score	3.25
Rank	#90	Overall
	#47	Relational DBMS
	#7	Time Series DBMS

Score	0.67
Rank	#233	Overall
	#20	Time Series DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	89.10
Rank	#14	Overall
	#2	Search engines

Website

aws.amazon.com/rds/aurora

druid.apache.org

github.com/kairosdb/kairosdb

www.snowflake.com

www.splunk.com

Technical documentation

docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/CHAP_Aurora.html

druid.apache.org/docs/latest/design

kairosdb.github.io

docs.snowflake.net/manuals/index.html

docs.splunk.com/Documentation/Splunk

Developer

Amazon

Apache Software Foundation and contributors

Snowflake Computing Inc.

Splunk Inc.

Initial release

2015

2012

2013

2014

2003

Current release

29.0.1, April 2024

1.2.2, November 2018

License

Commercial or Open Source

commercial

Open Source

Apache license v2

Open Source

Apache 2.0

commercial

Limited free edition and free developer edition available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Server operating systems

hosted

Linux
OS X
Unix

Linux
OS X
Windows

hosted

Linux
OS X
Solaris
Windows

Data scheme

yes

schema-less columns are supported

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

yes

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL for querying

yes

Splunk Search Processing Language for search commands

APIs and other access methods

ADO.NET
JDBC
ODBC

JDBC
RESTful HTTP/JSON API

Graphite protocol
HTTP REST
Telnet API

CLI Client
JDBC
ODBC

HTTP REST

Supported programming languages

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

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

Java
JavaScript

Node.js
PHP
Python

JavaScript (Node.js)
Python

C#
Java
JavaScript
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

user defined functions

yes

Triggers

yes

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

manual/auto, time-based

Sharding

based on Cassandra

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes, via HDFS, S3 or other storage engines

selectable replication factor

based on Cassandra

yes

Multi-source replication

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

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

A 'Transaction' in Splunk has a different meaning: grouping related events into a single one for later searching

Concurrency

Support for concurrent manipulation of data

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

fine grained access rights according to SQL-standard

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

simple password-based access control

Users with fine-grained authorization concept, user roles and pluggable authentication

Access rights for users and roles

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