DBMS > Amazon Aurora vs. etcd vs. Ignite vs. IRONdb vs. Snowflake

System Properties Comparison Amazon Aurora vs. etcd vs. Ignite vs. IRONdb vs. Snowflake

Editorial information provided by DB-Engines

Name

IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

MySQL and PostgreSQL compatible cloud service by Amazon

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

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

Primary database model

Relational DBMS

Key-value store

Key-value store
Relational DBMS

Time Series DBMS

Relational DBMS

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	7.03
Rank	#54	Overall
	#5	Key-value stores

Score	3.11
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

aws.amazon.com/rds/aurora

etcd.io
github.com/etcd-io/etcd

ignite.apache.org

www.circonus.com/solutions/time-series-database/

www.snowflake.com

Technical documentation

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

etcd.io/docs
github.com/etcd-io/etcd/tree/master/Documentation

apacheignite.readme.io/docs

docs.circonus.com/irondb/category/getting-started

docs.snowflake.net/manuals/index.html

Developer

Amazon

Apache Software Foundation

Circonus LLC.

Snowflake Computing Inc.

Initial release

2015

2017

2014

Current release

3.4, August 2019

Apache Ignite 2.6

V0.10.20, January 2018

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Apache 2.0

commercial

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

C++, Java, .Net

C and C++

Server operating systems

hosted

FreeBSD
Linux
Windows

experimental

Linux
OS X
Solaris
Windows

Linux

hosted

Data scheme

yes

schema-free

yes

schema-free

yes

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

Typing

predefined data types such as float or date

yes

text, numeric, histograms

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

ANSI-99 for query and DML statements, subset of DDL

SQL-like query language (Circonus Analytics Query Language: CAQL)

yes

APIs and other access methods

ADO.NET
JDBC
ODBC

gRPC
JSON over HTTP

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

HTTP API

CLI Client
JDBC
ODBC

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

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl

C#
C++
Java
PHP
Python
Ruby
Scala

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

yes (compute grid and cache interceptors can be used instead)

yes, in Lua

user defined functions

Triggers

yes

yes, watching key changes

yes (cache interceptors and events)

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

Automatic, metric affinity per node

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

yes (replicated cache)

configurable replication factor, datacenter aware

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate consistency per node, eventual consistency across nodes

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

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

Security Hooks for custom implementations

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

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