DBMS > Amazon Aurora vs. Hazelcast vs. KairosDB vs. Snowflake vs. TDSQL for MySQL

System Properties Comparison Amazon Aurora vs. Hazelcast vs. KairosDB vs. Snowflake vs. TDSQL for MySQL

Editorial information provided by DB-Engines

Name

Description

MySQL and PostgreSQL compatible cloud service by Amazon

A widely adopted in-memory data grid

Distributed Time Series DBMS based on Cassandra or H2

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

A high-performance distributed database management system with features such as automatic sharding, intelligent operation and maintenance, elastic scalability without downtime, and enterprise-grade security. It is highly compatible with MySQL.

Primary database model

Secondary database models

Document store

JSON support with IMDG 3.12

Document store
Spatial DBMS

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

Score	7.57
Rank	#51	Overall
	#32	Relational DBMS

Score	5.46
Rank	#61	Overall
	#7	Key-value stores

Score	0.67
Rank	#233	Overall
	#20	Time Series DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	0.85
Rank	#207	Overall
	#97	Relational DBMS

Website

aws.amazon.com/rds/aurora

hazelcast.com

github.com/kairosdb/kairosdb

www.snowflake.com

www.tencentcloud.com/products/dcdb

Technical documentation

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

hazelcast.org/imdg/docs

kairosdb.github.io

docs.snowflake.net/manuals/index.html

www.tencentcloud.com/document/product/1042

Developer

Amazon

Hazelcast

Snowflake Computing Inc.

Tencent

Initial release

2015

2008

2013

2014

2013

Current release

5.3.6, November 2023

1.2.2, November 2018

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; commercial licenses available

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

Java

Server operating systems

hosted

All OS with a Java VM

Linux
OS X
Windows

hosted

Data scheme

yes

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

the object must implement a serialization strategy

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language

yes

APIs and other access methods

ADO.NET
JDBC
ODBC

JCache
JPA
Memcached protocol
RESTful HTTP API

Graphite protocol
HTTP REST
Telnet API

CLI Client
JDBC
ODBC

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
Go
Java
JavaScript (Node.js)
Python
Scala

Java
JavaScript

Node.js
PHP
Python

JavaScript (Node.js)
Python

C
C#
C++
Java
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

Event Listeners, Executor Services

user defined functions

yes

Triggers

yes

Events

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

based on Cassandra

yes

Automatic sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Replicated Map

selectable replication factor

based on Cassandra

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

one or two-phase-commit; repeatable reads; read commited

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

Role-based access control

simple password-based access control

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

Users with fine-grained authorization concept

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.