DBMS > Amazon DynamoDB vs. IRONdb vs. Kingbase vs. SwayDB vs. Warp 10

System Properties Comparison Amazon DynamoDB vs. IRONdb vs. Kingbase vs. SwayDB vs. Warp 10

Editorial information provided by DB-Engines

Name

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

Description

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

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

An enterprise-class RDBMS compatible with PostgreSQL and Oracle and widely used in China.

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

Document store
Key-value store

Secondary database models

Document store
Spatial DBMS

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

Score	74.45
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	0.50
Rank	#257	Overall
	#119	Relational DBMS

Score	0.04
Rank	#387	Overall
	#61	Key-value stores

Score	0.14
Rank	#344	Overall
	#32	Time Series DBMS

Website

aws.amazon.com/dynamodb

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

www.kingbase.com.cn

swaydb.simer.au

www.warp10.io

Technical documentation

docs.aws.amazon.com/dynamodb

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

www.warp10.io/content/02_Getting_started

Developer

Amazon

Circonus LLC.

BeiJing KINGBASE Information technologies inc.

Simer Plaha

SenX

Initial release

2012

2017

1999

2018

2015

Current release

V0.10.20, January 2018

V8.0, August 2021

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

Open Source

GNU Affero GPL V3.0

Open Source

Apache License 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C and C++

C and Java

Scala

Java

Server operating systems

hosted

Linux

Linux
Windows

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

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

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

Standard with numerous extensions

APIs and other access methods

RESTful HTTP API

HTTP API

ADO.NET
gokb
JDBC
kdbndp
ODBC
PDI
PDO
Pro*C
psycopg2
QT

HTTP API
Jupyter
WebSocket

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

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

.Net
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

Java
Kotlin
Scala

Server-side scripts

Stored procedures

yes, in Lua

user defined functions

yes

WarpScript

Triggers

yes

by integration with AWS Lambda

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic, metric affinity per node

horizontal partitioning (by range, list and hash) and vertical partitioning

none

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

yes

configurable replication factor, datacenter aware

yes

none

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate consistency per node, eventual consistency across nodes

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

ACID across one or more tables within a single AWS account and region

ACID

Atomic execution of operations

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

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

fine grained access rights according to SQL-standard

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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