DBMS > Amazon DynamoDB vs. BigObject vs. Blueflood vs. Kdb vs. RDFox

System Properties Comparison Amazon DynamoDB vs. BigObject vs. Blueflood vs. Kdb vs. RDFox

Editorial information provided by DB-Engines

Name

Description

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

Analytic DBMS for real-time computations and queries

Scalable TimeSeries DBMS based on Cassandra

High performance Time Series DBMS

High performance knowledge graph and semantic reasoning engine

Primary database model

Document store
Key-value store

Relational DBMS

a hierachical model (tree) can be imposed

Time Series DBMS

Time Series DBMS
Vector DBMS

Graph DBMS
RDF store

Secondary database models

Relational 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	0.19
Rank	#329	Overall
	#146	Relational DBMS

Score	0.13
Rank	#346	Overall
	#33	Time Series DBMS

Score	7.71
Rank	#49	Overall
	#2	Time Series DBMS
	#1	Vector DBMS

Score	0.29
Rank	#300	Overall
	#24	Graph DBMS
	#13	RDF stores

Website

aws.amazon.com/dynamodb

bigobject.io

blueflood.io

kx.com

www.oxfordsemantic.tech

Technical documentation

docs.aws.amazon.com/dynamodb

docs.bigobject.io

github.com/rax-maas/blueflood/wiki

code.kx.com

docs.oxfordsemantic.tech

Developer

Amazon

BigObject, Inc.

Rackspace

Kx Systems, a division of First Derivatives plc

Oxford Semantic Technologies

Initial release

2012

2015

2013

2000

kdb was released 2000, kdb+ in 2003

2017

Current release

3.6, May 2018

6.0, Septermber 2022

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

free community edition available

Open Source

Apache 2.0

commercial

free 32-bit version

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

C++

Server operating systems

hosted

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Linux
OS X

Linux
OS X
Solaris
Windows

Linux
macOS
Windows

Data scheme

schema-free

yes

predefined scheme

yes

RDF schemas

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

table attribute 'grouped'

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like query language (q)

APIs and other access methods

RESTful HTTP API

fluentd
ODBC
RESTful HTTP API

HTTP REST

HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket

RESTful HTTP API
SPARQL 1.1

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala

C
Java

Server-side scripts

Stored procedures

Lua

user defined functions

Triggers

yes

by integration with AWS Lambda

yes

with views

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

based on Cassandra

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

selectable replication factor

based on Cassandra

Source-replica replication

replication via a shared file system

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

similar paradigm used for internal processing

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

none

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Immediate Consistency in stand-alone mode, Eventual Consistency in replicated setups

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

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

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

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)

rights management via user accounts

Roles, resources, and access types

More information provided by the system vendor

Specific characteristics

Integrated columnar database & programming system for streaming, real time and historical...
» more

Competitive advantages

provides seamless scalability; runs on industry standard server platforms; is top-ranked...
» more

Typical application scenarios

tick database streaming sensor data massive intelligence applications oil and gas...
» more

Key customers

Goldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
» more

Market metrics

kdb+ performance and reliability proven by our customers in critical infrastructure...
» more

Licensing and pricing models

upon request
» more

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.