DBMS > Amazon DynamoDB vs. jBASE vs. Kdb vs. Prometheus

System Properties Comparison Amazon DynamoDB vs. jBASE vs. Kdb vs. Prometheus

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Editorial information provided by DB-Engines

Name

Description

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

A robust multi-value DBMS comprising development tools and middleware

High performance Time Series DBMS

Open-source Time Series DBMS and monitoring system

Primary database model

Document store
Key-value store

Multivalue DBMS

Time Series DBMS
Vector DBMS

Time Series DBMS

Secondary database models

Relational DBMS

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

Score	74.07
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	1.41
Rank	#159	Overall
	#3	Multivalue DBMS

Score	7.55
Rank	#53	Overall
	#3	Time Series DBMS
	#1	Vector DBMS

Score	8.42
Rank	#47	Overall
	#2	Time Series DBMS

Website

aws.amazon.com/dynamodb

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-jbase

kx.com

prometheus.io

Technical documentation

docs.aws.amazon.com/dynamodb

docs.rocketsoftware.com/bundle?labelkey=jbase_5.9

code.kx.com

prometheus.io/docs

Developer

Amazon

Rocket Software (formerly Zumasys)

Kx Systems, a division of First Derivatives plc

Initial release

2012

1991

2000

kdb was released 2000, kdb+ in 2003

2015

Current release

5.7

3.6, May 2018

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

free 32-bit version

Open Source

Apache 2.0

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

Server operating systems

hosted

AIX
Linux
Windows

Linux
OS X
Solaris
Windows

Linux
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

optional

yes

Numeric data only

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

Import of XML data possible

Secondary indexes

yes

table attribute 'grouped'

SQL

Support of SQL

Embedded SQL for jBASE in BASIC

SQL-like query language (q)

APIs and other access methods

RESTful HTTP API

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API

HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket

RESTful HTTP/JSON API

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

.Net
Basic
Jabbascript
Java

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

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

Server-side scripts

Stored procedures

yes

user defined functions

Triggers

yes

by integration with AWS Lambda

yes

with views

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

yes

by Federation

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

Immediate Consistency

none

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

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)

Access rights can be defined down to the item level

rights management via user accounts

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...
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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
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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.