DBMS > Amazon Redshift vs. Apache Impala vs. Kdb vs. LokiJS

System Properties Comparison Amazon Redshift vs. Apache Impala vs. Kdb vs. LokiJS

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Analytic DBMS for Hadoop

High performance Time Series DBMS

In-memory JavaScript DBMS

Primary database model

Relational DBMS

Time Series DBMS
Vector DBMS

Document store

Secondary database models

Document store

Relational DBMS

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

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

Score	0.49
Rank	#260	Overall
	#42	Document stores

Website

aws.amazon.com/redshift

impala.apache.org

kx.com

github.com/techfort/LokiJS

Technical documentation

docs.aws.amazon.com/redshift

impala.apache.org/impala-docs.html

code.kx.com

techfort.github.io/LokiJS

Developer

Amazon (based on PostgreSQL)

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Kx Systems, a division of First Derivatives plc

Initial release

2012

2013

2000

kdb was released 2000, kdb+ in 2003

2014

Current release

4.1.0, June 2022

3.6, May 2018

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

commercial

free 32-bit version

Open Source

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++

JavaScript

Server operating systems

hosted

Linux

Linux
OS X
Solaris
Windows

server-less, requires a JavaScript environment (browser, Node.js)

Data scheme

yes

schema-free

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

restricted

yes

table attribute 'grouped'

yes

via views

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like DML and DDL statements

SQL-like query language (q)

APIs and other access methods

JDBC
ODBC

HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket

JavaScript API

Supported programming languages

All languages supporting JDBC/ODBC

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

JavaScript

Server-side scripts

Stored procedures

user defined functions

in Python

yes

user defined functions and integration of map-reduce

user defined functions

View functions in JavaScript

Triggers

yes

with views

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

similar paradigm used for internal processing

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

none

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

Transaction concepts

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

ACID

atomic operations within a single collection possible

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Serialization of a DB in a Node.JS/Cordova/PhoneGap environment. Usage of the IndexedDB-API in a browser.

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

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

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...
» 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.