DBMS > Amazon Redshift vs. HBase vs. Kdb vs. LevelDB vs. Sequoiadb

System Properties Comparison Amazon Redshift vs. HBase vs. Kdb vs. LevelDB vs. Sequoiadb

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Wide-column store based on Apache Hadoop and on concepts of BigTable

High performance Time Series DBMS

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

NewSQL database with distributed OLTP and SQL

Primary database model

Relational DBMS

Wide column store

Time Series DBMS
Vector DBMS

Key-value store

Document store
Relational DBMS

Secondary database models

Relational DBMS

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	30.50
Rank	#26	Overall
	#2	Wide column stores

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

Score	2.35
Rank	#111	Overall
	#19	Key-value stores

Score	0.45
Rank	#261	Overall
	#41	Document stores
	#122	Relational DBMS

Website

aws.amazon.com/redshift

hbase.apache.org

kx.com

github.com/google/leveldb

www.sequoiadb.com

Technical documentation

docs.aws.amazon.com/redshift

hbase.apache.org/book.html

code.kx.com

github.com/google/leveldb/blob/main/doc/index.md

www.sequoiadb.com/en/index.php?m=Files&a=index

Developer

Amazon (based on PostgreSQL)

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Kx Systems, a division of First Derivatives plc

Google

Sequoiadb Ltd.

Initial release

2012

2008

2000

kdb was released 2000, kdb+ in 2003

2011

2013

Current release

2.3.4, January 2021

3.6, May 2018

1.23, February 2021

License

Commercial or Open Source

commercial

Open Source

Apache version 2

commercial

free 32-bit version

Open Source

BSD

Open Source

Server: AGPL; Client: Apache V2

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
Unix
Windows

using Cygwin

Linux
OS X
Solaris
Windows

Illumos
Linux
OS X
Windows

Linux

Data scheme

yes

schema-free, schema definition possible

yes

schema-free

Typing

predefined data types such as float or date

yes

options to bring your own types, AVRO

yes

oid, date, timestamp, binary, regex

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

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like query language (q)

SQL-like query language

APIs and other access methods

JDBC
ODBC

Java API
RESTful HTTP API
Thrift

HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket

proprietary protocol using JSON

Supported programming languages

All languages supporting JDBC/ODBC

C
C#
C++
Groovy
Java
PHP
Python
Scala

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

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

.Net
C++
Java
PHP
Python

Server-side scripts

Stored procedures

user defined functions

in Python

yes

Coprocessors in Java

user defined functions

JavaScript

Triggers

yes

with views

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

Source-replica replication

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

similar paradigm used for internal processing

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency

Immediate Consistency

Eventual Consistency

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

Single row ACID (across millions of columns)

Document is locked during a transaction

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

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

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

rights management via user accounts

simple password-based access control

More information provided by the system vendor

Specific characteristics

Integrated columnar database & programming system for streaming, real time and historical...
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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...
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Key customers

Goldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
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Market metrics

kdb+ performance and reliability proven by our customers in critical infrastructure...
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Licensing and pricing models

upon request
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