DBMS > Amazon Redshift vs. Datastax Enterprise vs. EsgynDB vs. H2GIS vs. Kdb

System Properties Comparison Amazon Redshift vs. Datastax Enterprise vs. EsgynDB vs. H2GIS vs. Kdb

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

DataStax Enterprise (DSE) is the always-on, scalable data platform built on Apache Cassandra and designed for hybrid Cloud. DSE integrates graph, search, analytics, administration, developer tooling, and monitoring into a unified platform.

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Spatial extension of H2

High performance Time Series DBMS

Primary database model

Time Series DBMS
Vector DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS
Search engine
Vector DBMS

Relational DBMS

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	5.80
Rank	#60	Overall
	#4	Wide column stores

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	0.00
Rank	#383	Overall
	#7	Spatial DBMS

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

Website

aws.amazon.com/redshift

www.datastax.com/products/datastax-enterprise

www.esgyn.cn

www.h2gis.org

kx.com

Technical documentation

docs.aws.amazon.com/redshift

docs.datastax.com

www.h2gis.org/docs/home

code.kx.com

Developer

Amazon (based on PostgreSQL)

DataStax

Esgyn

CNRS

Kx Systems, a division of First Derivatives plc

Initial release

2012

2011

2015

2013

2000

kdb was released 2000, kdb+ in 2003

Current release

6.8, April 2020

3.6, May 2018

License

Commercial or Open Source

commercial

Open Source

LGPL 3.0

commercial

free 32-bit version

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.

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Implementation language

Java

C++, Java

Java

Server operating systems

hosted

Linux
OS X

Linux

Linux
OS X
Solaris
Windows

Data scheme

yes

schema-free

yes

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'

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like DML and DDL statements (CQL); Spark SQL

yes

SQL-like query language (q)

APIs and other access methods

JDBC
ODBC

Proprietary protocol

CQL (Cassandra Query Language)
TinkerPop Gremlin

with DSE Graph

ADO.NET
JDBC
ODBC

HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket

Supported programming languages

All languages supporting JDBC/ODBC

C
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

All languages supporting JDBC/ODBC/ADO.Net

Java

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

Server-side scripts

Stored procedures

user defined functions

in Python

Java Stored Procedures

yes

based on H2

user defined functions

Triggers

yes

with views

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

Sharding

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

configurable replication factor, datacenter aware, advanced replication for edge computing

Multi-source replication between multi datacenters

yes

based on H2

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
Tunable Consistency

consistency level can be individually decided with each write operation

Immediate 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

Atomicity and isolation are supported for single operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

fine grained access rights according to SQL-standard

Access rights for users can be defined per object

fine grained access rights according to SQL-standard

yes

based on H2

rights management via user accounts

More information provided by the system vendor

Specific characteristics

DataStax Enterprise is scale-out data infrastructure for enterprises that need to...
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Integrated columnar database & programming system for streaming, real time and historical...
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Competitive advantages

Supporting the following application requirements: Zero downtime - Built on Apache...
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provides seamless scalability; runs on industry standard server platforms; is top-ranked...
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Typical application scenarios

Applications that must be massively and linearly scalable with 100% uptime and able...
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tick database streaming sensor data massive intelligence applications oil and gas...
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Key customers

Capital One, Cisco, Comcast, eBay, McDonald's, Microsoft, Safeway, Sony, UBS, and...
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Goldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
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Market metrics

Among the Forbes 100 Most Innovative Companies, DataStax is trusted by 5 of the top...
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kdb+ performance and reliability proven by our customers in critical infrastructure...
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Licensing and pricing models

Annual subscription
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upon request
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