DBMS > Amazon Redshift vs. DolphinDB vs. Elasticsearch

System Properties Comparison Amazon Redshift vs. DolphinDB vs. Elasticsearch

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

DolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.

A distributed, RESTful modern search and analytics engine based on Apache Lucene

Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric

Primary database model

Relational DBMS

Time Series DBMS

Search engine

Secondary database models

Relational DBMS

Document store
Spatial DBMS
Vector DBMS

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	4.13
Rank	#80	Overall
	#6	Time Series DBMS

Score	135.35
Rank	#7	Overall
	#1	Search engines

Website

aws.amazon.com/redshift

www.dolphindb.com

www.elastic.co/elasticsearch

Technical documentation

docs.aws.amazon.com/redshift

docs.dolphindb.cn/en/help200/index.html

www.elastic.co/guide/en/elasticsearch/reference/current/index.html

Developer

Amazon (based on PostgreSQL)

DolphinDB, Inc

Elastic

Initial release

2012

2018

2010

Current release

v2.00.4, January 2022

8.6, January 2023

License

Commercial or Open Source

commercial

free community version available

Open Source

Elastic License

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++

Java

Server operating systems

hosted

Linux
Windows

All OS with a Java VM

Data scheme

yes

schema-free

Flexible type definitions. Once a type is defined, it is persistent

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.

Secondary indexes

restricted

yes

All search fields are automatically indexed

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like query language

APIs and other access methods

JDBC
ODBC

JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket

Java API
RESTful HTTP/JSON API

Supported programming languages

All languages supporting JDBC/ODBC

C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust

.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in Python

yes

Triggers

yes

by using the 'percolation' feature

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

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

ES-Hadoop Connector

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

Transaction concepts

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

ACID

yes

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

Memcached and Redis integration

User concepts

Access control

fine grained access rights according to SQL-standard

Administrators, Users, Groups

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