DBMS > Amazon Redshift vs. Databend vs. Dgraph vs. Elasticsearch vs. EsgynDB

System Properties Comparison Amazon Redshift vs. Databend vs. Dgraph vs. Elasticsearch vs. EsgynDB

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

An open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexity

Distributed and scalable native Graph DBMS

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

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

Primary database model

Secondary database models

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	0.30
Rank	#287	Overall
	#130	Relational DBMS

Score	1.45
Rank	#156	Overall
	#15	Graph DBMS

Score	135.35
Rank	#7	Overall
	#1	Search engines

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Website

aws.amazon.com/redshift

github.com/datafuselabs/databend
www.databend.com

dgraph.io

www.elastic.co/elasticsearch

www.esgyn.cn

Technical documentation

docs.aws.amazon.com/redshift

docs.databend.com

dgraph.io/docs

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

Developer

Amazon (based on PostgreSQL)

Databend Labs

Dgraph Labs, Inc.

Elastic

Esgyn

Initial release

2012

2021

2016

2010

2015

Current release

1.0.59, April 2023

8.6, January 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Apache 2.0

Open Source

Elastic License

commercial

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

Rust

Java

C++, Java

Server operating systems

hosted

hosted
Linux
macOS

Linux
OS X
Windows

All OS with a Java VM

Linux

Data scheme

yes

schema-free

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

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.

Secondary indexes

restricted

yes

All search fields are automatically indexed

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

SQL-like query language

yes

APIs and other access methods

JDBC
ODBC

CLI Client
JDBC
RESTful HTTP API

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

Java API
RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

Go
Java
JavaScript (Node.js)
Python
Rust

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

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

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

user defined functions

in Python

yes

Java Stored Procedures

Triggers

yes

by using the 'percolation' feature

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Synchronous replication via Raft

yes

Multi-source replication between multi datacenters

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

yes

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

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

yes

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

Memcached and Redis integration

User concepts

Access control

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept, user roles

Planned for future releases

fine grained access rights according to SQL-standard

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