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

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

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

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

Open Source Operational and Transactional Enterprise NoSQL Document Database

Primary database model

Secondary database models

Document store
Spatial DBMS
Vector DBMS

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	17.94
Rank	#34	Overall
	#21	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

Score	2.92
Rank	#101	Overall
	#18	Document stores

Website

aws.amazon.com/redshift

dgraph.io

www.elastic.co/elasticsearch

www.esgyn.cn

ravendb.net

Technical documentation

docs.aws.amazon.com/redshift

dgraph.io/docs

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

ravendb.net/docs

Developer

Amazon (based on PostgreSQL)

Dgraph Labs, Inc.

Elastic

Esgyn

Hibernating Rhinos

Initial release

2012

2016

2010

2015

2010

Current release

8.6, January 2023

5.4, July 2022

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Elastic License

commercial

Open Source

AGPL version 3, commercial license available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++, Java

Server operating systems

hosted

Linux
OS X
Windows

All OS with a Java VM

Linux

Linux
macOS
Raspberry Pi
Windows

Data scheme

yes

schema-free

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

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.

Secondary indexes

restricted

yes

All search fields are automatically indexed

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like query language

yes

SQL-like query language (RQL)

APIs and other access methods

JDBC
ODBC

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

Java API
RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

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

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

Server-side scripts

Stored procedures

user defined functions

in Python

yes

Java Stored Procedures

yes

Triggers

yes

by using the 'percolation' feature

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Synchronous replication via Raft

yes

Multi-source replication between multi datacenters

Multi-source replication

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

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

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

ACID, Cluster-wide transaction available

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

Planned for future releases

fine grained access rights according to SQL-standard

Authorization levels configured per client per database

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