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

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

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

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

Primary database model

Document store
Object oriented DBMS

Values are user defined objects

Secondary database models

Document store
Spatial DBMS
Vector DBMS

Graph DBMS
Search engine

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

Score	19.03
Rank	#34	Overall
	#21	Relational DBMS

Score	1.48
Rank	#158	Overall
	#15	Graph DBMS

Score	134.78
Rank	#7	Overall
	#1	Search engines

Score	0.23
Rank	#319	Overall
	#141	Relational DBMS

Score	1.02
Rank	#192	Overall
	#32	Document stores
	#6	Object oriented DBMS

Website

aws.amazon.com/redshift

dgraph.io

www.elastic.co/elasticsearch

www.esgyn.cn

www.gigaspaces.com

Technical documentation

docs.aws.amazon.com/redshift

dgraph.io/docs

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

docs.gigaspaces.com/latest/landing.html

Developer

Amazon (based on PostgreSQL)

Dgraph Labs, Inc.

Elastic

Esgyn

Gigaspaces Technologies

Initial release

2012

2016

2010

2015

2000

Current release

8.6, January 2023

15.5, September 2020

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Elastic License

commercial

Open Source

Apache Version 2; Commercial licenses available

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++, Java

Java, C++, .Net

Server operating systems

hosted

Linux
OS X
Windows

All OS with a Java VM

Linux

Linux
macOS
Solaris
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.

XML can be used for describing objects metadata

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-99 for query and DML statements

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

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

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++
Java
Python
Scala

Server-side scripts

Stored procedures

user defined functions

in Python

yes

Java Stored Procedures

yes

Triggers

yes

by using the 'percolation' feature

yes, event driven architecture

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

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

yes

Map-Reduce pattern can be built with XAP task executors

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

Consistency level configurable: ALL, QUORUM, ANY

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

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Planned for future releases

fine grained access rights according to SQL-standard

Role-based access control

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