DBMS > AgensGraph vs. Amazon Redshift vs. Elasticsearch vs. Graph Engine vs. Ignite

System Properties Comparison AgensGraph vs. Amazon Redshift vs. Elasticsearch vs. Graph Engine vs. Ignite

Editorial information provided by DB-Engines

Name

Description

Multi-model database supporting relational and graph data models and built upon PostgreSQL

Large scale data warehouse service for use with business intelligence tools

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

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

Primary database model

Graph DBMS
Relational DBMS

Relational DBMS

Search engine

Graph DBMS
Key-value store

Key-value store
Relational DBMS

Secondary database models

Document store
Spatial DBMS
Vector DBMS

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

Score	0.16
Rank	#333	Overall
	#30	Graph DBMS
	#146	Relational DBMS

Score	19.03
Rank	#34	Overall
	#21	Relational DBMS

Score	134.78
Rank	#7	Overall
	#1	Search engines

Score	0.62
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	3.64
Rank	#89	Overall
	#13	Key-value stores
	#48	Relational DBMS

Website

bitnine.net/agensgraph

aws.amazon.com/redshift

www.elastic.co/elasticsearch

www.graphengine.io

ignite.apache.org

Technical documentation

bitnine.net/documentation

docs.aws.amazon.com/redshift

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

www.graphengine.io/docs/manual

apacheignite.readme.io/docs

Developer

Bitnine Global Inc.

Amazon (based on PostgreSQL)

Elastic

Microsoft

Apache Software Foundation

Initial release

2016

2012

2010

2015

Current release

2.1, December 2018

8.6, January 2023

Apache Ignite 2.6

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

Open Source

Elastic License

Open Source

MIT License

Open Source

Apache 2.0

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

.NET and C

C++, Java, .Net

Server operating systems

Linux
OS X
Windows

hosted

All OS with a Java VM

.NET

Linux
OS X
Solaris
Windows

Data scheme

depending on used data model

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.

yes

Secondary indexes

yes

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

ANSI-99 for query and DML statements, subset of DDL

APIs and other access methods

Cypher Query Language
JDBC

JDBC
ODBC

Java API
RESTful HTTP/JSON API

RESTful HTTP API

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

Supported programming languages

C
Java
JavaScript
Python

All languages supporting JDBC/ODBC

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

C#
C++
F#
Visual Basic

C#
C++
Java
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

yes

user defined functions

in Python

yes

yes (compute grid and cache interceptors can be used instead)

Triggers

yes

by using the 'percolation' feature

yes (cache interceptors and events)

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

Sharding

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

yes (replicated cache)

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

yes (compute grid and hadoop accelerator)

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

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

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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

Security Hooks for custom implementations

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