DBMS > Amazon Redshift vs. EsgynDB vs. GridGain vs. NSDb vs. TinkerGraph

System Properties Comparison Amazon Redshift vs. EsgynDB vs. GridGain vs. NSDb vs. TinkerGraph

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

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

GridGain is an in-memory computing platform, built on Apache Ignite

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

A lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Time Series DBMS

Graph DBMS

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

Score	19.03
Rank	#34	Overall
	#21	Relational DBMS

Score	0.23
Rank	#319	Overall
	#141	Relational DBMS

Score	1.53
Rank	#155	Overall
	#26	Key-value stores
	#73	Relational DBMS

Score	0.00
Rank	#396	Overall
	#42	Time Series DBMS

Score	0.12
Rank	#344	Overall
	#34	Graph DBMS

Website

aws.amazon.com/redshift

www.esgyn.cn

www.gridgain.com

nsdb.io

tinkerpop.apache.org/docs/current/reference/#tinkergraph-gremlin

Technical documentation

docs.aws.amazon.com/redshift

www.gridgain.com/docs/index.html

nsdb.io/Architecture

Developer

Amazon (based on PostgreSQL)

Esgyn

GridGain Systems, Inc.

Initial release

2012

2015

2007

2017

2009

Current release

GridGain 8.5.1

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

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

C++, Java

Java, C++, .Net

Java, Scala

Java

Server operating systems

hosted

Linux

Linux
OS X
Solaris
Windows

Linux
macOS

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

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

restricted

yes

all fields are automatically indexed

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

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

SQL-like query language

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
ODBC

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

gRPC
HTTP REST
WebSocket

TinkerPop 3

Supported programming languages

All languages supporting JDBC/ODBC

All languages supporting JDBC/ODBC/ADO.Net

C#
C++
Java
PHP
Python
Ruby
Scala

Java
Scala

Groovy
Java

Server-side scripts

Stored procedures

user defined functions

in Python

Java Stored Procedures

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

Triggers

yes (cache interceptors and events)

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication between multi datacenters

yes (replicated cache)

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

none

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

Relationships in graphs

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

Using Apache Lucene

optional

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Security Hooks for custom implementations

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