DBMS > Amazon Neptune vs. GridGain vs. NCache vs. Snowflake

System Properties Comparison Amazon Neptune vs. GridGain vs. NCache vs. Snowflake

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Editorial information provided by DB-Engines

Name

Description

Fast, reliable graph database built for the cloud

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

Open-Source and Enterprise in-memory Key-Value Store

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Graph DBMS
RDF store

Key-value store
Relational DBMS

Key-value store

Relational DBMS

Secondary database models

Document store
Search engine

Using distributed Lucene

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

Score	2.29
Rank	#113	Overall
	#9	Graph DBMS
	#5	RDF stores

Score	1.55
Rank	#150	Overall
	#26	Key-value stores
	#70	Relational DBMS

Score	0.96
Rank	#195	Overall
	#29	Key-value stores

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

aws.amazon.com/neptune

www.gridgain.com

www.alachisoft.com/ncache

www.snowflake.com

Technical documentation

aws.amazon.com/neptune/developer-resources

www.gridgain.com/docs/index.html

www.alachisoft.com/resources/docs

docs.snowflake.net/manuals/index.html

Developer

Amazon

GridGain Systems, Inc.

Alachisoft

Snowflake Computing Inc.

Initial release

2017

2007

2005

2014

Current release

GridGain 8.5.1

5.3.3, April 2024

License

Commercial or Open Source

commercial

Open Source

Enterprise Edition available

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

Java, C++, .Net

C#, .NET, .NET Core, Java

Server operating systems

hosted

Linux
OS X
Solaris
Windows

Linux
Windows

hosted

Data scheme

schema-free

yes

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

Typing

predefined data types such as float or date

yes

partial

Supported data types are Lists, Queues, Hashsets, Dictionary and Counter

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

SQL

Support of SQL

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

SQL-like query syntax and LINQ for searching the cache. Cache Synchronization with SQL Server using SQL dependency.

yes

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

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

IDistributedCache
JCache
LINQ
Proprietary native API

CLI Client
JDBC
ODBC

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

C#
C++
Java
PHP
Python
Ruby
Scala

.Net
.Net Core
C#
Java
JavaScript (Node.js)
Python
Scala

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

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

support for stored procedures with SQL-Server CLR

user defined functions

Triggers

yes (cache interceptors and events)

yes

Notifications

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances.

yes (replicated cache)

yes, with selectable consistency level

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency
Strong Eventual Consistency over WAN with Conflict Resolution using Bridge Topology

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

optimistic locking and pessimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with encyption-at-rest

yes

In-memory capabilities

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

yes

User concepts

Access control

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

Security Hooks for custom implementations

Authentication to access the cache via Active Directory/LDAP (possible roles: user, administrator)

Users with fine-grained authorization concept, user roles and pluggable authentication

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

Bank of America, Citi, Natures Way, Charter Spectrum, Barclays, Henry Schein, GBM,...
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Market metrics

Market Leader in .NET Distributed Caching since 2005.
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Licensing and pricing models

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