DBMS > AgensGraph vs. EsgynDB vs. NCache vs. Rockset vs. Snowflake

System Properties Comparison AgensGraph vs. EsgynDB vs. NCache vs. Rockset vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

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

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

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

A scalable, reliable search and analytics service in the cloud, built on RocksDB

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

Primary database model

Graph DBMS
Relational DBMS

Secondary database models

Document store
Search engine

Using distributed Lucene

Relational DBMS
Search engine

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

Score	0.23
Rank	#315	Overall
	#26	Graph DBMS
	#140	Relational DBMS

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

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

Score	0.82
Rank	#212	Overall
	#36	Document stores

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

bitnine.net/agensgraph

www.esgyn.cn

www.alachisoft.com/ncache

rockset.com

www.snowflake.com

Technical documentation

bitnine.net/documentation

www.alachisoft.com/resources/docs

docs.rockset.com

docs.snowflake.net/manuals/index.html

Developer

Bitnine Global Inc.

Esgyn

Alachisoft

Rockset

Snowflake Computing Inc.

Initial release

2016

2015

2005

2019

2014

Current release

2.1, December 2018

5.3.3, April 2024

License

Commercial or Open Source

Open Source

Apache License 2.0

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

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Implementation language

C++, Java

C#, .NET, .NET Core, Java

C++

Server operating systems

Linux
OS X
Windows

Linux

Linux
Windows

hosted

Data scheme

depending on used data model

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

dynamic typing

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.

ingestion from XML files supported

yes

Secondary indexes

yes

all fields are automatically indexed

SQL

Support of SQL

yes

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

Read-only SQL queries, including JOINs

yes

APIs and other access methods

Cypher Query Language
JDBC

ADO.NET
JDBC
ODBC

IDistributedCache
JCache
LINQ
Proprietary native API

HTTP REST

CLI Client
JDBC
ODBC

Supported programming languages

C
Java
JavaScript
Python

All languages supporting JDBC/ODBC/ADO.Net

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

Go
Java
JavaScript (Node.js)
Python

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

Java Stored Procedures

support for stored procedures with SQL-Server CLR

user defined functions

Triggers

yes

Notifications

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

Sharding

yes

Automatic sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication between multi datacenters

yes, with selectable consistency level

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

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

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

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

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

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

Access rights for users and organizations can be defined via Rockset console

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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