DBMS > FatDB vs. NSDb vs. TinkerGraph

System Properties Comparison FatDB vs. NSDb vs. TinkerGraph

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Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Description

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

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

Document store
Key-value store

Time Series DBMS

Graph DBMS

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

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	0.08
Rank	#348	Overall
	#35	Graph DBMS

Website

nsdb.io

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

Technical documentation

nsdb.io/Architecture

Developer

FatCloud

Initial release

2012

2017

2009

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

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java, Scala

Java

Server operating systems

Windows

Linux
macOS

Data scheme

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.

Secondary indexes

yes

all fields are automatically indexed

SQL

Support of SQL

Via inetgration in SQL Server

SQL-like query language

APIs and other access methods

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

gRPC
HTTP REST
WebSocket

TinkerPop 3

Supported programming languages

Java
Scala

Groovy
Java

Server-side scripts

Stored procedures

yes

via applications

Triggers

yes

via applications

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Eventual Consistency

none

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

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

Can implement custom security layer via applications

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More resources

Recent citations in the news

Why developers like Apache TinkerPop, an open source framework for graph computing | Amazon Web Services
27 September 2021, AWS Blog

Introducing Gremlin query hints for Amazon Neptune
26 February 2019, AWS Blog

InfiniteGraph Gets Support for Common Graph Database Language and More
21 February 2012, SiliconANGLE News

provided by Google News

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