DBMS > FatDB vs. GBase vs. Ignite vs. NSDb vs. RRDtool

System Properties Comparison FatDB vs. GBase vs. Ignite vs. NSDb vs. RRDtool

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.

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

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.

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

Industry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database.

The data is stored in a circular buffer, thus the system storage footprint remains constant over time.

Primary database model

Document store
Key-value store

Relational DBMS

Key-value store
Relational DBMS

Time Series DBMS

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

Score	1.07
Rank	#185	Overall
	#86	Relational DBMS

Score	3.16
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	1.87
Rank	#136	Overall
	#11	Time Series DBMS

Website

www.gbase.cn

ignite.apache.org

nsdb.io

oss.oetiker.ch/rrdtool

Technical documentation

apacheignite.readme.io/docs

nsdb.io/Architecture

oss.oetiker.ch/rrdtool/doc

Developer

FatCloud

General Data Technology Co., Ltd.

Apache Software Foundation

Tobias Oetiker

Initial release

2012

2004

2015

2017

1999

Current release

GBase 8a, GBase 8s, GBase 8c

Apache Ignite 2.6

1.8.0, 2022

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Apache Version 2.0

Open Source

GPL V2 and FLOSS

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C, Java, Python

C++, Java, .Net

Java, Scala

Implementations in Java (e.g. RRD4J) and C# available

Server operating systems

Windows

Linux

Linux
OS X
Solaris
Windows

Linux
macOS

HP-UX
Linux

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

Numeric data only

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

Exporting into and restoring from XML files possible

Secondary indexes

yes

all fields are automatically indexed

SQL

Support of SQL

Via inetgration in SQL Server

Standard with numerous extensions

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

SQL-like query language

APIs and other access methods

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

ADO.NET
C API
JDBC
ODBC

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

gRPC
HTTP REST
WebSocket

in-process shared library
Pipes

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

Java
Scala

with librrd library
C#

with a different implementation of RRDTool
Java

with a different implementation of RRDTool
JavaScript (Node.js)

with a different implementation of RRDTool
Lua
Perl
PHP

with a wrapper library
Python
Ruby

Server-side scripts

Stored procedures

yes

via applications

user defined functions

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

Triggers

yes

via applications

yes

yes (cache interceptors and events)

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning (by range, list and hash) and vertical partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

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

Eventual Consistency
Immediate Consistency

Immediate Consistency

Eventual Consistency

none

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

by using the rrdcached daemon

Durability

Support for making data persistent

yes

Using Apache Lucene

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

Can implement custom security layer via applications

yes

Security Hooks for custom implementations

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More resources

DB-Engines blog posts

Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

Time Series DBMS as a new trend?
1 June 2015, Paul Andlinger

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