DBMS > BigObject vs. GBase vs. Graphite vs. Transwarp KunDB

System Properties Comparison BigObject vs. GBase vs. Graphite vs. Transwarp KunDB

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

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

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

OLTP DBMS based on a distributed architecture and highly compatible with MySQL and Oracle

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Relational DBMS

Time Series DBMS

Relational DBMS

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

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	1.07
Rank	#185	Overall
	#86	Relational DBMS

Score	4.57
Rank	#73	Overall
	#5	Time Series DBMS

Score	0.10
Rank	#344	Overall
	#151	Relational DBMS

Website

bigobject.io

www.gbase.cn

github.com/graphite-project/graphite-web

www.transwarp.cn/en/product/kundb

Technical documentation

docs.bigobject.io

graphite.readthedocs.io

Developer

BigObject, Inc.

General Data Technology Co., Ltd.

Chris Davis

Transwarp

Initial release

2015

2004

2006

Current release

GBase 8a, GBase 8s, GBase 8c

License

Commercial or Open Source

commercial

free community edition available

commercial

Open Source

Apache 2.0

commercial

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

Python

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Linux

Linux
Unix

Data scheme

yes

Typing

predefined data types such as float or date

yes

Numeric data only

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

SQL-like DML and DDL statements

Standard with numerous extensions

yes

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

ADO.NET
C API
JDBC
ODBC

HTTP API
Sockets

Supported programming languages

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Lua

user defined functions

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

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

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

locking

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

yes

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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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Recent citations in the news

Try out the Graphite monitoring tool for time-series data
29 October 2019, TechTarget

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1 April 2022, Datanami

The Billion Data Point Challenge: Building a Query Engine for High Cardinality Time Series Data
10 December 2018, Uber

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23 January 2015, InfoQ.com

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provided by Google News

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