DBMS > Cubrid vs. Google Cloud Spanner vs. Graphite vs. Tkrzw

System Properties Comparison Cubrid vs. Google Cloud Spanner vs. Graphite vs. Tkrzw

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Editorial information provided by DB-Engines

Name

Description

CUBRID is an open-source SQL-based relational database management system with object extensions for OLTP

A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

Primary database model

Relational DBMS

Time Series DBMS

Key-value store

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

Score	0.97
Rank	#189	Overall
	#86	Relational DBMS

Score	2.69
Rank	#101	Overall
	#51	Relational DBMS

Score	5.19
Rank	#62	Overall
	#4	Time Series DBMS

Score	0.00
Rank	#385	Overall
	#61	Key-value stores

Website

cubrid.com (korean)
cubrid.org (english)

cloud.google.com/spanner

github.com/graphite-project/graphite-web

dbmx.net/tkrzw

Technical documentation

cubrid.org/manuals

cloud.google.com/spanner/docs

graphite.readthedocs.io

Developer

CUBRID Corporation, CUBRID Foundation

Google

Chris Davis

Mikio Hirabayashi

Initial release

2008

2017

2006

2020

Current release

11.0, January 2021

0.9.3, August 2020

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Apache 2.0

Open Source

Apache Version 2.0

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

C, C++, Java

Python

C++

Server operating systems

Linux
Windows

hosted

Linux
Unix

Linux
macOS

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

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.

Secondary indexes

yes

SQL

Support of SQL

yes

Query statements complying to ANSI 2011

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

gRPC (using protocol buffers) API
JDBC

At present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API

HTTP API
Sockets

Supported programming languages

C
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

Go
Java
JavaScript (Node.js)
Python

JavaScript (Node.js)
Python

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

Java Stored Procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication with 3 replicas for regional instances.

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

by using interleaved tables, this features focuses more on performance improvements than on referential integrity

Transaction concepts

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

ACID

Strict serializable isolation

Concurrency

Support for concurrent manipulation of data

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

using specific database classes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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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

CUBRID: A FOSS RDBMS to Realise Your Next Big Idea
26 April 2018, Open Source For You

NHN Willing to Be More Open
24 November 2008, 코리아타임스

provided by Google News

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23 July 2024, InfoWorld

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1 August 2024, InfoQ.com

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1 August 2024, TechTarget

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1 August 2024, TechCrunch

provided by Google News

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

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

Getting Started with Monitoring using Graphite
23 January 2015, InfoQ.com

Most Prominent Time Series Databases For Data Scientists
6 September 2021, AIM

Real-Time Performance and Health Monitoring Using Netdata
2 September 2019, CNX Software

provided by Google News

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