DBMS > Google Cloud Bigtable vs. Graphite vs. openGemini vs. Postgres-XL

System Properties Comparison Google Cloud Bigtable vs. Graphite vs. openGemini vs. Postgres-XL

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Editorial information provided by DB-Engines

Name

Description

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

An open source distributed Time Series DBMS with high concurrency, high performance, and high scalability

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Primary database model

Key-value store
Wide column store

Time Series DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	3.15
Rank	#95	Overall
	#14	Key-value stores
	#8	Wide column stores

Score	4.83
Rank	#67	Overall
	#4	Time Series DBMS

Score	0.09
Rank	#361	Overall
	#37	Time Series DBMS

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Website

cloud.google.com/bigtable

github.com/graphite-project/graphite-web

www.opengemini.org
github.com/openGemini

www.postgres-xl.org

Technical documentation

cloud.google.com/bigtable/docs

graphite.readthedocs.io

docs.opengemini.org/guide

www.postgres-xl.org/documentation

Developer

Google

Chris Davis

Huawei and openGemini community

Initial release

2015

2006

2022

2014

since 2012, originally named StormDB

Current release

1.1, July 2023

10 R1, October 2018

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Apache Version 2.0

Open Source

Mozilla public license

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

Python

Server operating systems

hosted

Linux
Unix

Linux
Windows

Linux
macOS

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

Numeric data only

Integer, Float, Boolean, 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.

yes

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

distributed, parallel query execution

APIs and other access methods

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

HTTP API
Sockets

HTTP REST

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

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

JavaScript (Node.js)
Python

C
C++
Go
Java
JavaScript (Node.js)
Python
Rust

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Internal replication in Colossus, and regional replication between two clusters in different zones

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic single-row operations

ACID

MVCC

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

User concepts

Access control

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

Administrators and common users accounts

fine grained access rights according to SQL-standard

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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

Google says it'll stop charging fees to transfer data out of Google Cloud
11 January 2024, TechCrunch

Google Introduces Autoscaling for Cloud Bigtable for Optimizing Costs
31 January 2022, InfoQ.com

Google scales up Cloud Bigtable NoSQL database
27 January 2022, TechTarget

Review: Google Bigtable scales with ease
7 September 2016, InfoWorld

Google introduces Cloud Bigtable managed NoSQL database to process data at scale
6 May 2015, VentureBeat

provided by Google News

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

Grafana Labs Announces Mimir Time Series Database
1 April 2022, Datanami

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

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

How Grafana made observability accessible
12 June 2023, InfoWorld

provided by Google News

About HUAWEI Open Source
9 February 2022, Huawei

provided by Google News

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