DBMS > Google Cloud Bigtable vs. gStore vs. OpenTSDB vs. STSdb

System Properties Comparison Google Cloud Bigtable vs. gStore vs. OpenTSDB vs. STSdb

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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.

A native Graph DBMS to store and maintain very large RDF datasets.

Scalable Time Series DBMS based on HBase

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Key-value store
Wide column store

Graph DBMS
RDF store

Time Series DBMS

Key-value store

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

Score	2.97
Rank	#92	Overall
	#15	Key-value stores
	#8	Wide column stores

Score	0.03
Rank	#367	Overall
	#37	Graph DBMS
	#18	RDF stores

Score	1.59
Rank	#140	Overall
	#12	Time Series DBMS

Score	0.03
Rank	#365	Overall
	#54	Key-value stores

Website

cloud.google.com/bigtable

en.gstore.cn

opentsdb.net

github.com/STSSoft/STSdb4

Technical documentation

cloud.google.com/bigtable/docs

en.gstore.cn/#/enDocs

opentsdb.net/docs/build/html/index.html

Developer

Google

currently maintained by Yahoo and other contributors

STS Soft SC

Initial release

2015

2016

2011

Current release

1.2, November 2023

4.0.8, September 2015

License

Commercial or Open Source

commercial

Open Source

BSD

Open Source

LGPL

Open Source

GPLv2, commercial license available

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++

Java

Server operating systems

hosted

Linux

Linux
Windows

Windows

Data scheme

schema-free

schema-free and OWL/RDFS-schema support

schema-free

yes

Typing

predefined data types such as float or date

yes

numeric data for metrics, strings for tags

yes

primitive types and user defined types (classes)

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

SQL

Support of SQL

APIs and other access methods

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

HTTP API
SPARQL 1.1

HTTP API
Telnet API

.NET Client API

Supported programming languages

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

C++
Java
JavaScript (Node.js)
PHP
Python

Erlang
Go
Java
Python
R
Ruby

C#
Java

Server-side scripts

Stored procedures

yes

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on HBase

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

selectable replication factor

based on HBase

none

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)

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

Transaction concepts

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

Atomic single-row operations

yes

Concurrency

Support for concurrent manipulation of data

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.

User concepts

Access control

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

Users, roles and permissions, Role-Based Access Control (RBAC) supported

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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

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Recent citations in the news

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