DBMS > GBase vs. Google BigQuery vs. OpenTSDB vs. PlanetScale vs. WakandaDB

System Properties Comparison GBase vs. Google BigQuery vs. OpenTSDB vs. PlanetScale vs. WakandaDB

Editorial information provided by DB-Engines

Name

Description

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

Large scale data warehouse service with append-only tables

Scalable Time Series DBMS based on HBase

Scalable, distributed, serverless MySQL database platform built on top of Vitess

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

Secondary database models

Document store
Spatial DBMS

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

Score	1.05
Rank	#186	Overall
	#86	Relational DBMS

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	1.68
Rank	#142	Overall
	#12	Time Series DBMS

Score	1.49
Rank	#155	Overall
	#72	Relational DBMS

Score	0.10
Rank	#356	Overall
	#16	Object oriented DBMS

Website

www.gbase.cn

cloud.google.com/bigquery

opentsdb.net

planetscale.com

wakanda.github.io

Technical documentation

cloud.google.com/bigquery/docs

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

planetscale.com/docs

wakanda.github.io/doc

Developer

General Data Technology Co., Ltd.

Google

currently maintained by Yahoo and other contributors

PlanetScale

Wakanda SAS

Initial release

2004

2010

2011

2020

2012

Current release

GBase 8a, GBase 8s, GBase 8c

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

commercial

Open Source

LGPL

commercial

Open Source

AGPLv3, extended 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, Python

Java

C++, JavaScript

Server operating systems

Linux

hosted

Linux
Windows

Docker
Linux
macOS

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

numeric data for metrics, strings for tags

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

Standard with numerous extensions

yes

with proprietary extensions

APIs and other access methods

ADO.NET
C API
JDBC
ODBC

RESTful HTTP/JSON API

HTTP API
Telnet API

ADO.NET
JDBC
MySQL protocol
ODBC

RESTful HTTP API

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Erlang
Go
Java
Python
R
Ruby

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

JavaScript

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

proprietary syntax

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

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

none

Sharding

based on HBase

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

based on HBase

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

based on HBase

Eventual Consistency across shards
Immediate Consistency within a shard

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

Since BigQuery is designed for querying data

ACID at shard level

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

Users with fine-grained authorization concept

no user groups or roles

yes

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