DBMS > Galaxybase vs. Google BigQuery vs. Quasardb vs. Riak KV vs. SiteWhere

System Properties Comparison Galaxybase vs. Google BigQuery vs. Quasardb vs. Riak KV vs. SiteWhere

Editorial information provided by DB-Engines

Name

Description

Scalable, ACID-compliant native distributed parallel graph platform

Large scale data warehouse service with append-only tables

Distributed, high-performance timeseries database

Distributed, fault tolerant key-value store

M2M integration platform for persisting/querying time series data

Primary database model

with links between data sets and object tags for the creation of secondary indexes

Time Series DBMS

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

Score	0.00
Rank	#383	Overall
	#39	Graph DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Score	4.10
Rank	#82	Overall
	#9	Key-value stores

Score	0.06
Rank	#356	Overall
	#35	Time Series DBMS

Website

galaxybase.com

cloud.google.com/bigquery

quasar.ai

github.com/sitewhere/sitewhere

Technical documentation

cloud.google.com/bigquery/docs

doc.quasar.ai/master

www.tiot.jp/riak-docs/riak/kv/latest

sitewhere1.sitewhere.io/index.html

Developer

Chuanglin(Createlink) Technology Co., Ltd 浙江创邻科技有限公司

Google

quasardb

OpenSource, formerly Basho Technologies

SiteWhere

Initial release

2017

2010

2009

2010

Current release

Nov 20, November 2021

3.14.1, January 2024

3.2.0, December 2022

License

Commercial or Open Source

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

Open Source

Apache version 2, commercial enterprise edition

Open Source

Common Public Attribution License Version 1.0

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 and Java

C++

Erlang

Java

Server operating systems

Linux

hosted

BSD
Linux
OS X
Windows

Linux
OS X

Linux
OS X
Windows

Data scheme

Strong typed schema

yes

schema-free

predefined scheme

Typing

predefined data types such as float or date

yes

integer and binary

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.

Secondary indexes

yes

with tags

restricted

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

Browser interface
console (shell)
Graph API (Gremlin)
OpenCypher
Proprietary native API

RESTful HTTP/JSON API

HTTP API

HTTP API
Native Erlang Interface

HTTP REST

Supported programming languages

Go
Java
Python

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

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

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

user defined procedures and functions

user defined functions

in JavaScript

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

consistent hashing

Sharding

no "single point of failure"

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication with selectable replication factor

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

links between data sets can be stored

Transaction concepts

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

ACID

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using LevelDB

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Transient mode

User concepts

Access control

Role-based access control

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

Google Cloud Identity & Access Management (IAM)

Cryptographically strong user authentication and audit trail

yes, using Riak Security

Users with fine-grained authorization concept

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