DBMS > Google BigQuery vs. Kinetica vs. LokiJS vs. openGauss vs. PouchDB

System Properties Comparison Google BigQuery vs. Kinetica vs. LokiJS vs. openGauss vs. PouchDB

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

Fully vectorized database across both GPUs and CPUs

In-memory JavaScript DBMS

An enterprise-class RDBMS compatible with high-performance, high-availability and high-performance originally developed by Huawei

JavaScript DBMS with an API inspired by CouchDB

Primary database model

Secondary database models

Spatial DBMS
Time Series DBMS

Document store
Spatial DBMS

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

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	0.66
Rank	#234	Overall
	#107	Relational DBMS

Score	0.49
Rank	#260	Overall
	#42	Document stores

Score	1.06
Rank	#184	Overall
	#84	Relational DBMS

Score	2.34
Rank	#112	Overall
	#21	Document stores

Website

cloud.google.com/bigquery

www.kinetica.com

github.com/techfort/LokiJS

gitee.com/opengauss
opengauss.org

pouchdb.com

Technical documentation

cloud.google.com/bigquery/docs

docs.kinetica.com

techfort.github.io/LokiJS

docs.opengauss.org/en
gitee.com/opengauss/docs

pouchdb.com/guides

Developer

Google

Kinetica

Huawei and openGauss community

Apache Software Foundation

Initial release

2010

2012

2014

2019

2012

Current release

7.1, August 2021

3.0, March 2022

7.1.1, June 2019

License

Commercial or Open Source

commercial

Open Source

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++

JavaScript

C, C++, Java

JavaScript

Server operating systems

hosted

Linux

server-less, requires a JavaScript environment (browser, Node.js)

Linux

server-less, requires a JavaScript environment (browser, Node.js)

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

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

via views

yes

via views

SQL

Support of SQL

yes

SQL-like DML and DDL statements

ANSI SQL 2011

APIs and other access methods

RESTful HTTP/JSON API

JDBC
ODBC
RESTful HTTP API

JavaScript API

JDBC
ODBC

HTTP REST

only for PouchDB Server
JavaScript API

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C++
Java
JavaScript (Node.js)
Python

JavaScript

C
C++
Java

JavaScript

Server-side scripts

Stored procedures

user defined functions

in JavaScript

user defined functions

View functions in JavaScript

yes

View functions in JavaScript

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

horizontal partitioning (by range, list and hash)

Sharding

with a proxy-based framework, named couchdb-lounge

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

Source-replica replication

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

none

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Since BigQuery is designed for querying data

atomic operations within a single collection possible

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Serialization of a DB in a Node.JS/Cordova/PhoneGap environment. Usage of the IndexedDB-API in a browser.

yes

by using IndexedDB, WebSQL or LevelDB as backend

In-memory capabilities

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

yes

GPU vRAM or System RAM

yes

User concepts

Access control

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

Google Cloud Identity & Access Management (IAM)

Access rights for users and roles on table level

Access rights for users, groups and roles according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.