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

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

Editorial information provided by DB-Engines

Name

Description

A distributed reliable key-value store

Large scale data warehouse service with append-only tables

Fully vectorized database across both GPUs and CPUs

In-memory JavaScript DBMS

JavaScript DBMS with an API inspired by CouchDB

Primary database model

Key-value store

Relational DBMS

Document store

Secondary database models

Spatial DBMS
Time Series DBMS

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

Score	7.03
Rank	#54	Overall
	#5	Key-value stores

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	2.34
Rank	#112	Overall
	#21	Document stores

Website

etcd.io
github.com/etcd-io/etcd

cloud.google.com/bigquery

www.kinetica.com

github.com/techfort/LokiJS

pouchdb.com

Technical documentation

etcd.io/docs
github.com/etcd-io/etcd/tree/master/Documentation

cloud.google.com/bigquery/docs

docs.kinetica.com

techfort.github.io/LokiJS

pouchdb.com/guides

Developer

Google

Kinetica

Apache Software Foundation

Initial release

2010

2012

2014

2012

Current release

3.4, August 2019

7.1, August 2021

7.1.1, June 2019

License

Commercial or Open Source

Open Source

Apache Version 2.0

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

Server operating systems

FreeBSD
Linux
Windows

experimental

hosted

Linux

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

Data scheme

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

APIs and other access methods

gRPC
JSON over HTTP

RESTful HTTP/JSON API

JDBC
ODBC
RESTful HTTP API

JavaScript API

HTTP REST

only for PouchDB Server
JavaScript API

Supported programming languages

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C++
Java
JavaScript (Node.js)
Python

JavaScript

Server-side scripts

Stored procedures

user defined functions

in JavaScript

user defined functions

View functions in JavaScript

Triggers

yes, watching key changes

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

Sharding

with a proxy-based framework, named couchdb-lounge

Replication methods

Methods for redundantly storing data on multiple nodes

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

Source-replica replication

none

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

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

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

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