DBMS > Google BigQuery vs. LokiJS vs. Memcached vs. Sequoiadb

System Properties Comparison Google BigQuery vs. LokiJS vs. Memcached vs. Sequoiadb

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

In-memory JavaScript DBMS

In-memory key-value store, originally intended for caching

NewSQL database with distributed OLTP and SQL

Primary database model

Relational DBMS

Document store

Key-value store

Document store
Relational DBMS

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

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	0.43
Rank	#264	Overall
	#42	Document stores

Score	19.42
Rank	#32	Overall
	#4	Key-value stores

Score	0.45
Rank	#261	Overall
	#41	Document stores
	#122	Relational DBMS

Website

cloud.google.com/bigquery

github.com/techfort/LokiJS

www.memcached.org

www.sequoiadb.com

Technical documentation

cloud.google.com/bigquery/docs

techfort.github.io/LokiJS

github.com/memcached/memcached/wiki

www.sequoiadb.com/en/index.php?m=Files&a=index

Developer

Google

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

Sequoiadb Ltd.

Initial release

2010

2014

2003

2013

Current release

1.6.25, March 2024

License

Commercial or Open Source

commercial

Open Source

BSD license

Open Source

Server: AGPL; Client: Apache V2

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

JavaScript

C++

Server operating systems

hosted

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

FreeBSD
Linux
OS X
Unix
Windows

Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

oid, date, timestamp, binary, regex

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

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

RESTful HTTP/JSON API

JavaScript API

Proprietary protocol

proprietary protocol using JSON

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

JavaScript

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby

.Net
C++
Java
PHP
Python

Server-side scripts

Stored procedures

user defined functions

in JavaScript

View functions in JavaScript

JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Repcached, a Memcached patch, provides this functionallity

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Eventual Consistency

Foreign keys

Referential integrity

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

Document is locked during a transaction

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

In-memory capabilities

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

yes

User concepts

Access control

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

Google Cloud Identity & Access Management (IAM)

yes

using SASL (Simple Authentication and Security Layer) protocol

simple password-based access control

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