DBMS > BigObject vs. BoltDB vs. Google BigQuery vs. Lovefield

System Properties Comparison BigObject vs. BoltDB vs. Google BigQuery vs. Lovefield

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

An embedded key-value store for Go.

Large scale data warehouse service with append-only tables

Embeddable relational database for web apps written in pure JavaScript

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Key-value store

Relational DBMS

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

Score	0.19
Rank	#329	Overall
	#146	Relational DBMS

Score	0.80
Rank	#215	Overall
	#31	Key-value stores

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Website

bigobject.io

github.com/boltdb/bolt

cloud.google.com/bigquery

google.github.io/lovefield

Technical documentation

docs.bigobject.io

cloud.google.com/bigquery/docs

github.com/google/lovefield/blob/master/docs/spec_index.md

Developer

BigObject, Inc.

Google

Initial release

2015

2013

2010

2014

Current release

2.1.12, February 2017

License

Commercial or Open Source

commercial

free community edition available

Open Source

MIT License

commercial

Open Source

Apache 2.0

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

JavaScript

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

BSD
Linux
OS X
Solaris
Windows

hosted

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

tested with Chrome, Firefox, IE, Safari

Data scheme

yes

schema-free

yes

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

SQL

Support of SQL

SQL-like DML and DDL statements

yes

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

RESTful HTTP/JSON API

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

JavaScript

Server-side scripts

Stored procedures

Lua

user defined functions

in JavaScript

Triggers

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

Transaction concepts

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

yes

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

In-memory capabilities

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

yes

using MemoryDB

User concepts

Access control

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

Google Cloud Identity & Access Management (IAM)

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