DBMS > Google BigQuery vs. Graph Engine vs. LokiJS vs. Qdrant

System Properties Comparison Google BigQuery vs. Graph Engine vs. LokiJS vs. Qdrant

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

In-memory JavaScript DBMS

A high-performance vector database with neural network or semantic-based matching

Primary database model

Relational DBMS

Graph DBMS
Key-value store

Document store

Vector DBMS

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

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	0.67
Rank	#232	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	0.49
Rank	#260	Overall
	#42	Document stores

Score	1.28
Rank	#167	Overall
	#6	Vector DBMS

Website

cloud.google.com/bigquery

www.graphengine.io

github.com/techfort/LokiJS

github.com/qdrant/qdrant
qdrant.tech

Technical documentation

cloud.google.com/bigquery/docs

www.graphengine.io/docs/manual

techfort.github.io/LokiJS

qdrant.tech/documentation

Developer

Google

Microsoft

Qdrant

Initial release

2010

2014

2021

License

Commercial or Open Source

commercial

Open Source

MIT License

Open Source

Apache Version 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

.NET and C

JavaScript

Rust

Server operating systems

hosted

.NET

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

Docker
Linux
macOS
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

Numbers, Strings, Geo, Boolean

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

Keywords, numberic ranges, geo, full-text

SQL

Support of SQL

yes

APIs and other access methods

RESTful HTTP/JSON API

RESTful HTTP API

JavaScript API

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C#
C++
F#
Visual Basic

JavaScript

.Net
Go
Java
JavaScript (Node.js)
Python
Rust

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

View functions in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Collection-level 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, tunable 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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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)

Key-based authentication

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