DBMS > Google BigQuery vs. ReductStore vs. RethinkDB vs. TerminusDB

System Properties Comparison Google BigQuery vs. ReductStore vs. RethinkDB vs. TerminusDB

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

Designed to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Primary database model

Secondary database models

Spatial DBMS

Document store
RDF store

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

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	0.05
Rank	#384	Overall
	#44	Time Series DBMS

Score	2.66
Rank	#107	Overall
	#20	Document stores

Score	0.23
Rank	#316	Overall
	#27	Graph DBMS

Website

cloud.google.com/bigquery

github.com/reductstore
www.reduct.store

rethinkdb.com

terminusdb.com

Technical documentation

cloud.google.com/bigquery/docs

www.reduct.store/docs

rethinkdb.com/docs

terminusdb.github.io/terminusdb/#

Developer

Google

ReductStore LLC

The Linux Foundation

since July 2017

DataChemist Ltd.

Initial release

2010

2023

2009

2018

Current release

1.9, March 2024

2.4.1, August 2020

11.0.0, January 2023

License

Commercial or Open Source

commercial

Open Source

Business Source License 1.1

Open Source

Apache Version 2

Open Source

GPL V3

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++, Rust

C++

Prolog, Rust

Server operating systems

hosted

Docker
Linux
macOS
Windows

Linux
OS X
Windows

Linux

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

string, binary, float, bool, date, geometry

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

yes

SQL-like query language (WOQL)

APIs and other access methods

RESTful HTTP/JSON API

HTTP API

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C++
JavaScript (Node.js)
Python
Rust

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

JavaScript
Python

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

Triggers

Client-side triggers through changefeeds

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

range based

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate 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 single-document operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

MVCC based

yes

Durability

Support for making data persistent

yes

in-memory journaling

In-memory capabilities

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

User concepts

Access control

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

Google Cloud Identity & Access Management (IAM)

yes

users and table-level permissions

Role-based access control

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