DBMS > Google BigQuery vs. RethinkDB vs. Spark SQL vs. TinkerGraph vs. Transbase

System Properties Comparison Google BigQuery vs. RethinkDB vs. Spark SQL vs. TinkerGraph vs. Transbase

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

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

Spark SQL is a component on top of 'Spark Core' for structured data processing

A lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Secondary database models

Spatial DBMS

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Trend Chart

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	2.66
Rank	#107	Overall
	#20	Document stores

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Score	0.13
Rank	#345	Overall
	#35	Graph DBMS

Score	0.17
Rank	#334	Overall
	#148	Relational DBMS

Website

cloud.google.com/bigquery

rethinkdb.com

spark.apache.org/sql

tinkerpop.apache.org/docs/current/reference/#tinkergraph-gremlin

www.transaction.de/en/products/transbase.html

Technical documentation

cloud.google.com/bigquery/docs

rethinkdb.com/docs

spark.apache.org/docs/latest/sql-programming-guide.html

www.transaction.de/en/products/transbase/features.html

Developer

Google

The Linux Foundation

since July 2017

Apache Software Foundation

Transaction Software GmbH

Initial release

2010

2009

2014

2009

1987

Current release

2.4.1, August 2020

3.5.0 ( 2.13), September 2023

Transbase 8.3, 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

Open Source

Apache 2.0

Open Source

Apache 2.0

commercial

free development license

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Scala

Java

C and C++

Server operating systems

hosted

Linux
OS X
Windows

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

yes

schema-free

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 DML and DDL statements

yes

APIs and other access methods

RESTful HTTP/JSON API

JDBC
ODBC

TinkerPop 3

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

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

Java
Python
R
Scala

Groovy
Java

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
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

yes, utilizing Spark Core

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

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

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

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

yes

Concurrency

Support for concurrent manipulation of data

yes

MVCC based

yes

Durability

Support for making data persistent

yes

optional

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

users and table-level permissions

fine grained access rights according to SQL-standard

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