DBMS > Amazon Redshift vs. Google BigQuery vs. Google Cloud Datastore vs. InfluxDB

System Properties Comparison Amazon Redshift vs. Google BigQuery vs. Google Cloud Datastore vs. InfluxDB

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Large scale data warehouse service with append-only tables

Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform

DBMS for storing time series, events and metrics

Primary database model

Relational DBMS

Document store

Time Series DBMS

Secondary database models

Spatial DBMS

with GEO package

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	4.47
Rank	#76	Overall
	#12	Document stores

Score	25.83
Rank	#28	Overall
	#1	Time Series DBMS

Website

aws.amazon.com/redshift

cloud.google.com/bigquery

cloud.google.com/datastore

www.influxdata.com/products/influxdb-overview

Technical documentation

docs.aws.amazon.com/redshift

cloud.google.com/bigquery/docs

cloud.google.com/datastore/docs

docs.influxdata.com/influxdb

Developer

Amazon (based on PostgreSQL)

Google

Initial release

2012

2010

2008

2013

Current release

2.7.6, April 2024

License

Commercial or Open Source

commercial

Open Source

MIT-License; commercial enterprise version available

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

Server operating systems

hosted

Linux
OS X

through Homebrew

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, details here

Numeric data and Strings

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

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

SQL-like query language (GQL)

SQL-like query language

APIs and other access methods

JDBC
ODBC

RESTful HTTP/JSON API

gRPC (using protocol buffers) API
RESTful HTTP/JSON API

HTTP API
JSON over UDP

Supported programming languages

All languages supporting JDBC/ODBC

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala

Server-side scripts

Stored procedures

user defined functions

in Python

user defined functions

in JavaScript

using Google App Engine

Triggers

Callbacks using the Google Apps Engine

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

in enterprise version only

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication using Paxos

selectable replication factor

in enterprise version only

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on type of query and configuration

Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

via ReferenceProperties or Ancestor paths

Transaction concepts

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

ACID

Since BigQuery is designed for querying data

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

Depending on used storage engine

User concepts

Access control

fine grained access rights according to SQL-standard

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

Google Cloud Identity & Access Management (IAM)

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

simple rights management via user accounts

More information provided by the system vendor

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