DBMS > Apache Doris vs. Google BigQuery vs. InfluxDB vs. Linter

System Properties Comparison Apache Doris vs. Google BigQuery vs. InfluxDB vs. Linter

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Editorial information provided by DB-Engines

Name

Description

An MPP-based analytics DBMS embracing the MySQL protocol

Large scale data warehouse service with append-only tables

DBMS for storing time series, events and metrics

RDBMS for high security requirements

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Spatial DBMS

with GEO package

Spatial DBMS

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

Score	0.69
Rank	#237	Overall
	#108	Relational DBMS

Score	61.90
Rank	#19	Overall
	#13	Relational DBMS

Score	26.56
Rank	#28	Overall
	#1	Time Series DBMS

Score	0.10
Rank	#350	Overall
	#153	Relational DBMS

Website

doris.apache.org
github.com/apache/doris

cloud.google.com/bigquery

www.influxdata.com/products/influxdb-overview

linter.ru

Technical documentation

github.com/apache/doris/wiki

cloud.google.com/bigquery/docs

docs.influxdata.com/influxdb

Developer

Apache Software Foundation, originally contributed from Baidu

Google

relex.ru

Initial release

2017

2010

2013

1990

Current release

1.2.2, February 2023

2.7.5, January 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

MIT-License; commercial enterprise version available

commercial

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

Java

C and C++

Server operating systems

Linux

hosted

Linux
OS X

through Homebrew

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

Numeric data and Strings

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

yes

APIs and other access methods

JDBC
MySQL client

RESTful HTTP/JSON API

HTTP API
JSON over UDP

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

Supported programming languages

Java

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

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

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

proprietary syntax with the possibility to convert from PL/SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

Sharding

in enterprise version only

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

in enterprise version only

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

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

ACID

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)

simple rights management via user accounts

fine grained access rights according to SQL-standard

More information provided by the system vendor

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