DBMS > DuckDB vs. Google BigQuery vs. InfluxDB vs. LevelDB vs. Quasardb

System Properties Comparison DuckDB vs. Google BigQuery vs. InfluxDB vs. LevelDB vs. Quasardb

Editorial information provided by DB-Engines

Name

Description

An embeddable, in-process, column-oriented SQL OLAP RDBMS

Large scale data warehouse service with append-only tables

DBMS for storing time series, events and metrics

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

Distributed, high-performance timeseries database

Primary database model

Secondary database models

Spatial DBMS

with GEO package

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

Score	4.63
Rank	#69	Overall
	#37	Relational DBMS

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	24.39
Rank	#28	Overall
	#1	Time Series DBMS

Score	2.25
Rank	#115	Overall
	#19	Key-value stores

Score	0.21
Rank	#322	Overall
	#29	Time Series DBMS

Website

duckdb.org

cloud.google.com/bigquery

www.influxdata.com/products/influxdb-overview

github.com/google/leveldb

quasar.ai

Technical documentation

duckdb.org/docs

cloud.google.com/bigquery/docs

docs.influxdata.com/influxdb

github.com/google/leveldb/blob/main/doc/index.md

doc.quasar.ai/master

Developer

Google

quasardb

Initial release

2018

2010

2013

2011

2009

Current release

1.0.0, June 2024

2.7.6, April 2024

1.23, February 2021

3.14.1, January 2024

License

Commercial or Open Source

Open Source

MIT License

commercial

Open Source

MIT-License; commercial enterprise version available

Open Source

BSD

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

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++

Server operating systems

server-less

hosted

Linux
OS X

through Homebrew

Illumos
Linux
OS X
Windows

BSD
Linux
OS X
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

Numeric data and Strings

yes

integer and binary

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

with tags

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

Arrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC

RESTful HTTP/JSON API

HTTP API
JSON over UDP

HTTP API

Supported programming languages

C
C#

3rd party driver
C++
Crystal

3rd party driver
Go

3rd party driver
Java
Lisp

3rd party driver
Python
R
Ruby

3rd party driver
Rust
Swift
Zig

3rd party driver

.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++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

Server-side scripts

Stored procedures

user defined functions

in JavaScript

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

in enterprise version only

none

Sharding

consistent hashing

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

in enterprise version only

none

Source-replica replication with selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

yes

by using LevelDB

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

yes

Transient mode

User concepts

Access control

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

Google Cloud Identity & Access Management (IAM)

simple rights management via user accounts

Cryptographically strong user authentication and audit trail

More information provided by the system vendor

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Market metrics

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Licensing and pricing models

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