DBMS > DolphinDB vs. Google BigQuery vs. InfluxDB vs. OpenQM

System Properties Comparison DolphinDB vs. Google BigQuery vs. InfluxDB vs. OpenQM

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Editorial information provided by DB-Engines

Name

Description

DolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.

Large scale data warehouse service with append-only tables

DBMS for storing time series, events and metrics

QpenQM is a high-performance, self-tuning, multi-value DBMS

Primary database model

Secondary database models

Relational DBMS

Spatial DBMS

with GEO package

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

Score	4.03
Rank	#78	Overall
	#6	Time Series DBMS

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	24.39
Rank	#28	Overall
	#1	Time Series DBMS

Score	0.34
Rank	#284	Overall
	#10	Multivalue DBMS

Website

www.dolphindb.com

cloud.google.com/bigquery

www.influxdata.com/products/influxdb-overview

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

Technical documentation

docs.dolphindb.cn/en/help200/index.html

cloud.google.com/bigquery/docs

docs.influxdata.com/influxdb

Developer

DolphinDB, Inc

Google

Rocket Software, originally Martin Phillips

Initial release

2018

2010

2013

1993

Current release

v2.00.4, January 2022

2.7.6, April 2024

3.4-12

License

Commercial or Open Source

commercial

free community version available

commercial

Open Source

MIT-License; commercial enterprise version available

Open Source

GPLv2, extended commercial license 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

C++

Server operating systems

Linux
Windows

hosted

Linux
OS X

through Homebrew

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Data scheme

yes

schema-free

yes

with some exceptions

Typing

predefined data types such as float or date

yes

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

SQL-like query language

APIs and other access methods

JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket

RESTful HTTP/JSON API

HTTP API
JSON over UDP

Supported programming languages

C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust

.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

.Net
Basic
C
Java
Objective C
PHP
Python

Server-side scripts

Stored procedures

yes

user defined functions

in JavaScript

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

Sharding

in enterprise version only

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

in enterprise version only

yes

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

Transaction concepts

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

yes

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

Administrators, Users, Groups

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

Google Cloud Identity & Access Management (IAM)

simple rights management via user accounts

Access rights can be defined down to the item level

More information provided by the system vendor

Specific characteristics

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Typical application scenarios

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Key customers

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Market metrics

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Licensing and pricing models

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