DBMS > Google BigQuery vs. NSDb vs. OpenMLDB vs. Trino

System Properties Comparison Google BigQuery vs. NSDb vs. OpenMLDB vs. Trino

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

An open-source machine learning database that provides a feature platform for training and inference

Fast distributed SQL query engine for big data analytics. Forked from Presto and originally named PrestoSQL

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Relational DBMS

Document store
Key-value store
Spatial DBMS
Search engine
Time Series DBMS
Wide column store

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

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	0.02
Rank	#367	Overall
	#37	Time Series DBMS

Score	5.00
Rank	#66	Overall
	#36	Relational DBMS

Website

cloud.google.com/bigquery

nsdb.io

openmldb.ai

trino.io

Technical documentation

cloud.google.com/bigquery/docs

nsdb.io/Architecture

openmldb.ai/docs/zh/main

trino.io/broadcast
trino.io/docs/current

Social network pages

Developer

Google

4 Paradigm Inc.

Trino Software Foundation

Initial release

2010

2017

2020

2012

2020 rebranded from PrestoSQL

Current release

2024-2 February 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

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.

Starburst Galaxy offers a feature-rich user interface to connect all your data sources, manage your Trino clusters, and query your data.

Implementation language

Java, Scala

C++, Java, Scala

Java

Server operating systems

hosted

Linux
macOS

Linux

Linux
macOS

for devlopment

Data scheme

yes

Fixed schema

yes

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

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

all fields are automatically indexed

yes

depending on connected data-source

SQL

Support of SQL

yes

SQL-like query language

yes

APIs and other access methods

RESTful HTTP/JSON API

gRPC
HTTP REST
WebSocket

JDBC
SQLAlchemy

JDBC
RESTful HTTP API
Trino CLI

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Java
Scala

C++
Go
Java
Python
Scala

Go
Java
JavaScript (Node.js)
Python
R
Ruby

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes, depending on connected data-source

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning

depending on connected data-source

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

depending on connected data-source

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

depending on connected data-source

Foreign keys

Referential integrity

Transaction concepts

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

Since BigQuery is designed for querying data

depending on connected data-source

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Using Apache Lucene

yes

depending on connected data-source

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)

fine grained access rights according to SQL-standard

SQL standard access control

More information provided by the system vendor

Specific characteristics

Trino is the fastest open source, massively parallel processing SQL query engine...
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Competitive advantages

High performance analtyics and data processing of very large data sets Powerful ANSI...
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Typical application scenarios

Performant analytics query engine for data warehouses, data lakes, and data lakehouses...
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Key customers

Trino is widely adopted across the globe as freely-available open source software....
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Market metrics

33000+ commits in GitHub 8200+ stargazers in GitHub 1200+ pull requests merged in...
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Licensing and pricing models

Trino is an open source project and usage is therefore free. Commercial offerings...
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News

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8 May 2024

59: Querying Trino with Java and jOOQ
24 April 2024

A sneak peek of Trino Fest 2024
15 April 2024

Time travel in Delta Lake connector
11 April 2024

58: Understanding your users with Trino and Mitzu
4 April 2024

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.