DBMS > OushuDB vs. QuestDB vs. Snowflake vs. Splice Machine vs. Trino

System Properties Comparison OushuDB vs. QuestDB vs. Snowflake vs. Splice Machine vs. Trino

Editorial information provided by DB-Engines

Name

Description

A data warehouse powered by Apache HAWQ supporting descriptive analysis and advanced machine learning

A high performance open source SQL database for time series data

Cloud-based data warehousing service for structured and semi-structured data

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

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	0.04
Rank	#363	Overall
	#154	Relational DBMS

Score	2.52
Rank	#109	Overall
	#9	Time Series DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	0.54
Rank	#250	Overall
	#114	Relational DBMS

Score	5.00
Rank	#66	Overall
	#36	Relational DBMS

Website

www.oushu.com/product/oushuDB

Technical documentation

www.oushu.com/documentation

questdb.io/docs

docs.snowflake.net/manuals/index.html

splicemachine.com/how-it-works

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

Social network pages

Developer

Oushu

QuestDB Technology Inc

Snowflake Computing Inc.

Splice Machine

Trino Software Foundation

Initial release

2014

2012

2020 rebranded from PrestoSQL

Current release

4.0.1, August 2020

3.1, March 2021

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

Open Source

AGPL 3.0, commercial license available

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 (Zero-GC), C++, Rust

Java

Server operating systems

Linux

Linux
macOS
Windows

hosted

Linux
OS X
Solaris
Windows

Linux
macOS

for devlopment

Data scheme

yes

schema-free via InfluxDB Line Protocol

yes

support of semi-structured data formats (JSON, XML, Avro)

yes

Typing

predefined data types such as float or date

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.

yes

Secondary indexes

yes

depending on connected data-source

SQL

Support of SQL

Full-featured ANSI SQL support

SQL with time-series extensions

yes

APIs and other access methods

JDBC
ODBC

HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol

CLI Client
JDBC
ODBC

JDBC
Native Spark Datasource
ODBC

JDBC
RESTful HTTP API
Trino CLI

Supported programming languages

C
C++

PostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust

over HTTP

JavaScript (Node.js)
Python

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

Go
Java
JavaScript (Node.js)
Python
R
Ruby

Server-side scripts

Stored procedures

yes

user defined functions

yes

Java

yes, depending on connected data-source

Triggers

yes

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

yes

horizontal partitioning (by timestamps)

yes

Shared Nothhing Auto-Sharding, Columnar Partitioning

depending on connected data-source

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication with eventual consistency

yes

Multi-source replication
Source-replica replication

depending on connected data-source

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

depending on connected data-source

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

ACID for single-table writes

ACID

depending on connected data-source

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

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

through memory mapped files

yes

User concepts

Access control

Kerberos, SSL and role based access

Users with fine-grained authorization concept, user roles and pluggable authentication

Access rights for users, groups and roles according to SQL-standard

SQL standard access control

More information provided by the system vendor

Specific characteristics

Relational model with native time series support Column-based storage and time partitioned...
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Trino is the fastest open source, massively parallel processing SQL query engine...
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Competitive advantages

High ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
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High performance analtyics and data processing of very large data sets Powerful ANSI...
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Typical application scenarios

Financial tick data Industrial IoT Application Metrics Monitoring
» more

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

Banks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
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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

Open source Apache 2.0 QuestDB Enterprise QuestDB Cloud
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Trino is an open source project and usage is therefore free. Commercial offerings...
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59: Querying Trino with Java and jOOQ
24 April 2024

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15 April 2024

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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.