DBMS > Apache Druid vs. Snowflake vs. TerminusDB vs. Trino

System Properties Comparison Apache Druid vs. Snowflake vs. TerminusDB vs. Trino

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Editorial information provided by DB-Engines

Name

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

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

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

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

Graph DBMS

Relational DBMS

Secondary database models

Document store
RDF store

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	2.85
Rank	#96	Overall
	#50	Relational DBMS
	#6	Time Series DBMS

Score	133.72
Rank	#7	Overall
	#5	Relational DBMS

Score	0.19
Rank	#311	Overall
	#27	Graph DBMS

Score	5.28
Rank	#61	Overall
	#35	Relational DBMS

Website

Technical documentation

druid.apache.org/docs/latest/design

docs.snowflake.net/manuals/index.html

terminusdb.github.io/terminusdb/#

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

Developer

Apache Software Foundation and contributors

Snowflake Computing Inc.

DataChemist Ltd.

Trino Software Foundation

Initial release

2012

2014

2018

2012

2020 rebranded from PrestoSQL

Current release

30.0.0, June 2024

11.0.0, January 2023

License

Commercial or Open Source

Open Source

Apache license v2

commercial

Open Source

GPL V3

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.

Implementation language

Java

Prolog, Rust

Java

Server operating systems

Linux
OS X
Unix

hosted

Linux

Linux
macOS

for devlopment

Data scheme

yes

schema-less columns are supported

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

SQL for querying

yes

SQL-like query language (WOQL)

yes

APIs and other access methods

JDBC
RESTful HTTP/JSON API

CLI Client
JDBC
ODBC

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

JDBC
RESTful HTTP API
Trino CLI

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

JavaScript (Node.js)
Python

JavaScript
Python

Go
Java
JavaScript (Node.js)
Python
R
Ruby

Server-side scripts

Stored procedures

user defined functions

yes

yes, depending on connected data-source

Triggers

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

yes

Graph Partitioning

depending on connected data-source

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

yes

Journaling Streams

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

depending on connected data-source

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

depending on connected data-source

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory journaling

depending on connected data-source

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

User concepts

Access control

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

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

Role-based access control

SQL standard access control

More information provided by the system vendor

News

23 is a go, keeping pace with Java
17 September 2024

65: Performance boosts
12 September 2024

64: Control with Open Policy Agent OPA
22 August 2024

63: Querying with JS
1 August 2024

62: A lakehouse that simply works at Prezi
11 July 2024

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