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

System Properties Comparison Apache Druid vs. Netezza 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

Data warehouse and analytics appliance part of IBM PureSystems

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	7.56
Rank	#48	Overall
	#31	Relational DBMS

Score	0.19
Rank	#311	Overall
	#27	Graph DBMS

Score	5.28
Rank	#61	Overall
	#35	Relational DBMS

Website

druid.apache.org

www.ibm.com/products/netezza

terminusdb.com

trino.io

Technical documentation

druid.apache.org/docs/latest/design

terminusdb.github.io/terminusdb/#

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

Developer

Apache Software Foundation and contributors

IBM

DataChemist Ltd.

Trino Software Foundation

Initial release

2012

2000

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

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

Linux

included in appliance

Linux

Linux
macOS

for devlopment

Data scheme

yes

schema-less columns are supported

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.

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

JDBC
ODBC
OLE DB

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

C
C++
Fortran
Java
Lua
Perl
Python
R

JavaScript
Python

Go
Java
JavaScript (Node.js)
Python
R
Ruby

Server-side scripts

Stored procedures

yes

yes, depending on connected data-source

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Sharding

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

Source-replica replication

Journaling Streams

depending on connected data-source

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

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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More resources

Recent citations in the news

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26 June 2024, Business Wire

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Apache® Druid Wins Best Big Data Product in the 2023 BigDATAwire Readers’ Choice Awards
26 January 2024, Business Wire

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21 August 2019, AWS Blog

AWS and IBM Netezza come out in support of Iceberg in table format face-off
1 August 2023, The Register

Copy data from Netezza to Azure with Azure Data Factory
9 September 2019, Microsoft

IBM Completes Acquisition of Netezza
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Trinity College spinout TerminusDB secures €3.6m in investment
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The Perfect AI Storage: Trino From Facebook And Iceberg From Netflix?
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A look at Presto, Trino SQL query engines
9 August 2022, TechTarget

Trino: The Open-source Data Query Engine That Split from Facebook
30 March 2022, hackernoon.com

Query big data with resilience using Trino in Amazon EMR with Amazon EC2 Spot Instances for less cost
4 October 2023, AWS Blog

Starburst accelerates Trino to ‘Warp Speed’ to accelerate data querying
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provided by Google News

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