DBMS > Citus vs. Microsoft Azure Data Explorer vs. Newts vs. RocksDB vs. Trino

System Properties Comparison Citus vs. Microsoft Azure Data Explorer vs. Newts vs. RocksDB vs. Trino

Editorial information provided by DB-Engines

Name

Description

Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQL

Fully managed big data interactive analytics platform

Time Series DBMS based on Cassandra

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

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

Primary database model

column oriented

Secondary database models

Document store

If a column is of type dynamic docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types/dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store

this is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine

support for complex search expressions docs.microsoft.com/en-us/azure/kusto/query/parseoperator FTS, Geospatial docs.microsoft.com/en-us/azure/kusto/query/geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS

see docs.microsoft.com/en-us/azure/data-explorer/time-series-analysis

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	2.15
Rank	#117	Overall
	#56	Relational DBMS

Score	3.80
Rank	#81	Overall
	#43	Relational DBMS

Score	0.07
Rank	#375	Overall
	#41	Time Series DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Score	4.99
Rank	#65	Overall
	#36	Relational DBMS

Website

www.citusdata.com

azure.microsoft.com/services/data-explorer

opennms.github.io/newts

rocksdb.org

trino.io

Technical documentation

docs.citusdata.com

docs.microsoft.com/en-us/azure/data-explorer

github.com/OpenNMS/newts/wiki

github.com/facebook/rocksdb/wiki

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

Social network pages

Developer

Microsoft

OpenNMS Group

Facebook, Inc.

Trino Software Foundation

Initial release

2010

2019

2014

2013

2012

2020 rebranded from PrestoSQL

Current release

8.1, December 2018

cloud service with continuous releases

9.2.1, May 2024

License

Commercial or Open Source

Open Source

AGPL, commercial license also available

commercial

Open Source

Apache 2.0

Open Source

BSD

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

C++

Java

Server operating systems

Linux

hosted

Linux
OS X
Windows

Linux

Linux
macOS

for devlopment

Data scheme

yes

Fixed schema with schema-less datatypes (dynamic)

schema-free

yes

Typing

predefined data types such as float or date

yes

bool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types

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

specific XML type available, but no XML query functionality

yes

Secondary indexes

yes

all fields are automatically indexed

depending on connected data-source

SQL

Support of SQL

yes

standard, with numerous extensions

Kusto Query Language (KQL), SQL subset

yes

APIs and other access methods

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API

HTTP REST
Java API

C++ API
Java API

JDBC
RESTful HTTP API
Trino CLI

Supported programming languages

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R

Java

C
C++
Go
Java
Perl
Python
Ruby

Go
Java
JavaScript (Node.js)
Python
R
Ruby

Server-side scripts

Stored procedures

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

Yes, possible languages: KQL, Python, R

yes, depending on connected data-source

Triggers

yes

see docs.microsoft.com/en-us/azure/kusto/management/updatepolicy

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

based on Cassandra

horizontal partitioning

depending on connected data-source

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

other methods possible by using 3rd party extensions

yes

Implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

selectable replication factor

based on Cassandra

yes

depending on connected data-source

MapReduce

Offers an API for user-defined Map/Reduce methods

Spark connector (open source): github.com/Azure/azure-kusto-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

depending on connected data-source

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

depending on connected data-source

Concurrency

Support for concurrent manipulation of data

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

User concepts

Access control

fine grained access rights according to SQL-standard

Azure Active Directory Authentication

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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6 June 2024

60: Trino calling AI
22 May 2024

Big names round out the Trino Fest 2024 lineup
8 May 2024

59: Querying Trino with Java and jOOQ
24 April 2024

A sneak peek of Trino Fest 2024
15 April 2024

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