DBMS > Machbase Neo vs. Microsoft Azure Cosmos DB vs. Trino vs. Yaacomo

System Properties Comparison Machbase Neo vs. Microsoft Azure Cosmos DB vs. Trino vs. Yaacomo

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Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

TimeSeries DBMS for AIoT and BigData

Globally distributed, horizontally scalable, multi-model database service

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

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Time Series DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Secondary database models

Spatial 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	0.12
Rank	#339	Overall
	#30	Time Series DBMS

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	5.00
Rank	#66	Overall
	#36	Relational DBMS

Website

machbase.com

azure.microsoft.com/services/cosmos-db

trino.io

yaacomo.com

Technical documentation

machbase.com/dbms

learn.microsoft.com/azure/cosmos-db

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

Social network pages

Developer

Machbase

Microsoft

Trino Software Foundation

Q2WEB GmbH

Initial release

2013

2014

2012

2020 rebranded from PrestoSQL

2009

Current release

V8.0, August 2023

License

Commercial or Open Source

commercial

free test version available

commercial

Open Source

Apache Version 2.0

commercial

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

Server operating systems

Linux
macOS
Windows

hosted

Linux
macOS

for devlopment

Android
Linux
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON 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.

Secondary indexes

yes

All properties auto-indexed by default

depending on connected data-source

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

JDBC
RESTful HTTP API
Trino CLI

JDBC
ODBC

Supported programming languages

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

Go
Java
JavaScript (Node.js)
Python
R
Ruby

Server-side scripts

Stored procedures

JavaScript

yes, depending on connected data-source

Triggers

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

depending on connected data-source

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

Implicit feature of the cloud service

depending on connected data-source

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

depending on connected data-source

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Multi-item ACID transactions with snapshot isolation within a partition

depending on connected data-source

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

depending on connected data-source

yes

In-memory capabilities

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

yes

volatile and lookup table

yes

User concepts

Access control

simple password-based access control

Access rights can be defined down to the item level

SQL standard access control

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

Trino is the fastest open source, massively parallel processing SQL query engine...
» more

Competitive advantages

High performance analtyics and data processing of very large data sets Powerful ANSI...
» more

Typical application scenarios

Performant analytics query engine for data warehouses, data lakes, and data lakehouses...
» more

Key customers

Trino is widely adopted across the globe as freely-available open source software....
» more

Market metrics

33000+ commits in GitHub 8200+ stargazers in GitHub 1200+ pull requests merged in...
» more

Licensing and pricing models

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

News

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

57: Seeing clearly with OpenTelemetry
14 March 2024

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