DBMS > Cachelot.io vs. Trino vs. Vertica vs. Yanza

System Properties Comparison Cachelot.io vs. Trino vs. Vertica vs. Yanza

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Editorial information provided by DB-Engines

Name

Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

In-memory caching system

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

Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.

Time Series DBMS for IoT Applications

Primary database model

Key-value store

Relational DBMS

Column oriented

Time Series DBMS

Secondary database models

Document store
Key-value store
Spatial DBMS
Search engine
Time Series DBMS
Wide column store

Spatial DBMS
Time Series DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.00
Rank	#385	Overall
	#61	Key-value stores

Score	5.28
Rank	#61	Overall
	#35	Relational DBMS

Score	9.62
Rank	#42	Overall
	#26	Relational DBMS

Website

cachelot.io

trino.io

www.vertica.com

yanza.com

Technical documentation

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

vertica.com/documentation

Developer

Trino Software Foundation

OpenText

previously Micro Focus and Hewlett Packard

Yanza

Initial release

2015

2012

2020 rebranded from PrestoSQL

2005

2015

Current release

12.0.3, January 2023

License

Commercial or Open Source

Open Source

Simplified BSD License

Open Source

Apache Version 2.0

commercial

Limited community edition free

commercial

free version available

Cloud-based only

Only available as a cloud service

on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers

but mainly used as a service provided by Yanza

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Java

C++

Server operating systems

FreeBSD
Linux
OS X

Linux
macOS

for devlopment

Linux

Windows

Data scheme

schema-free

yes

Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.

schema-free

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

depending on connected data-source

No Indexes Required. Different internal optimization strategy, but same functionality included.

SQL

Support of SQL

yes

Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.

APIs and other access methods

Memcached protocol

JDBC
RESTful HTTP API
Trino CLI

ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL

character-based, interactive, front-end utility

HTTP API

Supported programming languages

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
OCaml
Perl
PHP
Python
Ruby

Go
Java
JavaScript (Node.js)
Python
R
Ruby

C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R

any language that supports HTTP calls

Server-side scripts

Stored procedures

yes, depending on connected data-source

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes, called Custom Alerts

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

none

depending on connected data-source

horizontal partitioning, hierarchical partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

depending on connected data-source

Multi-source replication

One, or more copies of data replicated across nodes, or object-store used for repository.

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Bi-directional Spark integration

Consistency concepts

Methods to ensure consistency in a distributed system

none

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

depending on connected data-source

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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.

User concepts

Access control

SQL standard access control

fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

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

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More resources

Recent citations in the news

The Perfect AI Storage: Trino From Facebook And Iceberg From Netflix?
30 April 2024, The Next Platform

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
8 February 2023, VentureBeat

provided by Google News

Vertica on Kubernetes
20 June 2024, blogs.opentext.com

OpenText Analytics Database: The ELT Advantage
9 August 2024, blogs.opentext.com

MapR Hadoop Upgrade Spins YARN, Supports HP Vertica Analytics Platform
31 May 2024, Data Center Knowledge

Stonebraker Seeks to Invert the Computing Paradigm with DBOS
12 March 2024, Datanami

What’s New in OpenText Vertica
10 January 2024, blogs.opentext.com

provided by Google News

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