DBMS > ClickHouse vs. Netezza vs. Redis vs. Snowflake vs. Trino

System Properties Comparison ClickHouse vs. Netezza vs. Redis vs. Snowflake vs. Trino

Editorial information provided by DB-Engines

Name

Description

A high-performance, column-oriented SQL DBMS for online analytical processing (OLAP) that uses all available system resources to their full potential to process each analytical query as fast as possible. It is available as both an open-source software and a cloud offering.

Data warehouse and analytics appliance part of IBM PureSystems

Popular in-memory data platform used as a cache, message broker, and database that can be deployed on-premises, across clouds, and hybrid environments

Redis focuses on performance so most of its design decisions prioritize high performance and very low latencies.

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

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

Primary database model

Relational DBMS

Key-value store

Multiple data types and a rich set of operations, as well as configurable data expiration, eviction and persistence

Relational DBMS

Secondary database models

Time Series DBMS

Document store

with RedisJSON
Graph DBMS

with RedisGraph
Spatial DBMS
Search engine

with RediSearch
Time Series DBMS

with RedisTimeSeries
Vector 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	16.20
Rank	#37	Overall
	#23	Relational DBMS

Score	10.18
Rank	#46	Overall
	#29	Relational DBMS

Score	156.44
Rank	#6	Overall
	#1	Key-value stores

Score	123.20
Rank	#9	Overall
	#6	Relational DBMS

Score	5.10
Rank	#70	Overall
	#38	Relational DBMS

Website

clickhouse.com

www.ibm.com/products/netezza

redis.com
redis.io

www.snowflake.com

trino.io

Technical documentation

clickhouse.com/docs

docs.redis.com/latest/index.html
redis.io/docs

docs.snowflake.net/manuals/index.html

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

Social network pages

Developer

Clickhouse Inc.

IBM

Redis project core team, inspired by Salvatore Sanfilippo

Development sponsored by Redis Inc.

Snowflake Computing Inc.

Trino Software Foundation

Initial release

2016

2000

2009

2014

2012

2020 rebranded from PrestoSQL

Current release

v24.3.2.23-lts, April 2024

7.2.4, January 2024

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

source-available extensions (modules), commercial licenses for Redis Enterprise

commercial

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.

Aiven for Clickhouse: Managed cloud data warehousing with high-speed analytics.
ClickHouse Cloud: Get the performance you love from open source ClickHouse in a serverless offering that takes care of the details so you can spend more time getting insight out of the fastest database on earth.
DoubleCloud: Fully managed ClickHouse alongside best-in-class managed open-source services to build analytics at scale.

Aiven for Redis: Fully managed in-memory key-value store for all your caching and speedy lookup needs.

Starburst Galaxy offers a feature-rich user interface to connect all your data sources, manage your Trino clusters, and query your data.

Implementation language

C++

Java

Server operating systems

FreeBSD
Linux
macOS

Linux

included in appliance

BSD
Linux
OS X
Windows

ported and maintained by Microsoft Open Technologies, Inc.

hosted

Linux
macOS

for devlopment

Data scheme

yes

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

yes

Typing

predefined data types such as float or date

yes

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

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

with RediSearch module

depending on connected data-source

SQL

Support of SQL

Close to ANSI SQL (SQL/JSON + extensions)

yes

with RediSQL module

yes

APIs and other access methods

gRPC
HTTP REST
JDBC
MySQL wire protocol
ODBC
PostgreSQL wire protocol
Proprietary protocol

JDBC
ODBC
OLE DB

proprietary protocol

RESP - REdis Serialization Protocol

CLI Client
JDBC
ODBC

JDBC
RESTful HTTP API
Trino CLI

Supported programming languages

3rd party library
C++
Elixir

3rd party library
Go

3rd party library
Java

3rd party library
JavaScript (Node.js)

3rd party library
Kotlin

3rd party library
Nim

3rd party library
Perl

3rd party library
PHP

3rd party library
Python

3rd party library
R

3rd party library
Ruby

3rd party library
Rust
Scala

3rd party library

C
C++
Fortran
Java
Lua
Perl
Python
R

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

JavaScript (Node.js)
Python

Go
Java
JavaScript (Node.js)
Python
R
Ruby

Server-side scripts

Stored procedures

yes

Lua; Redis Functions coming in Redis 7 (slides and Github)

user defined functions

yes, depending on connected data-source

Triggers

publish/subscribe channels provide some trigger functionality; RedisGears

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

key based and custom

Sharding

Automatic hash-based sharding with support for hash-tags for manual sharding

yes

depending on connected data-source

Replication methods

Methods for redundantly storing data on multiple nodes

Asynchronous and synchronous physical replication; geographically distributed replicas; support for object storages.

Source-replica replication

Multi-source replication

with Redis Enterprise Pack
Source-replica replication

Chained replication is supported

yes

depending on connected data-source

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

through RedisGears

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Causal consistency can be enabled in Active-Active databases
Strong consistency with Redis Raft
Strong eventual consistency with Active-Active

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

Atomic execution of command blocks and scripts and optimistic locking

ACID

depending on connected data-source

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

yes

Durability

Support for making data persistent

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

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

Access rights for users and roles. Column and row based policies. Quotas and resource limits. Pluggable authentication with LDAP and Kerberos. Password based, X.509 certificate, and SSH key authentication.

Users with fine-grained authorization concept

Access Control Lists (ACLs): redis.io/docs/management/security/acl
LDAP and Role-Based Access Control (RBAC) for Redis Enterprise
Mutual TLS authentication: redis.io/docs/management/security/encryption
Password-based authentication

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

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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

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