DBMS > ClickHouse vs. Redis vs. SpaceTime vs. Sphinx vs. Warp 10

System Properties Comparison ClickHouse vs. Redis vs. SpaceTime vs. Sphinx vs. Warp 10

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.

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.

SpaceTime is a spatio-temporal DBMS with a focus on performance.

Open source search engine for searching in data from different sources, e.g. relational databases

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

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

Spatial DBMS

Search engine

Time Series 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

Relational DBMS

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

Score	16.34
Rank	#38	Overall
	#23	Relational DBMS

Score	157.80
Rank	#6	Overall
	#1	Key-value stores

Score	0.00
Rank	#383	Overall
	#7	Spatial DBMS

Score	5.98
Rank	#56	Overall
	#5	Search engines

Score	0.07
Rank	#349	Overall
	#32	Time Series DBMS

Website

clickhouse.com

redis.com
redis.io

www.mireo.com/spacetime

sphinxsearch.com

www.warp10.io

Technical documentation

clickhouse.com/docs

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

sphinxsearch.com/docs

www.warp10.io/content/02_Getting_started

Developer

Clickhouse Inc.

Redis project core team, inspired by Salvatore Sanfilippo

Development sponsored by Redis Inc.

Mireo

Sphinx Technologies Inc.

SenX

Initial release

2016

2009

2020

2001

2015

Current release

v24.4.1.2088-stable, May 2024

7.2.4, January 2024

3.5.1, February 2023

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

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

commercial

Open Source

GPL version 2, commercial licence available

Open Source

Apache License 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.

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.

Implementation language

C++

Java

Server operating systems

FreeBSD
Linux
macOS

BSD
Linux
OS X
Windows

ported and maintained by Microsoft Open Technologies, Inc.

Linux

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

schema-free

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.

Secondary indexes

yes

with RediSearch module

yes

full-text index on all search fields

SQL

Support of SQL

Close to ANSI SQL (SQL/JSON + extensions)

with RediSQL module

A subset of ANSI SQL is implemented

SQL-like query language (SphinxQL)

APIs and other access methods

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

proprietary protocol

RESP - REdis Serialization Protocol

RESTful HTTP API

Proprietary protocol

HTTP API
Jupyter
WebSocket

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#
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

C#
C++
Python

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

yes

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

yes

WarpScript

Triggers

publish/subscribe channels provide some trigger functionality; RedisGears

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

Fixed-grid hypercubes

Sharding

Partitioning is done manually, search queries against distributed index is supported

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

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

Multi-source replication

with Redis Enterprise Pack
Source-replica replication

Chained replication is supported

Real-time block device replication (DRBD)

none

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

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

based on HBase

Foreign keys

Referential integrity

Transaction concepts

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

Atomic execution of command blocks and scripts and optimistic locking

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

The original contents of fields are not stored in the Sphinx index.

yes

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.

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

yes

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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