DBMS > etcd vs. InfluxDB vs. Redis vs. Tarantool vs. UniData,UniVerse

System Properties Comparison etcd vs. InfluxDB vs. Redis vs. Tarantool vs. UniData,UniVerse

Editorial information provided by DB-Engines

Name

Description

DBMS for storing time series, events and metrics

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.

In-memory computing platform with a flexible data schema for efficiently building high-performance applications

MultiValue database and application server with SQL mapping layer and meta database capabilities

Primary database model

Key-value store

Time Series DBMS

Key-value store

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

Document store
Key-value store
Relational DBMS

Multivalue DBMS

Secondary database models

Spatial DBMS

with GEO package

Document store

with RedisJSON
Graph DBMS

with RedisGraph
Spatial DBMS
Search engine

with RediSearch
Time Series DBMS

with RedisTimeSeries
Vector DBMS

Spatial DBMS

with Tarantool/GIS extension

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

Score	7.25
Rank	#54	Overall
	#5	Key-value stores

Score	25.83
Rank	#28	Overall
	#1	Time Series DBMS

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

Score	1.72
Rank	#144	Overall
	#25	Document stores
	#25	Key-value stores
	#66	Relational DBMS

Score	3.16
Rank	#97	Overall
	#2	Multivalue DBMS

Website

etcd.io
github.com/etcd-io/etcd

www.influxdata.com/products/influxdb-overview

redis.com
redis.io

www.tarantool.io

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-unidata

Technical documentation

etcd.io/docs
github.com/etcd-io/etcd/tree/master/Documentation

docs.influxdata.com/influxdb

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

www.tarantool.io/en/doc

docs.rocketsoftware.com/bundle?cluster=true&labelkey=unidata&labelkey=prod_unidata

Developer

Redis project core team, inspired by Salvatore Sanfilippo

Development sponsored by Redis Inc.

Rocket Software

Initial release

2013

2009

2008

1985

Current release

3.4, August 2019

2.7.6, April 2024

7.2.4, January 2024

2.10.0, May 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

MIT-License; commercial enterprise version available

Open Source

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

Open Source

BSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise

commercial

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

Implementation language

C and C++

Server operating systems

FreeBSD
Linux
Windows

experimental

Linux
OS X

through Homebrew

BSD
Linux
OS X
Windows

ported and maintained by Microsoft Open Technologies, Inc.

BSD
Linux
macOS

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

schema-free

Flexible data schema: relational definition for tables with ability to store json-like documents in columns

schema-free

Typing

predefined data types such as float or date

Numeric data and Strings

partial

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

string, double, decimal, uuid, integer, blob, boolean, datetime

optional

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

SQL

Support of SQL

SQL-like query language

with RediSQL module

Full-featured ANSI SQL support

yes

APIs and other access methods

gRPC
JSON over HTTP

HTTP API
JSON over UDP

proprietary protocol

RESP - REdis Serialization Protocol

Open binary protocol

Java API

JPA
JDBC
ODBC
OLE DB
Proprietary protocol
RESTful HTTP API
SOAP-based API

Supported programming languages

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl

.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala

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#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust

.Net
Basic

U2 Basic
C
Java

Server-side scripts

Stored procedures

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

Lua, C and SQL stored procedures

yes

Triggers

yes, watching key changes

publish/subscribe channels provide some trigger functionality; RedisGears

yes, before/after data modification events, on replication events, client session events

yes

U2 Basic

Partitioning methods

Methods for storing different data on different nodes

Sharding

in enterprise version only

Sharding

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

Sharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.

none

Replication methods

Methods for redundantly storing data on multiple nodes

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

selectable replication factor

in enterprise version only

Multi-source replication

with Redis Enterprise Pack
Source-replica replication

Chained replication is supported

Asynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)

Source-replica replication

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

Casual consistency across sharding partitions
Eventual consistency within replicaset partition

when using asyncronous replication
Immediate Consistency within single instance
Sequential consistency including linearizable read within replicaset partition

when using Raft

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic execution of command blocks and scripts and optimistic locking

ACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions

ACID

configurable

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

yes, cooperative multitasking

yes

Durability

Support for making data persistent

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

yes, write ahead logging

yes

In-memory capabilities

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

yes

Depending on used storage engine

yes

yes, full featured in-memory storage engine with persistence

User concepts

Access control

simple rights management via user accounts

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

Access Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles

Access rights according to SQL-standard and operating system based

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Market metrics

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Licensing and pricing models

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