DBMS > Hazelcast vs. Redis vs. Sphinx vs. Tarantool

System Properties Comparison Hazelcast vs. Redis vs. Sphinx vs. Tarantool

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

A widely adopted in-memory data grid

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.

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

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

Primary database model

Key-value store

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

Search engine

Document store
Key-value store
Relational DBMS

Secondary database models

Document store

JSON support with IMDG 3.12

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	6.87
Rank	#55	Overall
	#6	Key-value stores

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

Score	6.03
Rank	#60	Overall
	#6	Search engines

Score	1.67
Rank	#150	Overall
	#25	Document stores
	#25	Key-value stores
	#69	Relational DBMS

Website

Technical documentation

hazelcast.org/imdg/docs

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

sphinxsearch.com/docs

www.tarantool.io/en/doc

Developer

Hazelcast

Redis project core team, inspired by Salvatore Sanfilippo

Development sponsored by Redis Inc.

Sphinx Technologies Inc.

Initial release

2008

2009

2001

2008

Current release

5.3.6, November 2023

7.2.4, January 2024

3.5.1, February 2023

2.10.0, May 2022

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

Open Source

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

Open Source

GPL version 2, commercial licence available

Open Source

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

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

Java

C++

C and C++

Server operating systems

All OS with a Java VM

BSD
Linux
OS X
Windows

ported and maintained by Microsoft Open Technologies, Inc.

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

BSD
Linux
macOS

Data scheme

schema-free

yes

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

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

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

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

the object must implement a serialization strategy

Secondary indexes

yes

with RediSearch module

yes

full-text index on all search fields

yes

SQL

Support of SQL

SQL-like query language

with RediSQL module

SQL-like query language (SphinxQL)

Full-featured ANSI SQL support

APIs and other access methods

JCache
JPA
Memcached protocol
RESTful HTTP API

proprietary protocol

RESP - REdis Serialization Protocol

Proprietary protocol

Open binary protocol

Supported programming languages

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
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++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

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

Server-side scripts

Stored procedures

yes

Event Listeners, Executor Services

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

Lua, C and SQL stored procedures

Triggers

yes

Events

publish/subscribe channels provide some trigger functionality; RedisGears

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

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

Sharding

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

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

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Replicated Map

Multi-source replication

with Redis Enterprise Pack
Source-replica replication

Chained replication is supported

none

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

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 or Eventual Consistency selectable by user

Raft Consensus Algorithm

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

one or two-phase-commit; repeatable reads; read commited

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

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

yes

yes, cooperative multitasking

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, write ahead logging

In-memory capabilities

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

yes

yes, full featured in-memory storage engine with persistence

User concepts

Access control

Role-based access control

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

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.