DBMS > GridGain vs. Redis vs. Tarantool vs. UniData,UniVerse

System Properties Comparison GridGain vs. Redis vs. Tarantool vs. UniData,UniVerse

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Editorial information provided by DB-Engines

Name

Description

GridGain is an in-memory computing platform, built on Apache Ignite

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
Relational 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

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	1.55
Rank	#150	Overall
	#26	Key-value stores
	#70	Relational DBMS

Score	155.94
Rank	#6	Overall
	#1	Key-value stores

Score	1.67
Rank	#143	Overall
	#25	Document stores
	#25	Key-value stores
	#65	Relational DBMS

Score	2.85
Rank	#98	Overall
	#1	Multivalue DBMS

Website

www.gridgain.com

redis.com
redis.io

www.tarantool.io

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

Technical documentation

www.gridgain.com/docs/index.html

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

GridGain Systems, Inc.

Redis project core team, inspired by Salvatore Sanfilippo

Development sponsored by Redis Inc.

Rocket Software

Initial release

2007

2009

2008

1985

Current release

GridGain 8.5.1

7.2.5, May 2024

2.10.0, May 2022

License

Commercial or Open Source

commercial

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

Java, C++, .Net

C and C++

Server operating systems

Linux
OS X
Solaris
Windows

BSD
Linux
OS X
Windows

ported and maintained by Microsoft Open Technologies, Inc.

BSD
Linux
macOS

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

yes

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

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

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.

yes

Secondary indexes

yes

with RediSearch module

yes

SQL

Support of SQL

ANSI-99 for query and DML statements, subset of DDL

with RediSQL module

Full-featured ANSI SQL support

yes

APIs and other access methods

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

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

C#
C++
Java
PHP
Python
Ruby
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

yes (compute grid and cache interceptors can be used instead)

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

Lua, C and SQL stored procedures

yes

Triggers

yes (cache interceptors and events)

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

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

yes (replicated cache)

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

yes (compute grid and hadoop accelerator)

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

ACID

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

yes, full featured in-memory storage engine with persistence

User concepts

Access control

Security Hooks for custom implementations

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

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