DBMS > HugeGraph vs. IRONdb vs. Oracle Coherence vs. Redis vs. ReductStore

System Properties Comparison HugeGraph vs. IRONdb vs. Oracle Coherence vs. Redis vs. ReductStore

Editorial information provided by DB-Engines

Name

IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

A fast-speed and highly-scalable Graph DBMS

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

Oracles in-memory data grid solution

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.

Designed to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.

Primary database model

Graph DBMS

Time Series DBMS

Key-value store

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

Time Series 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

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

Score	0.17
Rank	#335	Overall
	#31	Graph DBMS

Score	1.97
Rank	#129	Overall
	#22	Key-value stores

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

Score	0.05
Rank	#384	Overall
	#44	Time Series DBMS

Website

github.com/hugegraph
hugegraph.apache.org

www.circonus.com/solutions/time-series-database/

www.oracle.com/java/coherence

redis.com
redis.io

github.com/reductstore
www.reduct.store

Technical documentation

hugegraph.apache.org/docs

docs.circonus.com/irondb/category/getting-started

docs.oracle.com/en/middleware/standalone/coherence

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

www.reduct.store/docs

Developer

Baidu

Circonus LLC.

Oracle

Redis project core team, inspired by Salvatore Sanfilippo

Development sponsored by Redis Inc.

ReductStore LLC

Initial release

2018

2017

2007

2009

2023

Current release

0.9

V0.10.20, January 2018

14.1, August 2023

7.2.5, May 2024

1.9, March 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

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

Open Source

Business Source License 1.1

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 and C++

Java

C++, Rust

Server operating systems

Linux
macOS
Unix

Linux

All OS with a Java VM

BSD
Linux
OS X
Windows

ported and maintained by Microsoft Open Technologies, Inc.

Docker
Linux
macOS
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

text, numeric, histograms

yes

partial

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

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

also supports composite index and range index

yes

with RediSearch module

SQL

Support of SQL

SQL-like query language (Circonus Analytics Query Language: CAQL)

with RediSQL module

APIs and other access methods

Java API
RESTful HTTP API
TinkerPop Gremlin

HTTP API

JCache
JPA
RESTful HTTP API

proprietary protocol

RESP - REdis Serialization Protocol

HTTP API

Supported programming languages

Groovy
Java
Python

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

.Net
C++
Java

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++
JavaScript (Node.js)
Python
Rust

Server-side scripts

Stored procedures

asynchronous Gremlin script jobs

yes, in Lua

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

Triggers

yes

Live Events

publish/subscribe channels provide some trigger functionality; RedisGears

Partitioning methods

Methods for storing different data on different nodes

yes

depending on used storage backend, e.g. Cassandra and HBase

Automatic, metric affinity per node

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

yes

depending on used storage backend, e.g. Cassandra and HBase

configurable replication factor, datacenter aware

yes, with selectable consistency level

Multi-source replication

with Redis Enterprise Pack
Source-replica replication

Chained replication is supported

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

through RedisGears

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate consistency per node, eventual consistency across nodes

Eventual Consistency
Immediate Consistency

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

Foreign keys

Referential integrity

yes

edges in graph

Transaction concepts

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

ACID

configurable

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

Durability

Support for making data persistent

yes

optionally

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

In-memory capabilities

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

yes

User concepts

Access control

Users, roles and permissions

authentification to access the cache via certificates or http basic 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

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