DBMS > IBM Cloudant vs. OpenQM vs. RDF4J vs. Redis vs. YugabyteDB

System Properties Comparison IBM Cloudant vs. OpenQM vs. RDF4J vs. Redis vs. YugabyteDB

Editorial information provided by DB-Engines

Name

Description

Database as a Service offering based on Apache CouchDB

QpenQM is a high-performance, self-tuning, multi-value DBMS

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

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.

High-performance distributed SQL database for global, internet-scale applications. Wire and feature compatible with PostgreSQL.

Primary database model

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

Relational 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

Document store
Wide column store

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

Score	2.64
Rank	#101	Overall
	#19	Document stores

Score	0.26
Rank	#293	Overall
	#10	Multivalue DBMS

Score	0.82
Rank	#208	Overall
	#7	RDF stores

Score	148.64
Rank	#6	Overall
	#1	Key-value stores

Score	2.36
Rank	#107	Overall
	#53	Relational DBMS

Website

www.ibm.com/products/cloudant

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

rdf4j.org

redis.com
redis.io

www.yugabyte.com

Technical documentation

cloud.ibm.com/docs/Cloudant

rdf4j.org/documentation

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

docs.yugabyte.com
github.com/yugabyte/yugabyte-db

Developer

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Rocket Software, originally Martin Phillips

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Redis project core team, inspired by Salvatore Sanfilippo

Development sponsored by Redis Inc.

Yugabyte Inc.

Initial release

2010

1993

2004

2009

2017

Current release

3.4-12

7.2.5, May 2024

2.19, September 2023

License

Commercial or Open Source

commercial

Open Source

GPLv2, extended commercial license available

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

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

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Erlang

Java

C and C++

Server operating systems

hosted

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Linux
OS X
Unix
Windows

BSD
Linux
OS X
Windows

ported and maintained by Microsoft Open Technologies, Inc.

Linux
OS X

Data scheme

schema-free

yes

with some exceptions

yes

RDF Schemas

schema-free

depending on used data model

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.

yes

Secondary indexes

yes

with RediSearch module

yes

SQL

Support of SQL

with RediSQL module

yes, PostgreSQL compatible

APIs and other access methods

RESTful HTTP/JSON API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

proprietary protocol

RESP - REdis Serialization Protocol

JDBC
YCQL, an SQL-based flexible-schema API with its roots in Cassandra Query Language
YSQL - a fully relational SQL API that is wire compatible with the SQL language in PostgreSQL

Supported programming languages

C#
Java
JavaScript
Objective-C
PHP
Ruby

.Net
Basic
C
Java
Objective C
PHP
Python

Java
PHP
Python

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++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust
Scala

Server-side scripts

Stored procedures

View functions (Map-Reduce) in JavaScript

yes

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

yes

sql, plpgsql, C

Triggers

yes

publish/subscribe channels provide some trigger functionality; RedisGears

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

none

Sharding

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

Hash and Range Sharding, row-level geo-partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

none

Multi-source replication

with Redis Enterprise Pack
Source-replica replication

Chained replication is supported

Based on Raft distributed consensus protocol, minimum 3 replicas for continuous availability

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

through RedisGears

Consistency concepts

Methods to ensure consistency in a distributed system

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

Strong consistency on writes and tunable consistency on reads

Foreign keys

Referential integrity

yes

Transaction concepts

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

atomic operations within a document possible

ACID

Isolation support depends on the API used

Atomic execution of command blocks and scripts and optimistic locking

Distributed ACID with Serializable & Snapshot Isolation. Inspired by Google Spanner architecture.

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

yes

Data access is serialized by the server

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

yes

based on RocksDB

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 can be defined per database

Access rights can be defined down to the item level

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

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.